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The Effect of a Chameleon Scalar Field on the Cosmic Microwave Background

Anne-Christine Davis a.c.davis@damtp.cam.ac.uk Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, Cambridge CB3 0WA, United Kingdom    Camilla A.O. Schelpe C.A.O.Schelpe@damtp.cam.ac.uk Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, Cambridge CB3 0WA, United Kingdom    Douglas J. Shaw D.Shaw@qmul.ac.uk Queen Mary University of London, Astronomy Unit, Mile End Road, London E1 4NS, United Kingdom
(July 30, 2025)
Abstract

We show that a direct coupling between a chameleon-like scalar field and photons can give rise to a modified Sunyaev–Zel’dovich (SZ) effect in the Cosmic Microwave Background (CMB). The coupling induces a mixing between chameleon particles and the CMB photons when they pass through the magnetic field of a galaxy cluster. Both the intensity and the polarization of the radiation are modified. The degree of modification depends strongly on the properties of the galaxy cluster such as magnetic field strength and electron number density. Existing SZ measurements of the Coma cluster enable us to place constraints on the photon-chameleon coupling. The constrained conversion probability in the cluster is 𝒫Coma(204GHz)<6.2×105{\mathcal{P}}_{\rm Coma}(204\,{\rm GHz})<6.2\times 10^{-5} at 95%95\% confidence, corresponding to an upper bound on the coupling strength of geff(cell)<2.2×108GeV1g_{\rm eff}^{\rm(cell)}<2.2\times 10^{-8}\,{\rm GeV}^{-1} or geff(Kolmo)<(7.232.5)×1010GeV1g_{\rm eff}^{\rm(Kolmo)}<(7.2-32.5)\times 10^{-10}\,{\rm GeV}^{-1}, depending on the model that is assumed for the cluster magnetic field structure. We predict the radial profile of the chameleonic CMB intensity decrement. We find that the chameleon effect extends further towards the edges of the cluster than the thermal SZ effect. Thus we might see a discrepancy between the X-ray emission data and the observed SZ intensity decrement. We further predict the expected change to the CMB polarization arising from the existence of a chameleon-like scalar field. These predictions could be verified or constrained by future CMB experiments.

I Introduction

Measurements of the current cosmic acceleration of the universe have led to theories of an unknown energy component with negative pressure in the Universe. This dark energy is generally modelled by a scalar field rolling down a flat potential. On Solar-system scales this scalar field should appear effectively massless. The origin of the dark energy scalar field is still highly speculative; some suggestions have involved the moduli fields of string theory. However, if a near-massless scalar field existed on Earth it should have been detected as a fifth force unless the coupling to normal matter was unnaturally suppressed. Khoury and Weltman Khoury04 introduced the chameleon scalar field which has gravitational strength or greater coupling to normal matter but a mass which depends on the density of surrounding matter. On cosmological scales the chameleon successfully acts as a low-mass dark energy candidate, while in the laboratory its large mass allows it to evade detection.

An extension to the original chameleon model is to include an interaction term between the chameleon and electromagnetic (EM) field of the form ϕMeffFμνFμν\frac{\phi}{M_{\rm eff}}F_{\mu\nu}F^{\mu\nu}, first suggested by Brax et al. Brax07 . This leads to interconversion between chameleons and photons in the presence of a magnetic field, which alters the intensity and polarization of any radiation entering the magnetic region. A coupling between the chameleon and EM fields gives rise to observational effects that could potentially be detected either astrophysically or in the laboratory Brax07 ; BurrageSN ; Burrage08 . These predictions have lead to constraints on the mass parameter MFM_{F} describing the coupling strength to the EM field: MF2×106GeVM_{F}\gtrsim 2\times 10^{6}\,\mathrm{GeV} Brax07 and MF1.1×109GeVM_{F}\gtrsim 1.1\times 10^{9}\,\mathrm{GeV} Burrage08 .

It was noted in Ref. Burrage08 that in low density backgrounds, such as the interstellar and intra-cluster mediums, the mixing between the chameleon field and photons is indistinguishable from the mixing of any very light scalar field with a linear coupling to FμνFμνF_{\mu\nu}F^{\mu\nu} or a very light pseudo-scalar with a linear coupling to ϵμνρσFμνFρσ\epsilon_{\mu\nu\rho\sigma}F^{\mu\nu}F^{\rho\sigma}. Such fields are collectively referred to as axion-like particles (ALPs). Standard ALPs have the same mass and photon-coupling everywhere. The best constraints on their parameters come from limits on their production in relatively high density regions such as stellar cores or in supernova 1987A ALPrev . Chameleon scalar fields represent one example of a subclass of ALPs that we term chameleonic ALPs. The defining feature of chameleonic ALPs is that the astrophysical constraints from high density regions are evaded or exponentially weakened. This may be because as the ambient density increases the field mass rises as in the chameleon model, or because the effective photon coupling weakens Jaeckel07 ; Burrage08 . This latter possibility is realized in the Olive–Pospelov model for a density-dependent fine-structure constant Olive08 . The results we derive in this paper technically apply to all ALPs, however the parameter range for which they apply is strongly ruled out for all but chameleonic ALPs. The model for chameleon-like theories is described in detail in subsection I.1 below.

In this paper we consider the propagation of the Cosmic Microwave Background (CMB) radiation through the magnetic field of a galaxy cluster. We predict the modification to the CMB intensity and polarization in the direction of galaxy clusters arising from mixing with a chameleonic ALP.

One of the significant foreground effects acting on the CMB as it passes through a galaxy cluster, which has been extensively verified by experiment, is the Sunyaev–Zel’dovich (SZ) effect. This arises from scattering of CMB photons off electrons in the galaxy cluster atmosphere, causing a change to the CMB intensity in the direction of the cluster. Measurements of the SZ effect can be compared to predictions of the CMB intensity decrement arising from the chameleon, and thus constrain the chameleon model parameters.

This paper is organized as follows: in §II, the conversion between photons and a general scalar ALP in a magnetic field is analysed, and note how it depends on the structure of the magnetic field. In §III, we briefly review the observational evidence for magnetic fields in the intra-cluster medium (ICM) and detail their typical properties. In §IV, we describe the standard SZ effect and show how this is modified when photons are converted to (chameleonic) ALPs in the intra-cluster medium. We note that the frequency and electron density dependence of the chameleonic SZ effect differs from that of the thermal and other standard contributions to the SZ effect. In §V, we exploit this difference to constrain the probability of photon-scalar conversion in the ICM. Under certain reasonable assumptions about the magnetic field structure, we convert these constraints to bounds on the effective photon to scalar coupling. In §VI we discuss the modification to the CMB polarization from chameleon-mixing. We summarize our results in §VII.

I.1 Chameleon-like Theories

Chameleon-like-theories, which include the standard chameleon model introduced by Khoury and Weltman Khoury04 as well as the Olive–Pospelov, varying αem\alpha_{\rm em} model Olive08 , are essentially generalized scalar-tensor theories and as such are described by the following action:

𝒮\displaystyle\mathcal{S} =\displaystyle= d4xg(MPl2212gμνμϕνϕ\displaystyle\int\mathrm{d}^{4}x\sqrt{-g}\left(\frac{M_{Pl}^{2}}{2}\mathcal{R}-\frac{1}{2}g^{\mu\nu}\partial_{\mu}\phi\partial_{\nu}\phi\right.
V(ϕ)14BF(ϕ/M)FμνFμν)\displaystyle\left.-V(\phi)-\frac{1}{4}B_{F}(\phi/M)F_{\mu\nu}F^{\mu\nu}\right)
+𝒮matter(ψ(i),Bi2(ϕ/M)gμν),\displaystyle+\mathcal{S}_{\mathrm{matter}}\left(\psi^{(i)},B^{2}_{i}(\phi/M)g_{\mu\nu}\right)\,,

where the ψi\psi_{i} are the matter fields and 𝒮matter\mathcal{S}_{\rm matter} is the matter action (excluding the kinetic term of electromagnetism). The Bi(ϕ/M)B_{i}(\phi/M) determine the coupling of the scalar, ϕ\phi, to different matter species; BF(ϕ/M)B_{F}(\phi/M) determines the photon-scalar coupling. For simplicity we assume a universal matter coupling Bi(ϕ/M)=Bm(ϕ/M)B_{i}(\phi/M)=B_{\rm m}(\phi/M), although we do not require that Bm=BFB_{\rm m}=B_{F}. Varying this action with respect to ϕ\phi gives the scalar field equation:

ϕ=Veffϕ(ϕ;F2,Tm),\displaystyle\square\phi=\frac{\partial V_{\rm eff}}{\partial\phi}(\phi;F^{2},T_{\rm m}), (2)

where

Veff(ϕ;F2,Tm)V(ϕ)+BF(ϕ)4F2+Bm(ϕ)Tm.V_{\rm eff}(\phi;F^{2},T_{\rm m})\equiv V(\phi)+\frac{B_{F}(\phi)}{4}F^{2}+B_{\rm m}(\phi)T_{\rm m}.

Here Tm=ρm3PmT_{\rm m}=\rho_{\rm m}-3P_{\rm m}, is the trace of the energy-momentum tensor and corresponds to the physical, measured density or pressure. For this derivation we must remember that the particle masses are constant and independent of ϕ\phi in the conformal Jordan frame with metric gμν(i)=Bi2gμνg_{\mu\nu}^{(i)}=B^{2}_{i}g_{\mu\nu}, while the length scales are measured in the Einstein conformal frame. Thus ρm=Bi3ρJordan\rho_{\rm m}=B_{i}^{3}\rho_{\mathrm{Jordan}}.

Whether or not a given scalar-tensor theory is chameleon-like is determined by the form of its self-interaction potential, V(ϕ)V(\phi), and its coupling functions, Bm(ϕ/M)B_{\rm m}(\phi/M) and BF(ϕ/M)B_{F}(\phi/M). A simple and very general prescription is that the magnitude of small perturbations in lnBF(ϕ/M)\ln B_{F}(\phi/M) and lnBi(ϕ/M)\ln B_{i}(\phi/M) about their values at the minimum of Veff(ϕ)V_{\rm eff}(\phi), and sourced by some small perturbation in TmT_{\rm m} or F2F^{2}, decreases as TmT_{\rm m} becomes large and positive, i.e. as the ambient density increases. This implies that for any combination of i,j=F,mi,j=F,m,

Hij(F2,Tm)=|(lnBi),ϕ(ϕmin/M)(lnBj),ϕ(ϕmin/M)V,ϕϕeff(ϕmin;F2,Tm)|\displaystyle H_{ij}(F^{2},T_{\rm m})=\left|\frac{(\ln B_{i})_{,\phi}(\phi_{\rm min}/M)(\ln B_{j})_{,\phi}(\phi_{\rm min}/M)}{V_{,\phi\phi}^{\rm eff}(\phi_{\rm min};F^{2},T_{\rm m})}\right| (3)

is a decreasing function of TmT_{\rm m}, where ϕmin\phi_{\rm min} is given by V,ϕeff(ϕmin;F2,Tm)=0V_{,\phi}^{\rm eff}(\phi_{\rm min};F^{2},T_{\rm m})=0. We must also require that ϕmin\phi_{\rm min} exists and that V,ϕϕeff(ϕmin;F2,Tm)>0V_{,\phi\phi}^{\rm eff}(\phi_{\rm min};F^{2},T_{\rm m})>0 for stability.

I.1.1 The Chameleon Model

In a standard chameleon theory, we assume that ϕ/M1\phi/M\ll 1 and approximate BF1+ϕ/MeffB_{F}\approx 1+\phi/M_{\rm eff} and Bm21+2ϕ/MB_{\rm m}^{2}\approx 1+2\phi/M, where this defines MM and MeffM_{\rm eff}. We expect Meff𝒪(M)M_{\rm eff}\sim{\cal O}(M) but this does not necessarily have to be the case. Assuming Tm/M|F2|/4MeffT_{\rm m}/M\gg|F^{2}|/4M_{\rm eff}, the condition on HijH_{ij} is then equivalent to

V,ϕϕϕ<0.V_{,\phi\phi\phi}<0.

This implies that the ϕ\phi field equations will be non-linear in ϕ\phi. Additionally the existence of ϕmin\phi_{\rm min} and stability implies

V,ϕ<0,V,ϕϕ>0.V_{,\phi}<0,\qquad V_{,\phi\phi}>0.

A typical choice of potential can always be described (in the limit of ϕΛ\phi\gg\Lambda) by

V(ϕ)Λ0+Λn+4nϕn,\displaystyle V(\phi)\approx\Lambda_{0}+\frac{\Lambda^{n+4}}{n\phi^{n}}, (4)

where for reasons of naturalness ΛO(Λ0)\Lambda\sim O(\Lambda_{0}). For the chameleon field to be a suitable candidate for dark energy,

Λ0=(2.4±0.3)×103eV.\displaystyle\Lambda_{0}=(2.4\pm 0.3)\times 10^{-3}\,{\rm eV}.

A corollary of Eq. (3) in chameleon theories is that the chameleon field is heavier in dense environments than it is in sparse ones. From Eq. (2), we can see that the mass of small perturbations, mϕm_{\phi}, in the chameleon field is simply given by mϕ2=V,ϕϕeffm_{\phi}^{2}=V^{\rm eff}_{,\phi\phi}. The chameleon field, ϕ\phi, rolls along the effective potential, VeffV_{\rm eff}, and the shape of VeffV_{\rm eff} depends on the ambient density through TmT_{\rm m}. For baryonic matter under normal conditions, TmρmT_{\rm m}\approx\rho_{\rm m}, and so when, as is often the case, ρm|F2|\rho_{\rm m}\gg|F^{2}| and ϕ/M1\phi/M\ll 1 we have,

VeffV(ϕ)+(1+ϕM)ρm.\displaystyle V_{\rm eff}\approx V(\phi)+\left(1+\frac{\phi}{M}\right)\rho_{\rm m}.

A plot of this effective potential, for when V(ϕ)V(\phi) is given by Eq. (4) and n=1n=1, is shown in Fig. 1.

Refer to caption
Figure 1: The chameleon effective potential, VeffV_{\mathrm{eff}}, is the sum of the scalar potential, V(ϕ)V(\phi), and a density-dependent term Khoury04 .

From this we can see that the value of ϕ\phi at the minimum will decrease as the density of the surrounding matter, ρm\rho_{\rm m}, increases, while the curvature of the effective potential at the minimum will increase. It is clear from this that the mass of the chameleon is greater in relatively high density environments such as laboratories on Earth, while in space the chameleon field is much lighter. It is this property that allows the chameleon field to have a strong coupling to matter, yet be light enough in space to produce interesting phenomena, such as non-negligible mixing with photons, whilst being heavy enough in the laboratory to avoid being ruled out by constraints on fifth-forces. A detailed discussion of the allowed chameleon parameters is given in Ref. MotaShaw .

The best direct upper-bounds on the matter coupling 1/M1/M come simply from the requirement that the chameleon field makes a negligible contribution to standard quantum amplitudes, roughly 1/M104GeV11/M\lesssim 10^{-4}\,{\rm GeV}^{-1} MotaShaw ; BraxLight . Stronger constraints have been derived on the photon coupling geff=1/Meffg_{\rm eff}=1/M_{\rm eff}. Laser-based laboratory searches for general ALPs, such as PVLAS PVLAS , and chameleons, such as GammeV GammeV , give geff106GeV1g_{\rm eff}\lesssim 10^{-6}\,{\rm GeV}^{-1}. Constraints on the production of starlight polarization from the mixing of photons with chameleon-like particles in the galactic magnetic field currently provide the strongest upper-bound of geff<9×1010GeV1g_{\rm eff}<9\times 10^{-10}\,{\rm GeV}^{-1} Burrage08 . With such couplings and for a standard choice of potential such as Eq. (4) with nO(1)n\sim O(1), mϕ1014eVm_{\phi}\ll 10^{-14}\,{\rm eV} in the galactic and intra-cluster media.

I.1.2 The Olive–Pospelov Model

In any theory with the action of Eq. (I.1), the effective fine-structure constant, αem\alpha_{\rm em}, is proportional to 1/BF(ϕ/M)1/B_{F}(\phi/M). Observations of QSO spectra suggest that the αem\alpha_{\rm em} in dust clouds roughly 10Gyrs10\,{\rm Gyrs} ago differs by a few parts in 10610^{6} from its value today as measured in the laboratory Webb . This could be explained by either a time variation VaryingAlpha in αem\alpha_{\rm em}, or a density dependence Olive08 since the clouds are much sparser than the laboratory environment. In standard chameleon theories the variation in αem\alpha_{\rm em} is constrained to be well below the level that can be detected, and so cannot explain this observation. Olive and Pospelov suggested a chameleon-like model in which a 𝒪(106){\cal O}(10^{-6}) change in αem\alpha_{\rm em} (or any other constant of nature) from dense to very sparse environments is feasible. This model has,

BF\displaystyle B_{F} =\displaystyle= 1+ξF2(ϕϕmM)2,\displaystyle 1+\frac{\xi_{F}}{2}\left(\frac{\phi-\phi_{\rm m}}{M}\right)^{2},
Bm\displaystyle B_{\rm m} =\displaystyle= 1+12(ϕϕmM)2,\displaystyle 1+\frac{1}{2}\left(\frac{\phi-\phi_{\rm m}}{M}\right)^{2},

where ξF\xi_{F} is an 𝒪(1){\cal O}(1) constant. Whilst one may consider more complicated choices for the potential, a simple choice satisfying all the required conditions is V(ϕ)=const+m2ϕ2/2V(\phi)={\rm const}+m^{2}\phi^{2}/2. In low density environments such as the interstellar or intra-cluster media ϕmin0\phi_{\rm min}\approx 0, while in high density environments such as the laboratory ϕminϕm\phi_{\rm min}\approx\phi_{\rm m}. The total fractional change in αem\alpha_{\rm em} from high to low density environments in this model is then δα/αξFϕm2/2M2\delta\alpha/\alpha\simeq\xi_{F}\phi_{\rm m}^{2}/2M^{2}.

The effective photon coupling in low density environments is

geff\displaystyle g_{\rm eff} =\displaystyle= 1/Meff(lnBF),ϕ(ϕmin/M)\displaystyle 1/M_{\rm eff}\equiv(\ln B_{F})_{,\phi}(\phi_{\rm min}/M)
\displaystyle\simeq BF,ϕ(ϕmin/M)103ξF1/2M|δα106α|1/2.\displaystyle B_{F,\phi}(\phi_{\rm min}/M)\approx\frac{10^{-3}\xi_{\rm F}^{1/2}}{M}\left|\frac{\delta\alpha}{10^{-6}\alpha}\right|^{1/2}.

In high density backgrounds geffg_{\rm eff} is much smaller. In low density backgrounds, the mass of the Olive–Pospelov scalar, mϕm2m_{\phi}\simeq m^{2} and the constraints found in Ref. Burrage08 imply mϕ1014eVm_{\phi}\ll 10^{-14}\,{\rm eV}. For the Olive–Pospelov model to satisfy all current experimental constraints, 1/M1/M must be neither too large nor too small. Olive and Pospelov gave the lower-bound 1/M109GeV11/M\gg 10^{-9}\,{\rm GeV}^{-1}, which for δα/αO(106)\delta\alpha/\alpha\sim O(10^{-6}) implies geff1012GeV1g_{\rm eff}\gg 10^{-12}\,{\rm GeV}^{-1}. Laboratory tests such as GammeV and PVLAS are insensitive to OP scalar fields, because at their relatively high operating densities the scalar-photon coupling is greatly suppressed. The best upper-bound on geffg_{\rm eff} comes, as with standard chameleon fields, from limits on the production of starlight polarization in the galaxy. Thus if the OP model is to explain a 10610^{-6} change in αem\alpha_{\rm em} as suggested by observations of QSO spectra, we must have 1012GeV1geff<9×1010GeV10^{-12}\,{\rm GeV}^{-1}\ll g_{\rm eff}<9\times 10^{-10}\,{\rm GeV}.

II Optics with a scalar Axion-Like Particle

In the presence of an axion-like particle (ALP), the properties of electromagnetic radiation propagating through a magnetic field are altered as a result of mixing between the ALP and photons. Over the past 25 years or so, there has been a great deal of work on this subject; for example Refs. Silkvie84 ; Raffelt88 ; Harai92 ; Burrage08 or see Ref. ALPrev for a recent review.

In this section, we present the equations which describe the mixing of a chameleon-like particle with the photon field in the presence of a magnetic field. We also present the solution of these equations, in the limit where the mixing is weak, for two different models of the magnetic field structure in the ICM.

Varying the action in Eq. (I.1) with respect to both ϕ\phi and AμA_{\mu}, we find Eq. (2) and

μ[BF(ϕ/M)Fμν]\displaystyle\nabla_{\mu}\left[B_{F}(\phi/M)F^{\mu\nu}\right] =\displaystyle= Jν,\displaystyle J^{\nu},

where JμJ^{\mu} is the background electromagnetic 4-current; μJμ=0\nabla_{\mu}J^{\mu}=0.

We are concerned with the propagation of light in sparse astrophysical backgrounds containing a magnetic field 𝐁(xμ)\mathbf{B}(x^{\mu}). The background values of the chameleon and photon fields are assumed to be slowly varying over length and time scales of 𝒪(1/ω){\cal O}(1/\omega) where ω\omega is the proper frequency of the electromagnetic radiation being considered. We define the perturbations in the photon and chameleon fields about their background values to be, aμ=AμA¯μa_{\mu}=A_{\mu}-\bar{A}_{\mu} and φ=ϕϕ¯\varphi=\phi-\bar{\phi}, respectively. When electromagnetic radiation propagates through a plasma with electron number density nen_{\rm e}, an effective photon mass-squared of ωpl2=4παemne/me\omega_{\rm pl}^{2}=4\pi\alpha_{\rm em}n_{e}/m_{e} is induced; ωpl\omega_{\rm pl} is the plasma frequency. Following Ref. Burrage08 in ignoring terms that are second order in the perturbations φ\varphi and aμa_{\mu}, and assuming ωH\omega\gg H where HH is the Hubble parameter, we find

𝐚¨+2𝐚\displaystyle-\ddot{\mathbf{a}}+\nabla^{2}\mathbf{a} \displaystyle\simeq φ×𝐁Meff+ωpl2𝐚,\displaystyle\frac{\boldsymbol{\nabla}\varphi\times\mathbf{B}}{M_{\rm eff}}+\omega_{\rm pl}^{2}\mathbf{a},
φ¨+2φ\displaystyle-\ddot{\varphi}+\nabla^{2}\varphi \displaystyle\simeq 𝐁(×𝐚)Meff+mϕ2φ,\displaystyle\frac{\mathbf{B}\cdot(\boldsymbol{\nabla}\times\mathbf{a})}{M_{\rm eff}}+m_{\phi}^{2}\varphi,

where 1/MeffBF,ϕ(ϕ¯)1/M_{\rm eff}\equiv B_{F,\phi}(\bar{\phi}) and mϕ2Veff,ϕϕ(ϕ¯,Tm,A¯μ)m_{\phi}^{2}\equiv V_{{\rm eff},\phi\phi}(\bar{\phi},T_{\rm m},\bar{A}_{\mu}).

We consider a photon field propagating in the 𝐳^\hat{\mathbf{z}} direction, so that in an orthonormal Cartesian basis (𝐱^,𝐲^,𝐳^)(\hat{\mathbf{x}},\hat{\mathbf{y}},\hat{\mathbf{z}}) we have 𝐚=(γx,γy,0)T\mathbf{a}=(\gamma_{x},\gamma_{y},0)^{\rm T}. The above equations of motion for the chameleon and photon polarization states can then be written in matrix form:

[t2z2(ωpl20ByMeffz0ωpl2BxMeffzByMeffzBxMeffzmϕ2)](γxγyφ)=0.\displaystyle\left[-\partial_{t}^{2}-\partial_{z}^{2}-\left(\begin{array}[]{ccc}\omega_{\rm pl}^{2}&0&-\frac{B_{y}}{M_{\rm eff}}\partial_{z}\\ 0&\omega_{\rm pl}^{2}&\frac{B_{x}}{M_{\rm eff}}\partial_{z}\\ \frac{B_{y}}{M_{\rm eff}}\partial_{z}&-\frac{B_{x}}{M_{\rm eff}}\partial_{z}&m_{\phi}^{2}\end{array}\right)\right]\left(\begin{array}[]{c}\gamma_{x}\\ \gamma_{y}\\ \varphi\end{array}\right)=0. (11)

Following a similar procedure to that in Ref. Raffelt88 , we assume the fields vary slowly over time and that the refractive index is close to unity which requires mϕ2/2ω2m_{\rm\phi}^{2}/2\omega^{2}, ωpl2/2ω2\omega_{\rm pl}^{2}/2\omega^{2} and |B|/2ωMeff|B|/2\omega M_{\rm eff} all 1\ll 1. Defining γi=γ~i(z)eiω(zt)+iβ(z)\gamma_{i}=\tilde{\gamma}_{i}(z)e^{i\omega(z-t)+i\beta(z)} and φ=φ~eiω(zt)+iβ(z)\varphi=\tilde{\varphi}e^{i\omega(z-t)+i\beta(z)} where β,z=ωpl2(z)/2ω\beta_{,z}=-\omega_{\rm pl}^{2}(z)/2\omega, we approximate t2ω2-\partial_{t}^{2}\approx\omega^{2} and ω2+z22ω(ω+iz)\omega^{2}+\partial_{z}^{2}\approx 2\omega(\omega+i\partial_{z}). In addition to this, we define the state vector

𝐮=(γ~x(z)γ~y(z)e2iΔ(z)φ~(z)).\displaystyle\mathbf{u}=\left(\begin{array}[]{c}\tilde{\gamma}_{x}(z)\\ \tilde{\gamma}_{y}(z)\\ e^{2i\Delta(z)}\tilde{\varphi}(z)\end{array}\right). (15)

where

Δ(z)=0zmeff2(x)4ωdx,\Delta(z)=\int_{0}^{z}\frac{m_{\rm eff}^{2}(x)}{4\omega}{\rm d}x,

and meff2=mϕ2(z)ωpl2(z)m_{\rm eff}^{2}=m_{\phi}^{2}(z)-\omega_{\rm pl}^{2}(z), which simplifies the above mixing field equations for 𝐚\mathbf{a} and φ\varphi to

𝐮,z=(z)2Meff𝐮,\displaystyle\mathbf{u}_{,z}=\frac{\mathcal{B}(z)}{2M_{\rm eff}}\mathbf{u}, (16)

where

(z)=(00Bye2iΔ00Bxe2iΔBye2iΔBxe2iΔ0).\displaystyle\mathcal{B}(z)=\left(\begin{array}[]{ccc}0&0&-B_{y}e^{-2i\Delta}\\ 0&0&B_{x}e^{-2i\Delta}\\ B_{y}e^{2i\Delta}&-B_{x}e^{2i\Delta}&0\end{array}\right). (20)

To solve this system of equations we expand, 𝐮=𝐮0+𝐮1+𝐮2+\mathbf{u}=\mathbf{u}_{0}+\mathbf{u}_{1}+\mathbf{u}_{2}+\ldots, such that

𝐮i+1=(z)2Meff𝐮i;𝐮0=0,\displaystyle{\mathbf{u}}_{i+1}^{\prime}=\frac{\mathcal{B}(z)}{2M_{\rm eff}}\mathbf{u}_{i}\,;\;{\mathbf{u}}_{0}^{\prime}=0\,,

and neglect the higher order terms from mixing. We define

1=0z(x)2Meffdx.\mathcal{M}_{1}=\int_{0}^{z}\frac{\mathcal{B}(x)}{2M_{\rm eff}}{\rm d}x.

We say that mixing is weak when

tr(1(z)1(z))1.\displaystyle{\rm tr}\left(\mathcal{M}_{1}^{\dagger}(z)\mathcal{M}_{1}(z)\right)\ll 1.

Thus Eq. (16) can be solved in the limit of weak-mixing:

𝐮(z)[𝕀+1(z)+2(z)]𝐮(0),\displaystyle\mathbf{u}(z)\simeq\left[\mathbb{I}+\mathcal{M}_{1}(z)+\mathcal{M}_{2}(z)\right]\mathbf{u}(0),

where 2=0z1(x)1(x)dx\mathcal{M}_{2}=\int_{0}^{z}\mathcal{M}_{1}^{\prime}(x)\mathcal{M}_{1}(x){\rm d}x, which can be written

𝐮(z)[𝕀+1(z)+12(C(z)+12(z))]𝐮(0),\displaystyle\mathbf{u}(z)\simeq\left[\mathbb{I}+\mathcal{M}_{1}(z)+\frac{1}{2}\left(\mathcal{M}_{C}(z)+\mathcal{M}_{1}^{2}(z)\right)\right]\mathbf{u}(0),

where explicitly

1\displaystyle\mathcal{M}_{1} =\displaystyle= (00Ay00AxAyAx0),\displaystyle\left(\begin{array}[]{ccc}0&0&-A_{y}^{\ast}\\ 0&0&A_{x}^{\ast}\\ A_{y}&-A_{x}&0\end{array}\right), (24)
C\displaystyle\mathcal{M}_{C} =\displaystyle= (CyyCxy0CxyCxx000Cxx+Cyy),\displaystyle\left(\begin{array}[]{ccc}-C_{yy}&-C^{\ast}_{xy}&0\\ C_{xy}&-C_{xx}&0\\ 0&0&C_{xx}+C_{yy}\end{array}\right), (28)

and

Ai\displaystyle A_{i} =\displaystyle= 0zdxBi(x)e2iΔ(x)2Meff,\displaystyle\int_{0}^{z}{\rm d}x\frac{B_{i}(x)e^{2i\Delta(x)}}{2M_{\rm eff}},
Cij\displaystyle C_{ij} =\displaystyle= 0zdx(Ai(x)Aj(x)Ai(x)Aj(x)).\displaystyle\int_{0}^{z}{\rm d}x\,\left(A_{i}^{\ast\prime}(x)A_{j}(x)-A_{i}^{\ast}(x)A_{j}^{\prime}(x)\right).

We note that n=n\mathcal{M}_{n}^{\dagger}=-\mathcal{M}_{n}.

The polarization state of radiation is described by its Stokes parameters: intensity Iγ(z)=|γx(z)|2+|γy(z)|2I_{\gamma}(z)=|\gamma_{x}(z)|^{2}+|\gamma_{y}(z)|^{2}, linear polarization Q(z)=|γx(z)|2|γy(z)|2Q(z)=|\gamma_{x}(z)|^{2}-|\gamma_{y}(z)|^{2} and U(z)=2Re(γx(z)γy(z))U(z)=2{\rm Re}\left(\gamma_{x}^{\ast}(z)\gamma_{y}(z)\right), and circular polarization V(z)=2Im(γx(z)γy(z))V(z)=2{\rm Im}\left(\gamma_{x}^{\ast}(z)\gamma_{y}(z)\right). Assuming there is no initial chameleon flux, Iϕ=|φ|2=0I_{\phi}=|\varphi|^{2}=0, then to leading order the final photon intensity is given by

Iγ(z)\displaystyle I_{\gamma}(z) =\displaystyle= Iγ(0)(1𝒫γϕ(z))\displaystyle I_{\gamma}(0)\left(1-\mathcal{P}_{\gamma\leftrightarrow\phi}(z)\right)
+Q(0)𝒬q(z)+U(0)𝒬u(z)+V(0)𝒬v(z),\displaystyle+Q(0)\mathcal{Q}_{\rm q}(z)+U(0)\mathcal{Q}_{\rm u}(z)+V(0)\mathcal{Q}_{\rm v}(z),

where we have defined,

𝒫γϕ(z)\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}(z) =\displaystyle= 12(|Ax(z)|2+|Ay(z)|2),\displaystyle\frac{1}{2}\left(|A_{x}(z)|^{2}+|A_{y}(z)|^{2}\right),
𝒬q(z)\displaystyle\mathcal{Q}_{\rm q}(z) =\displaystyle= 12(|Ax(z)|2|Ay(z)|2),\displaystyle\frac{1}{2}\left(|A_{x}(z)|^{2}-|A_{y}(z)|^{2}\right),
𝒬u(z)\displaystyle\mathcal{Q}_{\rm u}(z) =\displaystyle= Re(AxAy),\displaystyle{\rm Re}(A_{x}^{\ast}A_{y}),
𝒬v(z)\displaystyle\mathcal{Q}_{\rm v}(z) =\displaystyle= Im(AxAy).\displaystyle{\rm Im}(A_{x}^{\ast}A_{y}).

In this article we consider mixing with the CMB, the intrinsic polarization of which is small, i.e. Q2(0)+U2(0)+V2(0)/Iγ(0)1\sqrt{Q^{2}(0)+U^{2}(0)+V^{2}(0)}/I_{\gamma}(0)\ll 1. It follows that to leading order the modification to the Stokes parameters of the CMB radiation, from the effect of photon-ALP mixing, is

Δ𝐒(z)=Δ(Iγ(z)Q(z)U(z)V(z))\displaystyle\Delta\mathbf{S}(z)=\Delta\left(\begin{array}[]{c}I_{\gamma}(z)\\ Q(z)\\ U(z)\\ V(z)\end{array}\right) \displaystyle\approx (𝒫γϕ(z)𝒬q(z)𝒬u(z)𝒬v(z))Iγ(0).\displaystyle\left(\begin{array}[]{c}-\mathcal{P}_{\gamma\leftrightarrow\phi}(z)\\ \mathcal{Q}_{\rm q}(z)\\ \mathcal{Q}_{\rm u}(z)\\ \mathcal{Q}_{\rm v}(z)\end{array}\right)I_{\gamma}(0). (37)

To evaluate 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} we need a model for the spatial variation of the magnetic field and effective mass. Typically ne103102cm3n_{\rm e}\sim 10^{-3}\text{--}10^{-2}\,{\rm cm}^{-3} in galaxies and galaxy clusters and so ωpl𝒪(1012)eV\omega_{\rm pl}\sim{\cal O}(10^{-12})\,{\rm eV}. For the chameleon-like-theories detailed in §I.1, it follows that ωpl2mϕ2\omega_{\rm pl}^{2}\gg m_{\phi}^{2}. In what follows we assume that the scalar field is very light so that meff2ωpl2nem_{\rm eff}^{2}\approx-\omega_{\rm pl}^{2}\propto-n_{\rm e}. Spatial variations in meff2m_{\rm eff}^{2} are then entirely due to spatial variations in nen_{\rm e}.

The magnetic fields of galaxies and galaxy clusters have been measured to have a regular component 𝐁reg(z)\mathbf{B}_{\rm reg}(z), with a typical length scale of variation similar to the size of the object, and a turbulent component δ𝐁(z)\delta\mathbf{B}(z) which undergoes 𝒪(1){\cal O}(1) variations and reversals on much smaller scales. It is common, both in the literature concerning photon-ALP conversion in galaxy and cluster magnetic fields and in that concerning the measurement of those fields, to use a simple cell model to describe δ𝐁\delta\mathbf{B}. In this cell model one defines LcohL_{\rm coh} to be the length scale over which the random magnetic field is coherent, i.e. the typical scale over which field reversals of δ𝐁\delta\mathbf{B} occur. A given path of length LL is then divided into NN magnetic domains, N=L/LcohN=L/L_{\rm coh}. The magnetic field strength and electron density are assumed to be constant along the path, but the random magnetic field component, δ𝐁x\delta\mathbf{B}_{x}, is taken to have a different random orientation in each of the NN magnetic domains. Although the cell model for δ𝐁\delta\mathbf{B} is common in the literature and reveals most of the key features associated with astrophysical photon-ALP mixing, it is not accurate especially when |Δ(z=L)|1|\Delta(z=L)|\gg 1. Additionally, as was first noted in Ref. Ensslin03 , in this model we do not have δ𝐁=0\nabla\cdot\delta\mathbf{B}=0 as we should. A more realistic model for 𝐁\mathbf{B} is to assume a spectrum of fluctuations running from some very large scale (e.g. the scale of the galaxy or cluster) down to some very small scale (Lcoh\ll L_{\rm coh}). We describe these fluctuations by a correlation function RB(𝐱)=δ𝐁(𝐲)δ𝐁(𝐱+𝐲)R_{\rm B}(\mathbf{x})=\left\langle\delta\mathbf{B}(\mathbf{y})\delta\mathbf{B}(\mathbf{x}+\mathbf{y})\right\rangle and the associated power spectrum PB(k)P_{\rm B}(k); here the angled brackets indicate the expectation of the quantity inside them. We can, and should, also allow for a similar spectrum of fluctuations in the electron number density with some power spectrum PN(k)P_{\rm N}(k). We now evaluate 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} in both this power spectrum model and the cell model.

II.1 The Cell Model

In the cell model, we take meff2=constm_{\rm eff}^{2}={\rm const} and 𝐁=𝐁reg+δ𝐁\mathbf{B}=\mathbf{B}_{\rm reg}+\delta\mathbf{B} where 𝐁regconst\mathbf{B}_{\rm reg}\approx{\rm const} over the path length LL. For δ𝐁\delta\mathbf{B} we take (δ𝐁)x=Brandcosθn(\delta\mathbf{B})_{x}=B_{\rm rand}\cos\theta_{n} and (δ𝐁)y=Brandsinθn(\delta\mathbf{B})_{y}=B_{\rm rand}\sin\theta_{n} for (n1)Lcoh<z<nLcoh(n-1)L_{\rm coh}<z<nL_{\rm coh} where the θn\theta_{n} are independent random variables with identical distributions U(0,2π]U(0,2\pi]. We then have, over a path length LL,

Ai\displaystyle A_{i} =\displaystyle= (𝐀reg)i+(δ𝐀)i,\displaystyle(\mathbf{A}_{\rm reg})_{i}+(\delta\mathbf{A})_{i},
𝐀reg\displaystyle\mathbf{A}_{\rm reg} =\displaystyle= 2𝐁regωeiΔ¯Meffmeff2sinΔ¯,\displaystyle\frac{2\mathbf{B}_{\rm reg}\omega e^{i\bar{\Delta}}}{M_{\rm eff}m_{\rm eff}^{2}}\sin\bar{\Delta},
δ𝐀\displaystyle\delta\mathbf{A} =\displaystyle= 2BrandωeiΔ¯NMeffmeff2sin(Δ¯N)r=0N1𝐧^(r)e2iΔ¯rN,\displaystyle\frac{2B_{\rm rand}\omega e^{\frac{i\bar{\Delta}}{N}}}{M_{\rm eff}m_{\rm eff}^{2}}\sin\left(\frac{\bar{\Delta}}{N}\right)\sum_{r=0}^{N-1}\hat{\mathbf{n}}^{(r)}e^{\frac{2i\bar{\Delta}r}{N}},

where Δ¯=meff2L/4ω\bar{\Delta}=m_{\rm eff}^{2}L/4\omega and 𝐧^(n)=(cosθn,sinθn,0)T\hat{\mathbf{n}}^{(n)}=(\cos\theta_{n},\sin\theta_{n},0)^{\rm T}. It follows that the expected values of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} are,

𝒫¯γϕ\displaystyle\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} \displaystyle\equiv 𝒫γϕ=12(2BregωMeffmeff2)2sin2Δ¯\displaystyle\left\langle\mathcal{P}_{\gamma\leftrightarrow\phi}\right\rangle=\frac{1}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta}
+N2(2BrandωMeffmeff2)2sin2(Δ¯N),\displaystyle+\frac{N}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right),
𝒬¯q\displaystyle\bar{\mathcal{Q}}_{\rm q} =\displaystyle= cos2θreg2(2BregωMeffmeff2)2sin2Δ¯,\displaystyle\frac{\cos 2\theta_{\rm reg}}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},
𝒬¯u\displaystyle\bar{\mathcal{Q}}_{\rm u} =\displaystyle= sin2θreg2(2BregωMeffmeff2)2sin2Δ¯,\displaystyle\frac{\sin 2\theta_{\rm reg}}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},
𝒬¯v\displaystyle\bar{\mathcal{Q}}_{\rm v} =\displaystyle= 0,\displaystyle 0,

where we have used δ𝐁=0\left\langle\delta\mathbf{B}\right\rangle=0, and defined (𝐁reg)x=Bregcosθreg(\mathbf{B}_{\rm reg})_{x}=B_{\rm reg}\cos\theta_{\rm reg} and (𝐁reg)y=Bregsinθreg(\mathbf{B}_{\rm reg})_{y}=B_{\rm reg}\sin\theta_{\rm reg}. We also note that for Δ¯/N1\bar{\Delta}/N\gg 1 and N1N\gg 1, the variance of the 𝒬i\mathcal{Q}_{i} at a given frequency are 𝒪(𝒫¯γϕ2){\cal O}(\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}). We present the detailed evaluation of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} in the cell model in Appendix A.1. These results were first presented in Ref. Burrage08 .

We note that if, as is generally the case, Brand𝒪(Breg)B_{\rm rand}\sim{\cal O}(B_{\rm reg}), the effect of multiple box-like magnetic regions with coherence length LcohLL_{\rm coh}\ll L is to enhance the expected photon-ALP mixing probability by a factor of NN.

II.2 The Power Spectrum Model

A more generalised prescription for describing the magnetic field and electron density fluctuations is with a power spectrum model. As before, meff2ωpl2nem_{\rm eff}^{2}\simeq-\omega_{\rm pl}^{2}\propto n_{\rm e}. We assume that, for each ii and for fixed 𝐱\mathbf{x}, the turbulent component of the magnetic field δ𝐁i(𝐱)\delta\mathbf{B}_{i}(\mathbf{x}) is approximately a Gaussian random variable. We assume that the fluctuations are isotropic and so

RBij(𝐱;𝐲)δ𝐁i(𝐲)δ𝐁j(𝐱+𝐲)=13RB(𝐱;𝐲)δij.R_{{\rm B}\,ij}(\mathbf{x};\mathbf{y})\equiv\left\langle\delta\mathbf{B}_{i}(\mathbf{y})\delta\mathbf{B}_{j}(\mathbf{x}+\mathbf{y})\right\rangle=\frac{1}{3}R_{\rm B}(\mathbf{x};\mathbf{y})\delta_{ij}.

Finally we require (at least approximate) position independence for the fluctuations so that RB(𝐱;𝐲)RB(x)R_{\rm B}(\mathbf{x};\mathbf{y})\approx R_{\rm B}(x). RB(x)R_{\rm B}(x) is the auto-correlation function for the magnetic field fluctuations. The electron number density is divided into a constant part and a fluctuating part, ne=n¯e+δnen_{\rm e}=\bar{n}_{\rm e}+\delta n_{\rm e}, and we assume that 1+δne/n¯e1+\delta n_{\rm e}/\bar{n}_{\rm e} is a log-normally distributed random variable with mean 11 and variance δn2\left\langle\delta_{\rm n}^{2}\right\rangle, where δnδne/n¯e\delta_{\rm n}\equiv\delta n_{\rm e}/\bar{n}_{\rm e}. We define the electron density auto-correlation function by,

RN(x)=δne(𝐲)δne(𝐱+𝐲).R_{\rm N}(x)=\left\langle\delta n_{\rm e}(\mathbf{y})\delta n_{\rm e}(\mathbf{x}+\mathbf{y})\right\rangle.

The power spectra for the magnetic and electron density fluctuations, PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k), are defined:

RB(x)\displaystyle R_{\rm B}(x) =\displaystyle= 14πd3ke2πi𝐤𝐱PB(k)\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}ke^{2\pi i\mathbf{k}\cdot\mathbf{x}}P_{\rm B}(k)
=\displaystyle= k2dkPB(k)sin(2πkx)2πkx,\displaystyle\int k^{2}{\rm d}k\,P_{\rm B}(k)\frac{\sin(2\pi kx)}{2\pi kx},
RN(x)\displaystyle R_{\rm N}(x) =\displaystyle= 14πd3ke2πi𝐤𝐱PN(k)\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}ke^{2\pi i\mathbf{k}\cdot\mathbf{x}}P_{\rm N}(k)
=\displaystyle= k2dkPN(k)sin(2πkx)2πkx.\displaystyle\int k^{2}{\rm d}k\,P_{\rm N}(k)\frac{\sin(2\pi kx)}{2\pi kx}.

Following Ref. Murgia04 , we define correlation length scales, LBL_{\rm B} and LNL_{\rm N}, for the magnetic and electron density fluctuations respectively:

LB/N=0kdkPB/N(k)20k2dkPB/N(k).\displaystyle L_{\rm B/N}=\frac{\int_{0}^{\infty}k{\rm d}k\,P_{\rm B/N}(k)}{2\int_{0}^{\infty}k^{2}{\rm d}k\,P_{\rm B/N}(k)}. (39)

We define Δ¯=m¯eff2L/4ω4παemn¯eL/4meω\bar{\Delta}=\bar{m}_{\rm eff}^{2}L/4\omega\simeq-4\pi\alpha_{\rm em}\bar{n}_{\rm e}L/4m_{\rm e}\omega, and kcrit=|Δ¯/πL|k_{\rm crit}=|\bar{\Delta}/\pi L|. In Appendix A.2 we evaluate 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} at low frequencies, i.e. large |Δ¯||\bar{\Delta}|, in the power spectrum model. We assume there is some k3(B/N)kcritk_{-3}^{(\rm B/N)}\ll k_{\rm crit} such that PB/N(k)P_{\rm B/N}(k) decreases faster than k3k^{-3} as kk\rightarrow\infty for k>k3(B/N)k>k_{-3}^{(\rm B/N)}. This is equivalent to assuming that the dominant contribution to δ𝐁2\left\langle\delta\mathbf{B}^{2}\right\rangle and ne2\left\langle n_{\rm e}^{2}\right\rangle comes from spatial scales than are much larger than kcrit1k_{\rm crit}^{-1}. We expect that this dominant contribution will come from scales of the order of the coherence lengths of the magnetic field and electron density fluctuations and so are assuming that kcrit1LB,LNk_{\rm crit}^{-1}\ll L_{\rm B},\,L_{\rm N}. This and the other assumptions given above lead to,

𝒫¯γϕ\displaystyle\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} \displaystyle\equiv 𝒫γϕ12(2BeffωMeffm¯eff2)2IN3\displaystyle\left\langle\mathcal{P}_{\gamma\leftrightarrow\phi}\right\rangle\approx\frac{1}{2}\left(\frac{2B_{\rm eff}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}I_{\rm N}^{3}
14(2BregωMeffm¯eff2)2cos(2Δ¯)\displaystyle-\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}\cos\left(2\bar{\Delta}\right)
+Beff2L8Meff2n¯e2IN2WN(kcrit)+L24Meff2IN3WB(kcrit).\displaystyle+\frac{B_{\rm eff}^{2}L}{8M_{\rm eff}^{2}\bar{n}_{e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit})+\frac{L}{24M_{\rm eff}^{2}}I_{\rm N}^{3}W_{\rm B}(k_{\rm crit}).

where

IN\displaystyle I_{\rm N} =\displaystyle= 1+δn2,\displaystyle 1+\left\langle\delta_{\rm n}^{2}\right\rangle,
Beff2\displaystyle B_{\rm eff}^{2} =\displaystyle= 12(𝐳^×𝐁)2\displaystyle\frac{1}{2}\left\langle(\hat{\mathbf{z}}\times\mathbf{B})^{2}\right\rangle
=\displaystyle= Breg2/2+δ𝐁2/3,\displaystyle B_{\rm reg}^{2}/2+\left\langle\delta\mathbf{B}^{2}\right\rangle/3,
WB/N(kcrit)\displaystyle W_{{\rm B/N}}(k_{\rm crit}) =\displaystyle= kcritkdkPB/N(k).\displaystyle\int_{k_{\rm crit}}^{\infty}k{\rm d}k\,P_{\rm B/N}(k).

It is straightforward to check that 𝒬¯v=0\bar{\mathcal{Q}}_{\rm v}=0, and

𝒬¯q\displaystyle\bar{\mathcal{Q}}_{\rm q} \displaystyle\approx 𝒬0cos2θreg,\displaystyle\mathcal{Q}_{0}\cos 2\theta_{\rm reg},
𝒬¯u\displaystyle\bar{\mathcal{Q}}_{\rm u} \displaystyle\approx 𝒬0sin2θreg,\displaystyle\mathcal{Q}_{0}\sin 2\theta_{\rm reg},

where

𝒬0\displaystyle\mathcal{Q}_{0} =\displaystyle= 14(2BregωMeffm¯eff2)2IN3\displaystyle\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}I_{\rm N}^{3}
14(2BregωMeffm¯eff2)2cos(2Δ¯)\displaystyle-\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}\cos\left(2\bar{\Delta}\right)
+Breg2L16Meff2n¯e2IN2WN(kcrit).\displaystyle+\frac{B_{\rm reg}^{2}L}{16M_{\rm eff}^{2}\bar{n}_{\rm e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit}).

We note that, in contrast to the cell model, here we have an extra term in the expressions for the mean induced Stokes parameters which scales as LL. This term is associated with electron density fluctuations and is usually dominant when Δ¯1\bar{\Delta}\gg 1, as is the case for CMB photons in galaxy clusters.

We have assumed that near k=kcritk=k_{\rm crit} and for all large kk, both PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k) are decreasing faster than k3k^{-3}. We further assume that near k=kcritk=k_{\rm crit}, PB(k)PN(k)kα2P_{\rm B}(k)\propto P_{\rm N}(k)\propto k^{\alpha-2} for some α<1\alpha<-1. We define normalization constants CKC_{\rm K} and CNC_{\rm N}:

k2PB(k)\displaystyle k^{2}P_{\rm B}(k) =\displaystyle= 2CK(kk0)α,\displaystyle 2C_{\rm K}\left(\frac{k}{k_{0}}\right)^{\alpha}, (41)
k2PN(k)\displaystyle k^{2}P_{\rm N}(k) =\displaystyle= 2(2π)1/3CN2kα,\displaystyle 2(2\pi)^{1/3}C_{\rm N}^{2}k^{\alpha}, (42)

where k0=1kpc1k_{0}=1\,{\rm kpc}^{-1}. These forms hold for kO(kcrit)k\sim O(k_{\rm crit}). We have chosen the normalization for PBP_{\rm B} and PNP_{\rm N} to be consistent with the conventions of Refs. Han04 and Armstrong95 respectively, where α=5/3\alpha=-5/3 corresponds to three-dimensional Kolmogorov turbulence. It follows that,

WB(kcrit)\displaystyle W_{\rm B}(k_{\rm crit}) \displaystyle\approx 2CK|α|(kcritk0)α,\displaystyle\frac{2C_{\rm K}}{|\alpha|}\left(\frac{k_{\rm crit}}{k_{0}}\right)^{\alpha},
WN(kcrit)\displaystyle W_{\rm N}(k_{\rm crit}) \displaystyle\approx 2(2π)1/3|α|CN2kcritα.\displaystyle\frac{2(2\pi)^{1/3}}{|\alpha|}C_{\rm N}^{2}k_{\rm crit}^{\alpha}.

We have

kcrit12.4×102pc(ν100GHz)(103cm3n¯e),\displaystyle k_{\rm crit}^{-1}\approx 2.4\times 10^{-2}\,{\rm pc}\left(\frac{\nu}{100\,{\rm GHz}}\right)\left(\frac{10^{-3}\,{\rm cm}^{-3}}{\bar{n}_{\rm e}}\right), (43)

where ν=ω/2π\nu=\omega/2\pi is the frequency of the electromagnetic radiation. For galaxy clusters n¯e103102cm3\bar{n}_{\rm e}\sim 10^{-3}\textrm{--}10^{-2}\,{\rm cm}^{-3} and for CMB photons ν30300GHz\nu\sim 30-300\,{\rm GHz}. The typical critical length scale is then much smaller than a parsec, kcrit11030.1pck_{\rm crit}^{-1}\approx 10^{-3}\textrm{--}0.1\,{\rm pc}. The form and magnitude of PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k) in galaxy clusters for such small scales are not known empirically.

We note that the cell model is in fact a sub-class of the power spectrum model with an appropriate choice for WBW_{\rm B} and WNW_{\rm N}. When referring to the power spectrum model in what follows we will be referring to the specific case of PB(k)PN(k)kα2P_{\rm B}(k)\propto P_{\rm N}(k)\propto k^{\alpha-2} at large kk.

III Magnetic Fields in Galaxy Clusters

We saw in the previous section that the mixing of photons with light scalars depends crucially on the structure of the magnetic field along the line of sight. As the CMB photons propagate towards Earth they pass through clusters of galaxies. The space between individual galaxies in the cluster is filled with a hot plasma which supports a magnetic field. In this article, we are focused on the mixing of CMB photons and light (chameleonic) scalars in the intra-cluster (IC) medium. In this section we briefly review the observed properties of IC magnetic fields.

Intra-cluster magnetic fields have been observed to have field strengths as high as 30μG30\,\mu\hbox{G} Taylor93 . The galaxy clusters can be divided into two types: non-cooling core clusters for which the magnetic field in the ICM is generally found to be a few to 10μG10\,\mu\mathrm{G} and ordered on scales of 1020kpc10-20\,\mathrm{kpc}; while in cooling core systems the magnetic field strength is generally higher (around 1040μG10-40\,\mu\mathrm{G}) and ordered on smaller scales of a few to 10kpc10\,\mathrm{kpc} Clarke04 . In Table 1 we list the typical ranges for some of the galaxy cluster properties.

Features of a typical galaxy cluster :
magnetic field strength, 𝐁21/2\left\langle\mathbf{B}^{2}\right\rangle^{1/2} 0.10.1 - 30μG30\,\mu\hbox{G},
coherence length of magnetic field, LcohL_{\rm coh} 11 - 100 kpc100\hbox{\, kpc},
number of magnetic domains, N=L/LcohN=L/L_{\rm coh} 100100 - 10310^{3}
electron number density, nen_{\rm e} 10410^{-4} - 102 cm310^{-2}\hbox{\, cm}^{-3},
Table 1: List of the parameters for typical galaxy clusters Kronberg94 ; Ohno03 .

One of the common methods for determining cluster magnetic fields is the observation of Faraday rotation measures (RMs). The RM corresponds to a rotation of the polarization angle of an intrinsically polarized radio source located behind or embedded within the galaxy cluster. The RM along a line of sight in the 𝐳^\hat{\mathbf{z}} direction of a source at z=zsz=z_{\rm s} is given by:

RM(zs𝐳^)=a00zsne(x𝐳^)B(x𝐳^)dx,\displaystyle{\rm RM}(z_{\rm s}\hat{\mathbf{z}})=a_{0}\int_{0}^{z_{\rm s}}n_{\rm e}(x\hat{\mathbf{z}})B_{\parallel}(x\hat{\mathbf{z}}){\rm d}x,

where a0=αem3/π1/2me2a_{0}=\alpha_{\rm em}^{3}/\pi^{1/2}m_{\rm e}^{2}\,, BB_{\parallel} is the magnetic field along the line of sight, and the observer is at 𝐱=0\mathbf{x}=0. For a uniform magnetic field over a length LL along the line of sight and in a region of constant density, we expect RM=a0BneL\langle{\rm RM}\rangle=a_{0}B_{\parallel}n_{\rm e}L. However, the dispersion of Faraday RMs from extended radio sources suggests that this is not a realistic model for IC magnetic fields. Both the dispersion of the measured RMs and simulations suggest that IC magnetic fields typically have a sizeable component that is tangled on scales smaller than the cluster. The simplest model for a tangled magnetic field is, as we mentioned in the previous section, the cell model where the cluster is divided up into uniform cells with sides of length LcohL_{\rm coh}. The total magnetic field strength is assumed to be the same in every cell, but the orientation of the magnetic field in each cell is random. In the cell model the RM is given by a Gaussian distribution with zero mean, and variance

RM2a02Lcoh20L𝐁2(z)ne2(z)dz,\displaystyle\left\langle{\rm RM}^{2}\right\rangle\sim\frac{a_{0}^{2}L_{\rm coh}}{2}\int_{0}^{L}\left\langle\mathbf{B}^{2}(z)\right\rangle n_{\rm e}^{2}(z){\rm d}z,

where 𝐁2\left\langle\mathbf{B}^{2}\right\rangle is the average value of 𝐁2\mathbf{B}^{2} along the line of sight. We noted in the previous section that a more realistic model for the magnetic field is to assume a power spectrum of fluctuations. In this model one finds Murgia04 ,

RM2a02LB20L𝐁2(z)ne2(z)dz.\displaystyle\left\langle{\rm RM}^{2}\right\rangle\sim\frac{a_{0}^{2}L_{\rm B}}{2}\int_{0}^{L}\left\langle\mathbf{B}^{2}(z)\right\rangle n_{e}^{2}(z){\rm d}z\,.

To match the same observations with the same total field strength, LBL_{\rm B} in the power spectrum model should be equal to LcohL_{\rm coh} in the cell model. Whichever model is used, determination of the magnetic field from Faraday rotation measures is heavily reliant on the estimated coherence length of the magnetic field. A study by Clarke et al. Clarke01 examining the Faraday RMs of 16 “normal” clusters, i.e. free of strong radio halos and widespread cooling flows, found the following relationship between the average field strength and the inferred coherence length for the IC magnetic field:

|B|icm=510(Ldom10kpc)1/2h751/2μG\langle\left|B\right|\rangle_{\mathrm{icm}}=5\text{--}10\,\left(\frac{L_{\mathrm{dom}}}{10\,\mathrm{kpc}}\right)^{-1/2}h_{75}^{1/2}\,\mu\mathrm{G} (44)

where h75h_{75} is defined by H0=75h75kms1Mpc1H_{0}=75\,h_{75}\,\mathrm{km\,s^{-1}Mpc^{-1}}. This study excludes the cooling core systems which generally possess slightly higher magnetic field strengths.

The ambient electron number density also plays a crucial role in determining the strength of photon-scalar mixing. The electron density of cluster atmospheres can be determined from X-ray surface brightness observations, for example using ROSAT, which are fitted to a β\beta profile (see Ref. Govoni04 ):

ne(r)=n0(1+r2rc2)3β/2,n_{e}(r)=n_{0}\left(1+\frac{r^{2}}{r_{c}^{2}}\right)^{-3\beta/2},

where β𝒪(1)\beta\sim\mathcal{O}(1) and positive. The magnetic field is expected to decline with radius in a similar fashion to the electron density. Magneto-hydrodynamic (MHD) simulations of galaxy cluster formation suggest that 𝐁21/2neη\left\langle\mathbf{B}^{2}\right\rangle^{1/2}\propto\left\langle n_{e}\right\rangle^{\eta}, η=1\eta=1 while observations of Abell 119 suggest η=0.9\eta=0.9 Dolag . Two simple theoretical arguments for the value of η\eta, are (1) that the magnetic field is frozen-in and hence η=2/3\eta=2/3, or (2) the total magnetic energy, 𝐁2\propto\left\langle\mathbf{B}^{2}\right\rangle, scales as the thermal energy, ne\propto n_{\rm e}, and hence η=1/2\eta=1/2 Govoni04 . Faraday RM observations of clusters Clarke01 have found that the magnetic field extends as far as the ROSAT-detectable X-ray emission (coming purely from the electron density distribution). Typically this corresponds to a scale of 500kpc\sim 500\,\mathrm{kpc}.

III.1 Power Spectra of Cluster Magnetic Fields

As discussed in §II.2, fluctuations across a range of scales in the magnetic field and electron density in clusters can be described by their respective power spectra, PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k). On small scales the power spectra are parameterised by a power law form as given by Eqs. (41) and (42). In these equations the index α=5/3\alpha=-5/3 corresponds to the special case of three dimensional Kolmogorov turbulence. According to Kolmogorov’s 1941 theory of turbulence, the power spectrum of three dimensional turbulence on the smallest scales is universal and has P(k)k11/3P(k)\propto k^{-11/3}.

The values of the normalization constants, CN2C_{\rm N}^{2} and CKC_{\rm K}, in our own galaxy have been determined by Armstrong et al.Armstrong95 and Minter & Spangler Minter96 respectively. Armstrong et al. found α5/3\alpha\approx-5/3 for spatial scales 106m<k1<1013m10^{6}{\rm m}<k^{-1}<10^{13}{\rm m}, and CN2103m20/3C_{\rm N}^{2}\approx 10^{-3}{\rm m}^{-20/3}. Minter & Spangler also found α5/3\alpha\approx-5/3 for spatial scales 0.01pck13.6pc0.01\,{\rm pc}\lesssim k^{-1}\lesssim 3.6\,{\rm pc}, and CK0.95×1012ergcm3kpcC_{\rm K}\approx 0.95\times 10^{-12}\,{\rm erg}\,{\rm cm}^{-3}\,{\rm kpc}. On larger scales Han et al.Han04 found that the magnetic fluctuation power spectrum flattens with α0.37±0.1\alpha\approx-0.37\pm 0.1 for 0.5kpck115kpc0.5\,{\rm kpc}\lesssim k^{-1}\lesssim 15\,{\rm kpc}, and CK6.8×1013ergcm3kpcC_{\rm K}\approx 6.8\times 10^{-13}\,{\rm erg}\,{\rm cm}^{-3}\,{\rm kpc} on these scales.

Enßlin & Vogt Ensslin03 and Murgia et al.Murgia04 showed that information about the power spectrum of galaxy cluster magnetic fluctuations could also be gained from detailed RM images. The inferred galaxy cluster magnetic power spectra are consistent with a power law form and 2<α<0-2<\alpha<0 in different regions of the clusters. For instance, in Ref. Vogt03 Vogt & Enßlin analysed Faraday rotation maps of three galaxy clusters: Abell 400, Abell 2634 and Hydra A. They found that for k1kpc1k\gtrsim 1\,{\rm kpc}^{-1}, the power spectra of all three clusters were consistent with a power law form and 2<α<1.6-2<\alpha<-1.6, and hence consistent with a Kolomogorov power spectrum (α=5/3\alpha=-5/3) on small scales. For k1kpc1k\lesssim 1\,{\rm kpc}^{-1}, k2PBk^{2}P_{\rm B} was found to be roughly flat or slightly increasing with kk.

Such measurements only probe the power spectrum at spatial scales larger than a few kiloparsecs. In this work, we find that the photon to scalar field conversion rate is sensitive to PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k) on scales kcrit1\sim k_{\rm crit}^{-1} (Eq. (43)). Typically kcrit11030.1pck_{\rm crit}^{-1}\approx 10^{-3}\textrm{--}0.1\,{\rm pc} for the CMB in galaxy clusters. There are no observations of the form or magnitude of PB(k)P_{\rm B}(k) and PN(k)P_{\rm N}(k) on such small scales. We therefore estimate α\alpha by assuming that on scales kcrit1\lesssim k_{\rm crit}^{-1}, we have three dimensional Kolmogorov turbulence. The dominant contribution to δ𝐁2\left\langle\delta\mathbf{B}^{2}\right\rangle comes from scales where PBP_{\rm B} switches from dropping off more slowly than k3k^{-3} to dropping off faster than k3k^{-3} as kk increases. We define this scale to be kk_{\ast}. To estimate CKC_{\rm K} and CNC_{\rm N} we assume a simple model for PB/N(k)P_{\rm B/N}(k) whereby for kkk\gtrsim k_{\ast} up to and including kcritk_{\rm crit}, we have Kolmogorov turbulence, and for kkk\lesssim k_{\ast}, the power spectrum decreases more slowly than k3k^{-3} with increasing kk. We also assume that k2PB/N(k)constk^{2}P_{\rm B/N}(k)\rightarrow{\rm const} as k0k\rightarrow 0 so that the coherence lengths LBL_{\rm B} and LNL_{\rm N} (Eq. (39)) are well defined. We therefore assume,

k2PB(k)\displaystyle k^{2}P_{\rm B}(k) \displaystyle\approx 2CK(kk0)5/3,k>k,\displaystyle 2C_{\rm K}\left(\frac{k}{k_{0}}\right)^{-5/3},\quad k>k_{\ast},
k2PB(k)\displaystyle k^{2}P_{\rm B}(k) \displaystyle\approx 2CK(kk0)53(kk)β,kmin<k<k,\displaystyle 2C_{\rm K}\left(\frac{k_{\ast}}{k_{0}}\right)^{-\frac{5}{3}}\left(\frac{k}{k_{\ast}}\right)^{\beta},\quad k_{\rm min}<k<k_{\ast},

where β>1\beta>-1, and we can ignore the contribution of k2PB(k)k^{2}P_{\rm B}(k) for k<kmink<k_{\rm min}. It follows that,

δ𝐁2\displaystyle\left\langle\delta\mathbf{B}^{2}\right\rangle =\displaystyle= 14πd3kPB(k)\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}kP_{\rm B}(k)
=\displaystyle= [2f1+β(x)+3]CKk(kk0)5/3,\displaystyle\left[2f_{1+\beta}(x)+3\right]C_{\rm K}k_{\ast}\left(\frac{k_{\ast}}{k_{0}}\right)^{-5/3},
LBδ𝐁2\displaystyle L_{\rm B}\left\langle\delta\mathbf{B}^{2}\right\rangle =\displaystyle= 12kdkPB(k)\displaystyle\frac{1}{2}\int k\,{\rm d}k\,P_{\rm B}(k)
=\displaystyle= [fβ(x)+35]CK(kk0)5/3,\displaystyle\left[f_{\beta}(x)+\frac{3}{5}\right]C_{\rm K}\left(\frac{k_{\ast}}{k_{0}}\right)^{-5/3},

where x=kmin/kx=k_{\rm min}/k_{\ast} and we have defined

fβ(x)=1β[1xβ].f_{\beta}(x)=\frac{1}{\beta}\left[1-x^{\beta}\right].

From which we find,

k\displaystyle k_{\ast} =\displaystyle= LB1(fβ(x)+352f1+β(x)+3),\displaystyle L_{\rm B}^{-1}\left(\frac{f_{\beta}(x)+\frac{3}{5}}{2f_{1+\beta}(x)+3}\right),

and

k05/3CK\displaystyle k_{0}^{5/3}C_{\rm K} =\displaystyle= 457/3h(x)δ𝐁2LB2/3,\displaystyle\frac{4}{5^{7/3}}h(x)\left\langle\delta\mathbf{B}^{2}\right\rangle L_{\rm B}^{-2/3},

where

h(x)57/3(fβ(x)+35)2/34(2f1+β(x)+3)5/3.h(x)\equiv\frac{5^{7/3}(f_{\beta}(x)+\frac{3}{5})^{2/3}}{4(2f_{1+\beta}(x)+3)^{5/3}}.

On large scales, 100kpc1k10kpc1100\,{\rm kpc}^{-1}\lesssim k\lesssim 10\,{\rm kpc}^{-1}, observations such as those in Ref. Vogt03 are consistent with β0\beta\approx 0. We approximate kminO(Lclust1)k_{\rm min}\sim O(L_{\rm clust}^{-1}) where LclustL_{\rm clust} is the length scale of the magnetic region and we have kO(LB1)k_{\ast}\sim O(L_{\rm B}^{-1}). Thus k/kmin10200k_{\ast}/k_{\rm min}\sim 10-200 which gives, taking β0\beta\approx 0,

h(x)(58ln(k/kmin)+38)2/31.52.6.\displaystyle h(x)\approx\left(\frac{5}{8}\ln(k_{\ast}/k_{\rm min})+\frac{3}{8}\right)^{2/3}\sim 1.5\textrm{--}2.6.

Hence,

2k05/3CK(0.270.45)δ𝐁2LB2/3.\displaystyle 2k_{0}^{5/3}C_{\rm K}\approx\left(0.27\textrm{--}0.45\right)\left\langle\delta\mathbf{B}^{2}\right\rangle L_{\rm B}^{-2/3}.

For the galactic magnetic field where δ𝐁21/23μG\left\langle\delta\mathbf{B}^{2}\right\rangle^{1/2}\approx 3\,\mu{\rm G}, and LB2050pcL_{\rm B}\sim 20\textrm{--}50\,{\rm pc}, this gives

CK(0.72.2)×1012ergcm3kpc,\displaystyle C_{\rm K}\sim(0.7\textrm{--}2.2)\times 10^{-12}\,{\rm erg}\,{\rm cm}^{-3}\,{\rm kpc},

in line with observations. Following a similar procedure for CN2C_{\rm N}^{2} we estimate,

2(2π)1/3CN2n¯e2(0.270.45)δne2n¯e2LB2/3,\displaystyle 2(2\pi)^{1/3}C_{\rm N}^{2}\bar{n}_{e}^{-2}\approx\left(0.27\textrm{--}0.45\right)\frac{\left\langle\delta n_{\rm e}^{2}\right\rangle}{\bar{n}_{\rm e}^{2}}L_{\rm B}^{-2/3},

where δne2/n¯e2=IN1\left\langle\delta n_{\rm e}^{2}\right\rangle/\bar{n}_{\rm e}^{2}=I_{\rm N}-1, and we approximate LNL_{\rm N} by LBL_{\rm B}. The above expressions provide order of magnitude estimates for CKC_{\rm K} and CN2C_{\rm N}^{2}.

IV Chameleonic corrections to the Sunyaev–Zel’dovich Effect

One of the well-documented foreground effects acting on the CMB as it passes through galaxy clusters is the Sunyaev–Zel’dovich (SZ) effect. It arises from inverse-Compton scattering of CMB photons with free electrons in a hot plasma. The scattering process redistributes the energy of the photons causing a distortion in the frequency spectrum of the intensity. This is observed as a change in the apparent brightness of the CMB radiation in the direction of galaxy clusters. If a chameleon field or other light scalar couples to photons, the flux of CMB photons passing through galaxy clusters would additionally be altered by the mixing of this scalar field with CMB photons. As we shall see, for this new effect to be detectable the required effective scalar-photon coupling, geffg_{\rm eff}, and effective scalar mass, mϕm_{\phi}, are ruled out for standard axion-like-particles. A standard ALP with the required properties would violate constraints on ALP production in the Sun, He burning stars and SN1987A. However, all of these constraints feature ALP production in high density regions. If the ALP is a chameleon-like scalar field, then constraints from high density regions only very weakly constrain the properties of the scalar field in low density regions such as the ICM. A chameleon-like scalar field includes the chameleon and OP models discussed earlier or any other non-standard ALP for which one or both of geffg_{\rm eff} and 1/mϕ1/m_{\phi} decrease strongly enough as the ambient density increases. We refer to the correction to the Sunyaev–Zel’dovich effect due to mixing with some (chameleon-like) ALP as the chameleonic SZ (CSZ) effect.

In this section, we briefly review the properties of the CMB and the standard thermal Sunyaev–Zel’dovich effect before examining the chameleonic SZ effect.

IV.1 The CMB

The Cosmic Microwave Background (CMB) was emitted in the early Universe from the surface of last scattering at the time of recombination. This radiation is approximately uniform across the sky and has the intensity spectrum of a black-body radiating at a temperature of T0=2.725KT_{0}=2.725K:

I0=kBT02π2ω2c2xex1,\displaystyle I_{0}=\frac{k_{\rm B}T_{0}}{2\pi^{2}}\frac{\omega^{2}}{c^{2}}\frac{x}{e^{x}-1}\,,

where xω/kBT0x\equiv\omega/k_{\rm B}T_{0}, and kBk_{\rm B} is the Boltzmann constant. In addition to this monopole there are small fluctuations in the primary CMB arising from primordial density fluctuations at the time of emission. Small fluctuations in intensity are related to the changes in the characteristic black-body temperature by

δII0\displaystyle\frac{\delta I}{I_{0}} =\displaystyle= x1exδTT0.\displaystyle\frac{x}{1-e^{-x}}\frac{\delta T}{T_{0}}.

The root mean squared average of these primary fluctuations is 𝒪(102)μK{\cal O}(10^{2})\mu{\rm K}. As the CMB radiation propagates towards Earth there are foreground effects modifying the intensity which give rise to secondary fluctuations in the CMB. We expect the chameleonic SZ effect in galaxy clusters to be one such foreground. When considering these foreground effects, one generally treats the primary CMB fluctuations as Gaussian noise on top of the CMB monopole signal.

The primordial CMB radiation is also weakly polarized. The intensity and polarization of radiation in general is described by its Stokes vector (I,Q,U,V)(I,\,Q,\,U,\,V). The fractional linear polarization of the CMB is of the order Q21/2=U21/2106\langle Q^{2}\rangle^{1/2}=\langle U^{2}\rangle^{1/2}\sim 10^{-6}, while the circular polarization component, VV, is predicted to be zero from parity considerations in the early Universe.

IV.2 The Thermal SZ Effect

In the standard SZ effect the predicted fractional change to the temperature of CMB photons passing through a galaxy cluster is Birkinshaw99

ΔTSZT0=kBTemeτ0(xcoth(x2)4),\displaystyle\frac{\Delta T_{\mathrm{SZ}}}{T_{0}}=\frac{k_{\rm B}T_{\rm e}}{m_{\rm e}}\tau_{0}\left(x\coth\left(\frac{x}{2}\right)-4\right)\,, (45)

where x=ω/kBT0x=\omega/k_{\rm B}T_{0}, TeT_{\rm e} is the temperature of the electrons in the plasma, and τ0σTne(l)dl\tau_{0}\equiv\int\sigma_{\rm T}n_{\rm e}(l)\mathrm{d}l is the optical depth given by the integral along the line of sight of the number density of electrons multiplied by the Thompson cross-section, σT=6.65×1029m2\sigma_{\rm T}=6.65\times 10^{-29}{\rm m}^{2}. At low frequencies the SZ effect is seen as a decrement in the expected temperature from the CMB, while at high frequencies it is seen as a boost in the temperature. There are relativistic corrections to the above formula, but for the specific case of the Coma cluster that we consider in this paper the peculiar velocity is small and higher order corrections to the thermal SZ effect are negligible Itoh .

IV.3 The Chameleonic SZ Effect

We found in §II that on passing through a magnetic field of length LL, the photon-scalar mixing alters the intensity of light from I0I_{0} to IfI_{\rm f}, where IfI_{\rm f} is given by

If\displaystyle I_{\rm f} =\displaystyle= I0(1𝒫γϕ(L))\displaystyle I_{0}\left(1-\mathcal{P}_{\gamma\leftrightarrow\phi}(L)\right)
+Q0𝒬q(L)+U0𝒬u(L)+V0𝒬v(0).\displaystyle+Q_{0}\mathcal{Q}_{\rm q}(L)+U_{0}\mathcal{Q}_{\rm u}(L)+V_{0}\mathcal{Q}_{\rm v}(0).

The Q0Q_{0}, U0U_{0} and V0V_{0} are the initial values of the Stokes parameters. The CMB radiation is only very weakly polarized and observations confirm Q021/2/I0\left\langle Q_{0}^{2}\right\rangle^{1/2}/I_{0}, U021/2/I0𝒪(106)\left\langle U_{0}^{2}\right\rangle^{1/2}/I_{0}\sim{\cal O}(10^{-6}) and V021/2/I0106\left\langle V_{0}^{2}\right\rangle^{1/2}/I_{0}\ll 10^{-6}. The root mean squared values of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} are, however, all of similar magnitude, 𝒪(𝒫¯γϕ)\mathcal{O}(\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}). In addition to this the measurement issues arising from a finite frequency bin, as discussed in Appendix A.3, mean that the observed variance will be significantly reduced. Hence, for CMB photons, we have that

IfI0(1𝒫¯γϕ(L)),I_{\rm f}\approx I_{0}\left(1-\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L)\right),

and so the change in intensity due to the chameleonic SZ effect, ΔICSZ\Delta I_{\rm CSZ}, is given by

ΔICSZI0=𝒫¯γϕ(L).\displaystyle\frac{\Delta I_{\rm CSZ}}{I_{0}}=-\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L).

Transforming this to a change in temperature we have,

ΔTCSZT0=1exxΔICSZI0=ex1x𝒫¯γϕ(L).\displaystyle\frac{\Delta T_{\rm CSZ}}{T_{0}}=\frac{1-e^{-x}}{x}\frac{\Delta I_{\rm CSZ}}{I_{0}}=\frac{e^{-x}-1}{x}\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L).

where as before x=ω/kT0x=\omega/kT_{0}. We evaluated the expected value of 𝒫γϕ(L)\mathcal{P}_{\gamma\leftrightarrow\phi}(L) for different models of the IC magnetic field in §II above, and we note that it depends both on nen_{\rm e}, 𝐁\mathbf{B} and frequency ω\omega. We assume that inside the cluster 𝐁21/2neη\left\langle\mathbf{B}^{2}\right\rangle^{1/2}\propto\left\langle n_{\rm e}\right\rangle^{\eta}. This implies for the cell model we have,

ΔICSZI0ne2(1η)ω2,\displaystyle\frac{\Delta I_{\rm CSZ}}{I_{0}}\propto n_{\rm e}^{-2(1-\eta)}\omega^{2}, (46)

whereas in the power spectrum model, where PB(k)PN(k)kα2P_{\rm B}(k)\propto P_{\rm N}(k)\propto k^{\alpha-2} for kkcritk\geq k_{\rm crit} (Eq. (43)) and α<1\alpha<-1, we have to leading order,

ΔICSZI0ne2η+αωα,\displaystyle\frac{\Delta I_{\rm CSZ}}{I_{0}}\propto n_{\rm e}^{2\eta+\alpha}\omega^{-\alpha}, (47)

for the case α>2\alpha>-2. For α<2\alpha<-2, we find the above behaviour for higher frequencies, whereas at lower frequencies we find the same leading order scaling as we had in the cell model. A Kolmogorov spectrum for the magnetic turbulence has α=5/3\alpha=-5/3, if we take η=0.9\eta=0.9 as suggested by observations, then the CSZ effect scales as ne2/15ω5/3n_{\rm e}^{2/15}\omega^{5/3}.

For comparison, the thermal SZ effect is proportional to nen_{\rm e} and has a non-power law frequency dependence. We note that for α<1\alpha<-1 and η1\eta\leq 1, ΔICSZ/I0\Delta I_{\rm CSZ}/I_{0} always has a shallower nen_{\rm e} dependence than ΔISZ/I0\Delta I_{\rm SZ}/I_{0}. In principle, the chameleonic SZ effect can be distinguished from the standard contributions to the SZ effect using both its electron density and frequency dependences. It should be noted, though, that in both Eqs. (46) and (47) we have assumed that the magnetic and electron density correlation lengths do not vary as nen_{\rm e} varies. Simulations suggest that the correlation length increases with radius, although the precise form of this variation is uncertain. If we assume that Lcoh=LBLNL_{\rm coh}=L_{\rm B}\propto L_{\rm N}, and estimate the high-kk power spectrum according to the prescription given in §III.1, we see that

ΔICSZI0ne2η+α0ωα0Lcoh1+α0,\frac{\Delta I_{\rm CSZ}}{I_{0}}\propto n_{\rm e}^{2\eta+\alpha_{0}}\omega^{-\alpha_{0}}L_{\rm coh}^{1+\alpha_{0}},

where α0=α\alpha_{0}=\alpha if 2α<1-2\leq\alpha<-1, and α0=2\alpha_{0}=-2 in the cell model. The LcohL_{\rm coh} scaling for α<2\alpha<-2 is more complicated, at higher frequencies it is given by the above formula with α0=α\alpha_{0}=\alpha, whereas at lower frequencies, ΔICSZ\Delta I_{\rm CSZ} is independent of LcohL_{\rm coh} at leading order. In what follows we assume that 2α<1-2\leq\alpha<-1 for the power spectrum model. We discuss how the spatial variation of ΔICSZ\Delta I_{\rm CSZ} can be used to constrain photon-scalar mixing further in §V.3 below.

V Application

In this section, we apply the results derived above to constrain the probability of photon-scalar mixing at CMB frequencies in the intra-cluster medium. We found that in the power spectrum model, 𝒫¯γϕωα\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}\propto\omega^{-\alpha}, for 2α<1-2\leq\alpha<-1 where α\alpha is the slope of the power spectra for the magnetic and electron density fluctuations in the region kkcritk\geq k_{\rm crit} (Eq. (43)). The cell model for the magnetic field effectively has α=2\alpha=-2. We write

𝒫¯γϕ(L,ω)=𝒫¯γϕ(L,ω0)(ωω0)α,\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega)=\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega_{0})\left(\frac{\omega}{\omega_{0}}\right)^{-\alpha},

for some fixed frequency ω0\omega_{0} of the order of the CMB frequency. For given objects we are able to constrain 𝒫¯γϕ(L,ω0)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega_{0}), the average probability of photon to scalar conversion at ω0\omega_{0}. We pick ω0\omega_{0} so that for the range, 2α<1-2\leq\alpha<-1, the resulting constraint on 𝒫¯γϕ(L,ω)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega) is almost independent of α\alpha.

V.1 Magnitude of Chameleonic SZ Effect

Using our evaluation of 𝒫¯γϕ(L,ω)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega) in Eqs. (II.1) and (II.2), a constraint on 𝒫¯γϕ(L,ω0)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega_{0}) can be be transformed into a constraint on the effective photon-scalar coupling geff=1/Meffg_{\rm eff}=1/M_{\rm eff}. 𝒫¯γϕ(L,ω0)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega_{0}) depends on quantities which are not known a priori, such as 𝐁2\left\langle\mathbf{B}^{2}\right\rangle, ne\left\langle n_{\rm e}\right\rangle, ne2\left\langle n_{\rm e}^{2}\right\rangle, LBL_{\rm B}, LNL_{\rm N}, CBC_{\rm B} and CNC_{\rm N}. The accuracy to which these parameters can be measured or estimated will therefore limit the constraints on geffg_{\rm eff}. The derived constraint on geffg_{\rm eff} will also depend strongly on α\alpha. We explicitly consider the relation between geffg_{\rm eff} and 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} for two models: the cell model where effectively α=2\alpha=-2 and the Kolmogorov turbulence model where α=5/3\alpha=-5/3. The constraint on 𝒫¯γϕ(L,ω0)\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L,\omega_{0}) is, however, reasonably model independent, with only a slight dependence on α\alpha.

In the cell model, Eq. (II.1) gives,

𝒫(cell)(L,ν)\displaystyle\mathcal{P}^{(\rm cell)}(L,\nu) =\displaystyle= (3.2×1010)g102B10μG2n0.012\displaystyle\left(3.2\times 10^{-10}\right)g_{10}^{2}B_{10\mu{\rm G}}^{2}n_{0.01}^{-2}
L200(L1kpccoh)1ν2142,\displaystyle L_{200}(L^{\rm coh}_{1\,{\rm kpc}})^{-1}\nu_{214}^{2}\,,

where B10μG=δ𝐁21/2/10μGB_{10\mu{\rm G}}=\left\langle\delta\mathbf{B}^{2}\right\rangle^{1/2}/10\mu{\rm G}, n0.01=ne/102cm3n_{0.01}=n_{\rm e}/10^{-2}{\rm cm}^{-3}, ν214=ν/214GHz\nu_{214}=\nu/214\,{\rm GHz}, L200=L/200kpcL_{200}=L/200\,{\rm kpc}, L1kpccoh=Lcoh/1kpcL^{\rm coh}_{1\,{\rm kpc}}=L_{\rm coh}/1\,{\rm kpc} and g10=geff/(1010GeV1)g_{10}=g_{\rm eff}/(10^{-10}\,{\rm GeV}^{-1}). We have assumed Δ¯/N1\bar{\Delta}/N\gg 1 and that measurements are over a finite frequency bin so that sin2(Δ¯/N)1/2\sin^{2}(\bar{\Delta}/N)\approx 1/2.

A potentially more realistic model for the magnetic field structure is to assume that the magnetic and electron density power spectra follow a Kolmogorov power law for kk ranging from Lcoh1L_{\rm coh}^{-1} to at least kcritk_{\rm crit}, where kcritk_{\rm crit} is given by Eq. (43). For kLcoh1k\lesssim L_{\rm coh}^{-1} we assume that k2P(k)k^{2}P(k) is either approximately flat or increasing. The dominant contribution to the magnetic field fluctuations then comes from spatial scales of about LcohL_{\rm coh}. In §III.1, we considered a parameterisation of PB(k)P_{\rm B}(k) with these properties, and found

2CKk05/3=(0.270.45)δ𝐁2LB2/3.\displaystyle 2C_{\rm K}k_{0}^{5/3}=(0.27\text{--}0.45)\left\langle\delta\mathbf{B}^{2}\right\rangle L_{\rm B}^{-2/3}.

We also assume that the δne/n¯e\delta n_{\rm e}/\bar{n}_{\rm e} power spectrum is proportional to that of δ𝐁\delta\mathbf{B}. Under these assumptions, Eq. (II.2) gives,

𝒫(Kolmo)(L,ν)=(2.43.8×107)g102B10μG2n0.015/3\displaystyle\mathcal{P}^{(\rm Kolmo)}(L,\nu)=\left(2.4\text{--}3.8\times 10^{-7}\right)g_{10}^{2}B_{10\mu{\rm G}}^{2}n_{0.01}^{-5/3}
ν2145/3L200(L1kpccoh)2/3(IN2(2IN1)12).\displaystyle\nu_{214}^{5/3}L_{200}\left(L^{\rm coh}_{1\,{\rm kpc}}\right)^{-2/3}\left(\frac{I_{N}^{2}(2I_{N}-1)}{12}\right).

A reasonable value for INI_{\rm N} based on electron density fluctuations in our galaxy is IN12I_{\rm N}\sim 1\text{--}2, and hence IN2(2IN1)112I_{\rm N}^{2}(2I_{\rm N}-1)\sim 1\text{--}12.

The relationship between magnetic field strength and coherence length found from a study of 16 non-cooling core clusters (Eq. (44)) allows us to simplify the above prediction for the case of non-cooling core clusters. For the range 1kpc<Lcoh<100kpc1\,{\rm kpc}<L_{\rm coh}<100\,{\rm kpc}, we find that in the cell model,

8.0×1014𝒫(cell)g102L200n0.012ν21423.2×109.\displaystyle 8.0\times 10^{-14}\lesssim\frac{\mathcal{P}^{(\rm cell)}}{g_{10}^{2}L_{200}n_{0.01}^{-2}\nu_{214}^{2}}\lesssim 3.2\times 10^{-9}.

Similarly in the Kolmogorov power spectrum model, including the range for IN12I_{\rm N}\sim 1\text{--}2, we find

2.2×1011𝒫(Kolmo)g102L200n0.015/3ν2145/33.8×106.\displaystyle 2.2\times 10^{-11}\lesssim\frac{\mathcal{P}^{(\rm Kolmo)}}{g_{10}^{2}L_{200}n_{0.01}^{-5/3}\nu_{214}^{5/3}}\lesssim 3.8\times 10^{-6}.

Cooling core clusters generally have slightly higher magnetic fields and so we might expect them to exhibit a greater chameleon effect. Hydra A is a good example of a galaxy cluster with strong cooling flows Taylor93 . Faraday RMs from an embedded radio source in the cluster have been analysed to suggest a smooth component to the magnetic field of strength 6μG6\,\mu\mathrm{G} ordered on 100kpc100\,\mathrm{kpc} scales and a tangled component of strength 30μG30\,\mu\mathrm{G} ordered on scales of 4kpc4\,\mathrm{kpc}. It is this latter component which makes the dominant contribution to 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}. X-ray data of the cluster indicate a core radius of Rcore=130kpcR_{\rm core}=130\,\mathrm{kpc} and average electron density of 102cm310^{-2}\,\mathrm{cm^{-3}}. We approximate the path length, LL, as being equal to twice the core radius Lcore=2Rcore=260kpcL_{\rm core}=2R_{\rm core}=260\,{\rm kpc}. With these values we find (taking IN=12)I_{\rm N}=1\text{--}2),

𝒫Hydra(cell)\displaystyle\mathcal{P}_{\rm Hydra}^{\rm(cell)} =\displaystyle= (0.93×109)g102ν2142,\displaystyle\left(0.93\times 10^{-9}\right)g_{10}^{2}\nu_{214}^{2},
𝒫Hydra(Kolmo)\displaystyle\mathcal{P}_{\rm Hydra}^{\rm(Kolmo)} =\displaystyle= (0.9017.9×107)g102ν2145/3.\displaystyle\left(0.90\text{--}17.9\times 10^{-7}\right)g_{10}^{2}\nu_{214}^{5/3}.

If, on the other hand, we consider a specific example of a non-cooling core cluster such as the nearby Coma cluster of galaxies, we find little change to the chameleon-photon conversion rate. The IC magnetic field at the centre of the Coma cluster was determined from Faraday RMs of an embedded source by Feretti et al. Feretti95 . They found a uniform component of strength 0.2±0.1μG0.2\pm 0.1\,\mu\mathrm{G} coherent on scales of 200kpc200\,\mathrm{kpc} and a tangled component of strength 8.5±1.5μG8.5\pm 1.5\,\mu\mathrm{G} coherent on much shorter scales of 1kpc1\,\mathrm{kpc} extending across the core region of the cluster (Lcore198kpcL_{\rm core}\approx 198\,\mathrm{kpc}). The electron density at the centre of the cluster is 4×103cm34\times 10^{-3}{\rm cm}^{-3}. We approximate LL by LcoreL_{\rm core}, and find

𝒫Coma(cell)\displaystyle\mathcal{P}_{\rm Coma}^{\rm(cell)} =\displaystyle= (1.4×109)g102ν2142,\displaystyle\left(1.4\times 10^{-9}\right)g_{10}^{2}\nu_{214}^{2}, (48)
𝒫Coma(Kolmo)\displaystyle\mathcal{P}_{\rm Coma}^{\rm(Kolmo)} =\displaystyle= (0.6412.7×107)g102ν2145/3.\displaystyle\left(0.64\text{--}12.7\times 10^{-7}\right)g_{10}^{2}\nu_{214}^{5/3}. (49)

We note that although the Coma cluster core has a weaker magnetic field compared to Hydra A, it also has a lower electron density which enhances the chameleon effect. Hence the two factors approximately balance out to give a similar magnitude of the CSZ effect for both Hydra A and Coma.

V.2 The Coma Cluster

The nearby Coma cluster of galaxies is unique in having detailed measurements of both its magnetic field structure and the SZ effect. Using SZ measurements along lines of sight through the core of the Coma cluster, we are able to constrain 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} for the Coma cluster. The SZ effect towards the centre of the cluster has been measured over a range of frequencies by various probes: OVRO, WMAP and MITO. These results have been assimilated and analysed in Batistelli03 . The frequency measurements of the change to the CMB background temperature are summarized in Table 2 and plotted in Fig 2.

Experiment ν/GHz\nu/\mathrm{GHz} δν/GHz\delta\nu/\mathrm{GHz} ΔTSZ/μK\Delta T_{\mathrm{SZ}}/\mu K
OVRO 32.0 6.5 520±83-520\pm 83
WMAP 60.8 13.0 240±180-240\pm 180
WMAP 93.5 19 340±180-340\pm 180
MITO 143 30 184±39-184\pm 39
MITO 214 30 32±79-32\pm 79
MITO 272 32 172±36172\pm 36
Table 2: SZ measurements of the Coma cluster.
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Figure 2: SZ measurements of the Coma cluster from OVRO, WMAP and MITO. The solid line is the predicted thermal SZ effect assuming a maximum likelihood optical depth, τ0=4.7×103\tau_{0}=4.7\times 10^{-3}. The dashed line is the upper bound to the maximum likelihood fit for the combined thermal and chameleonic SZ effects.

The predicted thermal SZ effect was given in Eq. (45) and depends on the optical depth and the electron temperature in the plasma. For the Coma cluster atmosphere, kTe8.2keVkT_{\rm e}\simeq 8.2\,\mathrm{keV}. The optical depth τ0\tau_{0} is generally treated as an unknown parameter and inferred from the intensity measurements using a maximum likelihood analysis. Including the chameleonic contribution which is assumed to scale as ωα\omega^{-\alpha}, the predicted form for ΔT/T0\Delta T/T_{0} in the Coma cluster is,

ΔTpredT0\displaystyle\frac{\Delta T^{\rm pred}}{T_{0}} =\displaystyle= 1.6×102(xcoth(x2)4)τ0\displaystyle 1.6\times 10^{-2}\left(x\coth\left(\frac{x}{2}\right)-4\right)\tau_{0}
+(ex1)xα01(kBT0ω0)α0𝒫Coma(ω0),\displaystyle+\left(e^{-x}-1\right)x^{-\alpha_{0}-1}\left(\frac{k_{\rm B}T_{0}}{\omega_{0}}\right)^{-\alpha_{0}}\mathcal{P}_{\rm Coma}(\omega_{0}),

where x=ω/kBT0x=\omega/k_{\rm B}T_{0}; α0=α\alpha_{0}=\alpha if 2α<1-2\lesssim\alpha<-1 in the power spectrum model and α0=2\alpha_{0}=-2 in the cell model; and 𝒫Coma(ω0)=𝒫γϕ(L,ω0)\mathcal{P}_{\rm Coma}(\omega_{0})=\mathcal{P}_{\gamma\leftrightarrow\phi}(L,\omega_{0}) for lines

of sight through the centre of the Coma cluster. We maximize the likelihood, LL, over the parameter space of τ0\tau_{0} and 𝒫Coma(ω0)\mathcal{P}_{\rm Coma}(\omega_{0}) where

2logL=i(ΔTiobsΔTipred(τ0,𝒫Coma))2σi2.\displaystyle-2\log L=\sum_{i}\frac{(\Delta T_{i}^{\rm obs}-\Delta T^{\rm pred}_{i}(\tau_{0},\mathcal{P}_{\rm Coma}))^{2}}{\sigma_{i}^{2}}.

Here ΔTiobs\Delta T_{i}^{\rm obs} are the observed values of ΔT\Delta T at a frequency νi=ωi/2π\nu_{i}=\omega_{i}/2\pi, and σi\sigma_{i} are their standard errors. ΔTipred\Delta T^{\rm pred}_{i} are the values of ΔT\Delta T as given by Eq. (V.2). We define τ^0\hat{\tau}_{0} and 𝒫^Coma\hat{\mathcal{P}}_{\rm Coma} to be the best fit values of τ0\tau_{0} and 𝒫Coma\mathcal{P}_{\rm Coma}. Confidence limits are then estimated by assuming that

χ2(τ0,𝒫Coma)=2log(L(τ0,𝒫Coma)L(τ^0,𝒫^Coma)),\displaystyle\chi^{2}(\tau_{0},\mathcal{P}_{\rm Coma})=-2\log\left(\frac{L(\tau_{0},\mathcal{P}_{\rm Coma})}{L(\hat{\tau}_{0},\hat{\mathcal{P}}_{\rm Coma})}\right),

follows a χ12\chi^{2}_{1} distribution. We find that when ω0=0.844meV\omega_{0}=0.844\,{\rm meV} (ν=204GHz\nu=204\,{\rm GHz}), the constraints on 𝒫Coma\mathcal{P}_{\rm Coma} are almost independent of α0\alpha_{0}. For all 2α0<1-2\leq\alpha_{0}<-1, the best fit value and estimated standard error of τ0\tau_{0} is virtually independent of α0\alpha_{0}. Fig. 3 shows the 68%68\%, 95%95\% and 99.9%99.9\% confidence limits on τ0\tau_{0} and 𝒫Coma(ω0=0.844meV)\mathcal{P}_{\rm Coma}(\omega_{0}=0.844\,{\rm meV}). Maximizing χ2\chi^{2} with respect to 𝒫Coma{\mathcal{P}}_{\rm Coma}, gives τ0=(4.7±1.0)×103\tau_{0}=(4.7\pm 1.0)\times 10^{-3}. Maximizing with respect to τ0\tau_{0} gives the following 95%95\% confidence limit on 𝒫Coma(204GHz){\mathcal{P}}_{\rm Coma}(204\,{\rm GHz}):

𝒫Coma(204GHz)<6.2×105(95%).\displaystyle{\mathcal{P}}_{\rm Coma}(204\,{\rm GHz})<6.2\times 10^{-5}\quad(95\%).

The dashed line in Fig. 2 shows the best fit total SZ effect for the 95%95\% confidence upper-bound when 𝒫Coma(204GHz)=6.2×105\mathcal{P}_{\rm Coma}(204\,{\rm GHz})=6.2\times 10^{-5}, with α0=2\alpha_{0}=-2. It is clear that the preference towards smaller values of 𝒫Coma\mathcal{P}_{\rm Coma} is due mostly to the measurement points at 143GHz143\,{\rm GHz} and 272GHz272\,{\rm GHz} which have the smallest error bars. A very similar picture is seen for other values of α0\alpha_{0}.

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Figure 3: Confidence limits from Coma cluster SZ measurements on the optical depth, τ0\tau_{0}, and the photon to scalar conversion probability, 𝒫Coma\mathcal{P}_{\rm Coma}, at 204GHz204\,{\rm GHz}.

From Eqs. (48) and (49), we have

𝒫Coma(cell)(204GHz)=(1.3×109)g102(Brand8.5μG)2\displaystyle\mathcal{P}_{\rm Coma}^{(\rm cell)}(204\,{\rm GHz})=\left(1.3\times 10^{-9}\right)g_{10}^{2}\left(\frac{B_{\rm rand}}{8.5\,\mu{\rm G}}\right)^{2}
(4×103cm3ne)2(L198Lcoh),\displaystyle\left(\frac{4\times 10^{-3}\,{\rm cm}^{-3}}{n_{\rm e}}\right)^{2}\left(\frac{L}{198L_{\rm coh}}\right),
𝒫Coma(Kolmo)(204GHz)=(0.5911.8×107)g102(Brand8.5μG)2\displaystyle\mathcal{P}_{\rm Coma}^{(\rm Kolmo)}(204\,{\rm GHz})=\left(0.59\text{--}11.8\times 10^{-7}\right)g_{10}^{2}\left(\frac{B_{\rm rand}}{8.5\,\mu{\rm G}}\right)^{2}
(4×103cm3ne)5/3(L198kpc)(Lcoh1kpc)2/3.\displaystyle\left(\frac{4\times 10^{-3}\,{\rm cm}^{-3}}{n_{\rm e}}\right)^{-5/3}\left(\frac{L}{198\,{\rm kpc}}\right)\left(\frac{L_{\rm coh}}{1\,{\rm kpc}}\right)^{-2/3}.

Fixing Brand=8.5μGB_{\rm rand}=8.5\,\mu{\rm G}, L=198kpcL=198\,{\rm kpc}, Lcoh=1kpcL_{\rm coh}=1\,{\rm kpc} and ne=4×103cm3n_{\rm e}=4\times 10^{-3}\,{\rm cm}^{-3} as suggested by observations, we find that the 95% confidence upper bound on 𝒫Coma\mathcal{P}_{\rm Coma} is equivalent to

geff(cell)<2.2×108GeV1g_{\rm eff}^{\rm(cell)}<2.2\times 10^{-8}\,{\rm GeV}^{-1}

in the cell model for the magnetic field, or

geff(Kolmo)<(7.232.5)×1010GeV1,g_{\rm eff}^{\rm(Kolmo)}<(7.2\text{--}32.5)\times 10^{-10}\,{\rm GeV}^{-1},

if turbulent Kolmogorov power spectrum is assumed. We note that the constraint geff<7.2×1010GeV1g_{\rm eff}<7.2\times 10^{-10}\,{\rm GeV}^{-1}, which corresponds to IN1+δne2/n¯e22I_{\rm N}\equiv 1+\left\langle\delta n_{e}^{2}/\bar{n}_{e}^{2}\right\rangle\approx 2 and the power spectrum being assumed to be of Kolmogorov form, is equivalent to Meff>1.1×109GeVM_{\rm eff}>1.1\times 10^{9}\,{\rm GeV}. This was the constraint on MeffM_{\rm eff} found by limiting the chameleonic production of starlight polarization in Ref. Burrage08 . It is clear that whilst the constraint on 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} at 204GHz204\,{\rm GHz} is reasonably independent of the magnetic field model, the equivalent constraint on geffg_{\rm eff} is not and depends strongly on the form and magnitude of the fluctuations in the magnetic field and the electron number density.

V.3 SZ Profiles

The above analysis for the Coma cluster involves measurements of the average intensity decrement towards the centre of the cluster at multiple frequencies. Higher frequency measurements are more successful in constraining the conversion probability than low frequency ones, since ΔICSZ\Delta I_{\rm CSZ} grows with frequency. Potentially better constraints could be found by also considering the radial profile of the intensity decrement. In §III, we discussed the scaling of the magnetic field and electron density with radius:

n¯e\displaystyle\bar{n}_{e} =\displaystyle= n0(1+r2rc2)3β/2,\displaystyle n_{0}\left(1+\frac{r^{2}}{r_{\rm c}^{2}}\right)^{-3\beta/2},
𝐁21/2\displaystyle\left\langle\mathbf{B}^{2}\right\rangle^{1/2} \displaystyle\propto n¯eη,\displaystyle\bar{n}_{e}^{\eta},

where rcr_{\rm c} is the core radius and we have assumed a β\beta-model for the gas distribution. The standard thermal SZ effect is proportional to the integral of nen_{\rm e} along the line of sight, while the chameleonic SZ effect depends on nen_{\rm e}, 𝐁21/2\left\langle\mathbf{B}^{2}\right\rangle^{1/2} and LcohL_{\rm coh}. As one moves away from the cluster core, simulations show that the coherence length increases, however the radial scaling LcohL_{\rm coh} is uncertain. To calculate the radial dependence of the chameleonic SZ effect, we must specify how LcohL_{\rm coh} depends on rr. We make the simple ansatz that, at least inside the virial radius, Lcohneγ/3βL_{\rm coh}\propto n_{\rm e}^{-\gamma/3\beta} for some γ\gamma, so that

Lcoh\displaystyle L_{\rm coh} =\displaystyle= Lcoh0(1+r2rc2)γ/2,\displaystyle L_{{\rm coh}0}\left(1+\frac{r^{2}}{r_{\rm c}^{2}}\right)^{\gamma/2},

where Lcoh0L_{{\rm coh}0} is the coherence length in the centre of the cluster. Based solely on dimensional grounds, estimated values for γ\gamma are: γ=β\gamma=\beta so that Lcohne1/3L_{\rm coh}\propto n_{\rm e}^{-1/3}, or γ=1\gamma=1 so that LcohrL_{\rm coh}\propto r for large rr. The simulations of Ref. Ohno03 , suggest that for large rr, LcohL_{\rm coh} roughly scales as rr inside the virial radius, rvirr_{\rm vir}.

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Figure 4: Chameleonic (red dot-dashed line for α=2\alpha=-2 and solid blue line for α=5/3\alpha=-5/3) and thermal (dashed black line) SZ intensity decrement profiles for a simulated cluster at six different frequencies (taken to be the same as the frequency bands in the Coma cluster measurements). The simulated cluster has 𝒫γϕ(204GHz)=3×105\mathcal{P}_{\gamma\leftrightarrow\phi}(204\,{\rm GHz})=3\times 10^{-5} and τ0=5×103\tau_{0}=5\times 10^{-3} through the centre of the cluster, rc=100kpcr_{c}=100\,\mathrm{kpc} and rvir=2Mpcr_{\rm vir}=2\,{\rm Mpc}. We assume η=0.9\eta=0.9 and β=γ=1\beta=\gamma=1.

For a constant δ𝐁2\left\langle\delta\mathbf{B}^{2}\right\rangle, n¯e\bar{n}_{\rm e} and LcohL_{\rm coh}, we found that,

𝒫γϕLLcoh1+α0δ𝐁2n¯eα0,\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}\propto LL_{\rm coh}^{1+\alpha_{0}}\left\langle\delta\mathbf{B}^{2}\right\rangle\bar{n}_{e}^{\alpha_{0}},

where α0=α\alpha_{0}=\alpha if 2α<1-2\leq\alpha<-1 in the power spectrum model, and α0=2\alpha_{0}=-2 in the cell model. When δ𝐁2\left\langle\delta\mathbf{B}^{2}\right\rangle, n¯e\bar{n}_{\rm e} and LcohL_{\rm coh} vary slowly along the line of sight we should change this to

𝒫γϕdzLcoh1+α0(z)δ𝐁2(z)n¯eα0(z)dz.\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}\propto\int{\rm d}zL_{\rm coh}^{1+\alpha_{0}}(z)\left\langle\delta\mathbf{B}^{2}(z)\right\rangle\bar{n}_{e}^{\alpha_{0}}(z){\rm d}z.

We define rr_{\perp} to be the projected distance from the cluster centre for a given line of sight. We also assume that the turbulent cluster magnetic field only extends out to some characteristic radius rmaxr_{\rm max}, and then dies off very quickly due to LcohL_{\rm coh} growing very quickly or δ𝐁2(z)\left\langle\delta\mathbf{B}^{2}(z)\right\rangle decreasing much faster than n¯eη\bar{n}_{\rm e}^{\eta}. We discuss reasonable values for rmaxr_{\rm max} below. With our assumed models for the radial dependence of the coherence length, magnetic field and electron density, we have

𝒫γϕ(r)Lcore(1+r2rc2)p2Ix(r;p,rmax,rc),\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}(r_{\perp})\propto L_{\rm core}\left(1+\frac{r_{\perp}^{2}}{r_{\rm c}^{2}}\right)^{\frac{p}{2}}I_{x}(r_{\perp};p,r_{\rm max},r_{c}), (51)

where p=1+(1+α0)γ3β(2η+α0)p=1+(1+\alpha_{0})\gamma-3\beta(2\eta+\alpha_{0}), Lcore=2rcL_{\rm core}=2r_{\rm c} and

Ix\displaystyle I_{x} =\displaystyle= 0dx(1+x2)(p1)2w(x;xmax).\displaystyle\int_{0}^{\infty}{\rm d}x\,\left(1+x^{2}\right)^{\frac{(p-1)}{2}}w(x;x_{\rm max}). (52)

We have introduced a window function, w(x)w(x), to impose the rapid decay of magnetic turbulence for rrmaxr\gtrsim r_{\rm max}. A simple model for w(x;xmax)w(x;x_{\rm max}) would be that w=1w=1 for r2<rmax2r^{2}<r_{\rm max}^{2} and 0 otherwise. This corresponds to w=H(xmaxx)w=H(x_{\rm max}-x) where HH is the heaviside function, and

xmax=rmax2r2rc2+r2.x_{\rm max}=\sqrt{\frac{r_{\rm max}^{2}-r_{\perp}^{2}}{r_{\rm c}^{2}+r_{\perp}^{2}}}.

Alternatively, we could impose a smoother decay of the turbulent magnetic field by taking w=exp(r2/rmax2)w=\exp(-r^{2}/r_{\rm max}^{2}), which corresponds to

w(x)=exp(r2+(rc2+r2)x2rmax2).\displaystyle w(x)=\exp\left(-\frac{r_{\perp}^{2}+(r_{c}^{2}+r_{\perp}^{2})x^{2}}{r_{\rm max}^{2}}\right). (53)

In what follows we approximate w(x)w(x) by this latter form.

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Figure 5: The effective path length LL through the magnetic region. The leftmost plot shows pp values corresponding to η=0.9\eta=0.9 and η=1\eta=1 in the Kolmogorov (α=5/3\alpha=-5/3) and cell (α=2\alpha=-2) magnetic field models when β=γ=1\beta=\gamma=1. These are the values of η\eta suggested by observations and simulations. The rightmost plot shows pp values corresponding to η=1/2\eta=1/2 and η=2/3\eta=2/3 again in the Kolmogorov and cell magnetic field models with β=γ=1\beta=\gamma=1; these are the values of η\eta suggested theoretically. In the Kolmogorov model η={1/2,2/3,0.9,1}\eta=\left\{1/2,2/3,0.9,1\right\} corresponds to p={7/3,4/3,2/30,2/3}p=\left\{7/3,4/3,-2/30,-2/3\right\}. In the cell model the same values of η\eta give p={3,2,6/10,0}p=\left\{3,2,6/10,0\right\}.

All that remains is to determine a reasonable estimate for the largest radius to which the turbulent cluster magnetic field extends, rmaxr_{\rm max}. We note that whenever p>0p>0, the dominant contribution to the integral in Eq. (51) will come from the largest values of xx, i.e. from rrmaxr\sim r_{\rm max}. The value of rmaxr_{\rm max} will, therefore, play an important role in such scenarios. Assuming β=γ=1\beta=\gamma=1, in the cell magnetic field model (α0=2\alpha_{0}=-2) we have pcell=6(1η)p_{\rm cell}=6(1-\eta) and so pcell>0p_{\rm cell}>0 for η<1\eta<1, while if we assume a Kolmogorov spectrum with α0=5/3\alpha_{0}=-5/3 we have pKolmo=6(8/9η)p_{\rm Kolmo}=6(8/9-\eta) and so pcell>0p_{\rm cell}>0 for η<8/9\eta<8/9. In Ref. Ryu08 , the quantity ϖrmstage\varpi_{\rm rms}t_{\rm age} is introduced where taget_{\rm age} is the age of the Universe and ϖrms\varpi_{\rm rms} is the root mean squared value of the vorticity; ϖ=×𝐯\varpi=\nabla\times\mathbf{v}, where 𝐯\mathbf{v} is the peculiar velocity. In Ref. Ryu08 it is estimated that when ϖrmstage\varpi_{\rm rms}t_{\rm age} is greater than 𝒪(1)\mathcal{O}(1), turbulence has had time to develop. In a virialized structure we have the following order of magnitude estimates: ϖO(v(r)/r)\varpi\sim O(v(r)/r) and v2(r)O(M(r)/r)v^{2}(r)\sim O(M(r)/r) where M(r)M(r) is the mass inside a radius rr. Thus,

ϖrmstage𝒪(ρ¯(r)/ρc),\varpi_{\rm rms}t_{\rm age}\sim{\cal O}(\sqrt{\bar{\rho}(r)/\rho_{\rm c}}),

where ρ¯(r)\bar{\rho}(r) is the average density inside a radius rr and ρc\rho_{\rm c} is the cosmological critical density today. Beyond the virial radius, we expect that ϖ2<𝒪(M(r)/r2)\varpi^{2}<{\cal O}(M(r)/r^{2}), as the vorticity acts to slow down the collapse. Roughly then we expect ωrmstage\omega_{\rm rms}t_{\rm age} to be smaller than a few when rrvirr\gg r_{\rm vir}, and larger at smaller radii. We choose rmaxr_{\rm max} so that the chameleonic SZ effect dies off quickly for r>rvirr>r_{\rm vir}. With the choice Gaussian window function given in Eq. (53), a suitable choice is rmaxrvirr_{\rm max}\approx r_{\rm vir}.

We have the following approximate scalings for the thermal and chameleonic SZ effects:

ΔTSZT0\displaystyle\frac{\Delta T_{\rm SZ}}{T_{0}} \displaystyle\propto (1+r2rc2)123β2,\displaystyle\left(1+\frac{r_{\perp}^{2}}{r_{\rm c}^{2}}\right)^{\frac{1}{2}-\frac{3\beta}{2}},
ΔTCSZT0\displaystyle\frac{\Delta T_{\rm CSZ}}{T_{0}} \displaystyle\propto (1+r2rc2)p2Ix(r;p,rvir,rc),\displaystyle\left(1+\frac{r_{\perp}^{2}}{r_{\rm c}^{2}}\right)^{\frac{p}{2}}I_{x}(r_{\perp};p,r_{\rm vir},r_{\rm c}),

where IxI_{x} is given by Eq. (52) and we take the Gaussian window function given in Eq. (53) to impose the decay of the turbulent magnetic field for r>rmaxrvirr>r_{\rm max}\approx r_{\rm vir}. For rrvirr_{\perp}\ll r_{\rm vir}, the chameleonic contribution to the SZ effect will decrease less rapidly than the thermal one when,

p+3β1=(1+α0)γ+3(1α02η)β>0.p+3\beta-1=(1+\alpha_{0})\gamma+3(1-\alpha_{0}-2\eta)\beta>0.

For γβ\gamma\approx\beta, and η1\eta\leq 1 this holds for all 2α0<1-2\leq\alpha_{0}<-1. Hence, even if the thermal SZ effect dominates near the centre of the cluster, measurements of the SZ effect at radii rcrrvirr_{\rm c}\ll r\ll r_{\rm vir} might be able to detect the chameleonic effect.

In Fig. 4 we plot the predicted profiles for the chameleonic and thermal SZ effects at different frequencies for a model cluster, with η=0.9\eta=0.9 and β=γ=1\beta=\gamma=1. We assume that the cluster properties are similar to those of the Coma cluster and assume 𝒫γϕ=3×105\mathcal{P}_{\gamma\leftrightarrow\phi}=3\times 10^{-5} at ν=204GHz\nu=204\,{\rm GHz} for a line of sight through the centre of the cluster. This is roughly the 1σ\sigma confidence limit derived earlier from Coma cluster observations. We take rc100kpcr_{\rm c}\approx 100\,{\rm kpc}, and rmaxrvir2Mpcr_{\rm max}\approx r_{\rm vir}\approx 2\,{\rm Mpc}. The optical depth for a line of sight through the centre of cluster is taken to be τ0=5×103\tau_{0}=5\times 10^{-3}. The black dashed line shows the usual thermal SZ effect, the dot-dashed red line is the chameleonic SZ effect for α0=2\alpha_{0}=-2 (cell model) and the solid blue line is the chameleonic SZ effect for α0=5/3\alpha_{0}=-5/3 (Kolmogorov turbulence model). In general, the smaller the value of η\eta, the more slowly the chameleonic SZ effect decays with distance from the cluster centre. We note that for 30GHzν300GHz30\,{\rm GHz}\lesssim\nu\lesssim 300\,\rm GHz, a chameleonic SZ effect of this magnitude dominates over the thermal SZ effect for r500kpcr_{\perp}\gtrsim 500\,{\rm kpc}. At frequencies around 150GHzν275GHz150\,{\rm GHz}\lesssim\nu\lesssim 275\,{\rm GHz}, the chameleonic SZ effect is dominant for rrcr_{\perp}\gtrsim r_{\rm c}. Measurements of the CMB intensity decrement associated with clusters over such a frequency range and for rrcr\gtrsim r_{\rm c} could be particularly useful in constraining the properties of chameleon-like theories.

There has been some suggestion of a discrepancy between X-ray emission data as measured by ROSAT, which determines the electron density distribution, and the SZ intensity decrement as measured by WMAP ROSATvsWMAP . In the analysis the expected signal derived from X-ray measurements is fitted to the observed SZ effect at large radii. They conclude that the observed intensity decrement at the centre of the cluster is then less than the predicted SZ effect. However a possible alternative is the existence of a chameleon-like scalar field, which would cause an enhancement in the SZ effect at large radii. The WMAP data includes measurements at 94GHz94\,{\rm GHz} for which the chameleon effect could be significant.

In §V.1, we estimated 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} in terms of the properties of the cluster magnetic fields, and approximated the path length, LL, through the magnetic region for a light ray passing through the cluster as being equal to twice the core radius, i.e. LLcore=2rcL\approx L_{\rm core}=2r_{\rm c}. However, the relatively flat radial profile (for rrvirr\lesssim r_{\rm vir}) of the chameleonic SZ effect derived above suggests that LL is generally much larger than LcoreL_{\rm core}, and for p>0p>0 is better approximated as being 𝒪((rvir/rc)pLcore){\cal O}((r_{\rm vir}/r_{\rm c})^{p}L_{\rm core}). Using the model introduced above for the radial behaviour of the electron density, the magnetic field and LcohL_{\rm coh}, we find that the effective path length is given by:

L=LcoreIx(0;p,rmaxrvir,rc).\displaystyle L=L_{\rm core}I_{x}(0;p,r_{\rm max}\approx r_{\rm vir},r_{c}).

It follows from Eq. (52) and Eq. (53) that L/LcoreL/L_{\rm core} depends on two parameters pp and rvir/rcr_{\rm vir}/r_{\rm c}. In Fig. 5, we plot L/LcoreL/L_{\rm core} against rvir/rcr_{\rm vir}/r_{c} for different values of pp. Reasonable estimates for η\eta are η=1/2\eta=1/2, 2/32/3, 0.90.9 and 11. η=1/2\eta=1/2 and η=2/3\eta=2/3 are based upon theoretical expectations, the former being for equipartition of magnetic and thermal energy and the latter being if the magnetic field is frozen in. Observations and simulations suggest that these values are unrealistic and instead indicate η=0.9\eta=0.9 and η=1\eta=1 respectively. With β=γ=1\beta=\gamma=1 and η={0.9,1}\eta=\{0.9,1\}, p={2/30,2/3}p=\{-2/30,-2/3\} in the Kolmogorov model, and p={6/10,0}p=\{6/10,0\} in the cell model. We plot these values of pp for 5<rvir/rc<405<r_{\rm vir}/r_{\rm c}<40 in the leftmost plot of Fig. 5. We can see that in all four cases LcoreL11LcoreL_{\rm core}\lesssim L\lesssim 11L_{\rm core} for the range of rvir/rcr_{\rm vir}/r_{\rm c} considered. Since 𝒫γϕgeff2\mathcal{P}_{\gamma\leftrightarrow\phi}\propto g_{\rm eff}^{2}, this corresponds to no more than a factor 33 or so enhancement in sensitivity to geffg_{\rm eff}. If instead we consider η={1/2,2/3}\eta=\{1/2,2/3\} then p={7/3,4/3}p=\{7/3,4/3\} in the Kolmogorov model and p={3,2}p=\{3,2\} in the cell model. We plot these values of pp in the rightmost plot of Fig. 5. In these cases, we see that LLcoreL\gg L_{\rm core}, and as expected L/Lcore𝒪((rvir/rc)p)L/L_{\rm core}\sim{\cal O}((r_{\rm vir}/r_{\rm c})^{p}). Since η=1/2\eta=1/2 and η=2/3\eta=2/3 do not appear to be supported by observations, and because the structure of cluster magnetic fields at radii rrcorer\gg r_{\rm core} is far from certain, we do not view values of LLcoreL\gg L_{\rm core} as being particularly realistic. The more realistic scenarios are those shown in the leftmost plot in Fig. 5 where 1L/Lcore111\lesssim L/L_{\rm core}\lesssim 11.

VI Modifications to the CMB Polarization

In addition to modifying the intensity of light that has passed through magnetic regions, we found in §II that the presence of a chameleon-like scalar field also alters the polarization of the light. We define Q0Q_{0}, U0U_{0} and V0V_{0} to be the fractional intrinsic CMB polarizations. We found that after mixing with the chameleon in a magnetic region,

Q\displaystyle Q =\displaystyle= Q0+𝒬q,\displaystyle Q_{0}+\mathcal{Q}_{\rm q},
U\displaystyle U =\displaystyle= U0+𝒬u,\displaystyle U_{0}+\mathcal{Q}_{\rm u},
V\displaystyle V =\displaystyle= V0+𝒬v.\displaystyle V_{0}+\mathcal{Q}_{\rm v}.

We use angled brackets to denote an average over many lines of sight at fixed frequency, i.e. fixed Δ\Delta. In both the cell and power spectrum models we find,

𝒬q\displaystyle\left\langle\mathcal{Q}_{\rm q}\right\rangle =\displaystyle= QQ0=𝒬0cos2θreg,\displaystyle\left\langle Q-Q_{0}\right\rangle=\mathcal{Q}_{0}\cos 2\theta_{\rm reg},
𝒬u\displaystyle\left\langle\mathcal{Q}_{\rm u}\right\rangle =\displaystyle= UU0=𝒬0sin2θreg,\displaystyle\left\langle U-U_{0}\right\rangle=\mathcal{Q}_{0}\sin 2\theta_{\rm reg},
𝒬v\displaystyle\left\langle\mathcal{Q}_{\rm v}\right\rangle =\displaystyle= VV0=0,\displaystyle\left\langle V-V_{0}\right\rangle=0,

where Bxreg=BregcosθregB^{\rm reg}_{x}=B^{\rm reg}\cos\theta_{\rm reg} and Byreg=BregsinθregB^{\rm reg}_{y}=B^{\rm reg}\sin\theta_{\rm reg} define θreg\theta_{\rm reg}. Detailed derivations of these formulae are presented in Appendix A. In the cell model,

𝒬012(2BregωMeffmeff2)2sin2Δ¯,\mathcal{Q}_{0}\simeq\frac{1}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},

whereas in the power spectrum model,

𝒬0\displaystyle\mathcal{Q}_{0} \displaystyle\simeq 14(2BregωMeffm¯eff2)2IN3\displaystyle\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}I_{\rm N}^{3}
14(2BregωMeffm¯eff2)2cos(m¯eff2L2ω)\displaystyle-\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}\cos\left(\frac{\bar{m}_{\rm eff}^{2}L}{2\omega}\right)
+Breg2L16Meff2n¯e2IN2WN(kcrit).\displaystyle+\frac{B_{\rm reg}^{2}L}{16M_{\rm eff}^{2}\bar{n}_{\rm e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit}).

In both cases 𝒬0=𝒫reg\mathcal{Q}_{0}=\mathcal{P}^{\rm reg} where 𝒫reg\mathcal{P}^{\rm reg} is the contribution of the regular magnetic field to the conversion probability. In addition to the contribution from mixing in the regular magnetic field along a given line of sight, the Stokes parameters will also pick up a contribution from the turbulent magnetic field. The magnitude and direction of this contribution is determined by the direction and size of the magnetic field fluctuations along the line of sight, and so vanishes when averaged over many lines of sight. Along any given line of sight it would be observed as an essentially random contribution, and would be present in the variance of the 𝒬i\mathcal{Q}_{i}, given by σi2(Δ¯,Δ¯)\sigma_{i}^{2}(\bar{\Delta},\bar{\Delta}):

σi2(Δ1,Δ2)=𝒬i(Δ1)𝒬i(Δ2)𝒬i(Δ1)𝒬i(Δ2).\displaystyle\sigma_{i}^{2}(\Delta_{1},\Delta_{2})=\left\langle\mathcal{Q}_{i}(\Delta_{1})\mathcal{Q}_{i}(\Delta_{2})\right\rangle-\left\langle\mathcal{Q}_{i}(\Delta_{1})\right\rangle\left\langle\mathcal{Q}_{i}(\Delta_{2})\right\rangle.

A detailed calculation of these σi\sigma_{i} is given in Appendix A. We find similar results for both the cell and power spectrum models. In the latter we have,

σq2(Δ¯,Δ¯)\displaystyle\sigma_{\rm q}^{2}(\bar{\Delta},\bar{\Delta}) \displaystyle\approx 12𝒫¯γϕ2+12𝒬02cos4θreg,\displaystyle\frac{1}{2}\bar{\mathcal{P}}^{2}_{\gamma\leftrightarrow\phi}+\frac{1}{2}\mathcal{Q}_{0}^{2}\cos 4\theta_{\rm reg},
σu2(Δ¯,Δ¯)\displaystyle\sigma_{\rm u}^{2}(\bar{\Delta},\bar{\Delta}) \displaystyle\approx 12𝒫¯γϕ212𝒬02cos4θreg,\displaystyle\frac{1}{2}\bar{\mathcal{P}}^{2}_{\gamma\leftrightarrow\phi}-\frac{1}{2}\mathcal{Q}_{0}^{2}\cos 4\theta_{\rm reg},
σv2(Δ¯,Δ¯)\displaystyle\sigma_{\rm v}^{2}(\bar{\Delta},\bar{\Delta}) \displaystyle\approx 12𝒫¯γϕ212𝒬02.\displaystyle\frac{1}{2}\bar{\mathcal{P}}^{2}_{\gamma\leftrightarrow\phi}-\frac{1}{2}\mathcal{Q}_{0}^{2}\,.

Hence, looking along a single line of sight at a single frequency, we would expect |Q||Q|, |U||U|, |V|𝒪(𝒫¯γϕ/2)|V|\sim\mathcal{O}(\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}/\sqrt{2}), since 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} is dominated by the contribution from the random magnetic field (𝒫¯γϕ𝒫reg=𝒬0\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}\gg\mathcal{P}^{\rm reg}=\mathcal{Q}_{0}). The best upper bound on 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} from the Coma cluster SZ measurements was,

𝒫¯γϕ(204GHz)<6.2×105,\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(204\,{\rm GHz})<6.2\times 10^{-5},

along lines of sight passing though the Coma cluster core. Along such lines of sight, we might expect chameleonic contributions to QQ, UU and VV that are as large as a few×105{\rm few}\times 10^{-5}. If this were the case then the magnitude of all three Stokes parameters would be roughly 10100μK10-100\,\mu{\rm K}, which is orders of magnitude larger than the measured 0.11μK0.1-1\mu{\rm K} level of QQ and UU and the even lower bound on the circular polarization, VV. One might imagine, therefore, that CMB polarization measurements could greatly improve the upper limit on 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}, say placing it around the 10710^{-7} level. We found in §V.2 that in the Kolmogorov model for the power spectrum of magnetic fluctuations, 𝒫Coma(Kolmo)\mathcal{P}_{\rm Coma}^{\rm(Kolmo)} could be almost as large as 10610^{-6} with g10O(1)g_{10}\sim O(1). An upper limit of 10710^{-7} could therefore constrain Meff1010GeVM_{\rm eff}\gtrsim 10^{10}\,{\rm GeV}. However, there are two important caveats of which we must take account and which limit the ability of realistic experiments to detect the chameleonic contribution to the CMB polarization.

Firstly, the random effect (whose variance is given by the σi2\sigma_{i}^{2}) vanishes when one averages over many lines of sight which have taken different paths through the random magnetic regions. The coherence length, LcohL_{\rm coh}, provides the typical length scale of the random magnetic regions. We therefore expect that roughly parallel light rays with a perpendicular separation dLcohd\gg L_{\rm coh} will have taken different paths through the magnetic regions. If the cluster in question is a distance, DclustdD_{\rm clust}\gg d, from us then light rays with a separation, dLcohd\lesssim L_{\rm coh}, will subtend an angle θcoh\lesssim\theta_{\rm coh} when observed on the sky, where

θcoh=10800πLcohDclustarcmin.\theta_{\rm coh}=\frac{10800}{\pi}\frac{L_{\rm coh}}{D_{\rm clust}}\,{\rm arcmin}.

As an example we consider the values for these quantities for the Coma and Hydra A clusters: (Dclust,Lcoh)(100Mpc,1kpc)(D_{\rm clust},L_{\rm coh})\sim(100\,{\rm Mpc},1\,{\rm kpc}) and (50Mpc,4kpc)\sim(50\,{\rm Mpc},4\,{\rm kpc}) respectively. This results in θcoh0.03arcmin\theta_{\rm coh}\sim 0.03\,{\rm arcmin} for Coma and θcoh0.27arcmin\theta_{\rm coh}\sim 0.27{\rm arcmin} for Hydra A. In order to resolve the random chameleonic contribution to the CMB polarization, a survey must have an angular resolution better than θcoh\theta_{\rm coh}. The polarization of the CMB in the direction of galaxy clusters has not so far been measured, but there are plans to incorporate a polarization detector at the South Pole Telescope, SPT-pol, which is expected to be completed in the next few years SPTelescope . SPT is searching for clusters on the sky by exploiting the SZ effect. Each pixel of detectors at SPT represents one arc-minute, and the aim is to have 10μK10\,\mu{\rm K} sensitivity per pixel. For a cluster such as Coma where LcohL_{\rm coh} is relatively small, this one arc-minute angular resolution is not enough to resolve the random chameleonic contribution to the polarization. Even for a cluster such as Hydra A where Lcoh/DclustL_{\rm coh}/D_{\rm clust} is larger, it is still a factor of four larger than θcoh\theta_{\rm coh}. In general, resolving the random chameleonic contribution to the Stokes parameters will require an ability to resolve the polarization signal on scales smaller than a few arc-seconds.

Even if one has the required angular resolution, there is still an additional technical limit on the ability to detect the random chameleonic modification to the Stokes parameters. The expressions given for the σi2\sigma_{i}^{2} assume that measurements are made at precisely one frequency. Any realistic measurement will, however, not be entirely monochromatic but represent an average over some frequency band. Suppose one makes a measurement at a nominal wavelength, λ¯\bar{\lambda}, which is actually an average (with some window function) over a range λλ¯(δλ,δλ)\lambda-\bar{\lambda}\in(-\delta\lambda,\delta\lambda). This corresponds to the value of Δ¯\bar{\Delta} running between Δ¯δΔ\bar{\Delta}-\delta\Delta and Δ¯+δΔ\bar{\Delta}+\delta\Delta where δΔ=Δ¯(δλ/λ)\delta\Delta=\bar{\Delta}(\delta\lambda/\lambda). The measured variance in the Stokes parameters will then be given by,

σ^i2(Δ¯)=1(2δΔ)2Δ¯δΔΔ¯+δΔdΔ1Δ¯δΔΔ¯+δΔdΔ2σi2(Δ1,Δ2).\displaystyle\hat{\sigma}^{2}_{i}(\bar{\Delta})=\frac{1}{(2\delta\Delta)^{2}}\int_{\bar{\Delta}-\delta\Delta}^{\bar{\Delta}+\delta\Delta}{\rm d}\Delta_{1}\int_{\bar{\Delta}-\delta\Delta}^{\bar{\Delta}+\delta\Delta}{\rm d}\Delta_{2}\,\sigma_{i}^{2}(\Delta_{1},\Delta_{2}).

A full calculation of the σi2(Δ1,Δ2)\sigma^{2}_{i}(\Delta_{1},\Delta_{2}) shows that the dominant term in it drops off as 1/(Δ1Δ2)1/(\Delta_{1}-\Delta_{2}) when |Δ1Δ2|1|\Delta_{1}-\Delta_{2}|\gg 1. It follows that when δΔ1\delta\Delta\gg 1, σ^i2\hat{\sigma}^{2}_{i} is suppressed by a factor 𝒪(1/δΔ2)\mathcal{O}(1/\delta\Delta^{2}) relative to its value when δΔ=0\delta\Delta=0. Now,

δΔ(4.3×103)(ne103cm3)(L100kpc)(δλ1μm).\displaystyle\delta\Delta\approx(4.3\times 10^{3})\left(\frac{n_{\rm e}}{10^{-3}\,{\rm cm}^{-3}}\right)\left(\frac{L}{100\,{\rm kpc}}\right)\left(\frac{\delta\lambda}{1\,\mu{\rm m}}\right).

Typically for CMB radiation λ1mm1cm\lambda\sim 1\,{\rm mm}\text{--}1\,{\rm cm}, and so to achieve δΔ1\delta\Delta\lesssim 1, we would require δλ/λ<106107\delta\lambda/\lambda<10^{-6}-10^{-7} which is many orders of magnitude smaller than the typical spectral resolution of CMB experiments, δλ/λ104102\delta\lambda/\lambda\sim 10^{-4}-10^{-2}.

It is clear then that both the angular and spectral resolution of detectors would have to improve significantly before the random chameleonic contribution to the CMB polarization could be detected. The smaller regular component, however, does not suffer from such issues, although unfortunately it does not source the (more unusual) circular polarization in the CMB. In the cell model the contribution from the regular magnetic field is a factor of 1/N1/N smaller than 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}. In the power spectrum model, however, electron density fluctuations result in some enhancement of the regular magnetic field conversion probability. The regular contributions to both QQ and UU are generally dominated by the term in 𝒬0\mathcal{Q}_{0} coming from the electron density fluctuations:

𝒬0\displaystyle\mathcal{Q}_{0} \displaystyle\approx Breg2L16Meff2n¯e2IN2WN(kcrit).\displaystyle\frac{B_{\rm reg}^{2}L}{16M_{\rm eff}^{2}\bar{n}_{\rm e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit}).

Assuming that k2PN=2(2π)1/3CN2kαk^{2}P_{\rm N}=2(2\pi)^{1/3}C_{\rm N}^{2}k^{\alpha} for kLcoh1k\gtrsim L_{\rm coh}^{-1}, we found in §III.1 that for a Kolmogorov spectrum with α=5/3\alpha=-5/3,

2(2π)1/3CN2\displaystyle 2(2\pi)^{1/3}C_{\rm N}^{2} \displaystyle\approx (0.270.45)n¯e2(IN1)Lcoh2/3.\displaystyle(0.27\text{--}0.45)\bar{n}_{\rm e}^{2}(I_{\rm N}-1)L_{\rm coh}^{-2/3}.

Hence in the Kolmogorov model,

𝒬0\displaystyle\mathcal{Q}_{0} \displaystyle\sim 102IN2(IN1)Breg2LLcoh2/3Meff2kcrit5/3,\displaystyle 10^{-2}\frac{I_{\rm N}^{2}(I_{\rm N}-1)B_{\rm reg}^{2}LL_{\rm coh}^{-2/3}}{M_{\rm eff}^{2}}k_{\rm crit}^{-5/3},
\displaystyle\approx (01.5×109)g102ν2145/3B1μG2L200\displaystyle(0\text{--}1.5\times 10^{-9})g_{10}^{2}\nu_{214}^{5/3}B_{1\mu{\rm G}}^{2}L_{200}
n0.015/3(L1kpccoh)2/3,\displaystyle n_{0.01}^{-5/3}\left(L_{1\,{\rm kpc}}^{\rm coh}\right)^{-2/3},

where as before IN=12I_{\rm N}=1\text{--}2, g10=1010GeV/Meffg_{10}=10^{10}\,{\rm GeV}/M_{\rm eff}, etc. and we define B1μG=Breg/1μGB_{1\mu{\rm G}}=B_{\rm reg}/1\mu{\rm G}. For the Coma cluster with L198kpcL\approx 198\,\mathrm{kpc}, n¯e4×103cm3\bar{n}_{\rm e}\approx 4\times 10^{-3}\,{\rm cm}^{-3}, Breg0.2μGB_{\rm reg}\approx 0.2\,\mu{\rm G} and Lcoh1kpcL_{\rm coh}\approx 1\,{\rm kpc} this gives,

𝒬0Coma(02.9)×1010g102ν2145/3,\displaystyle\mathcal{Q}_{0}^{\rm Coma}\sim(0\text{--}2.9)\times 10^{-10}g_{10}^{2}\nu_{214}^{5/3},

whereas for Hydra A with L260kpcL\approx 260\,{\rm kpc}, n¯e102cm3\bar{n}_{\rm e}\approx 10^{-2}\,{\rm cm}^{-3}, Lcoh4kpcL_{\rm coh}\approx 4\,{\rm kpc} and Breg6μGB_{\rm reg}\approx 6\,\mu{\rm G} we have,

𝒬0Hydra(03.0)×109g102ν2145/3.\displaystyle\mathcal{Q}_{0}^{\rm Hydra}\sim(0\text{--}3.0)\times 10^{-9}g_{10}^{2}\nu_{214}^{5/3}.

For the chameleon-induced linear polarization to be at a similar level to the intrinsic CMB polarization one would require 𝒬0few×107\mathcal{Q}_{0}\sim{\rm few}\times 10^{-7}. For the Coma cluster this would require g1027g_{10}\gtrsim 27 corresponding to 𝒫Coma(214GHz)few×104\mathcal{P}_{\rm Coma}(214\,{\rm GHz})\sim{\rm few}\times 10^{-4}, which is strongly ruled out by our analysis of the SZ effect. However in Hydra A, where the large scale magnetic field is much stronger, one could achieve 𝒬0few×107\mathcal{Q}_{0}\sim{\rm few}\times 10^{-7} with only g102.6g_{10}\approx 2.6 which is a factor of 4 smaller than the lowest upper bound on g10g_{10} found previously from the Coma SZ measurements. It is feasible, therefore, that future searches for CMB polarization in the direction of galaxy clusters could, in some cases, reveal an enhancement of polarization at higher frequencies. However this would only be expected to occur for clusters, such as Hydra A, with suitably large regular magnetic fields, 𝒪(10μG)\mathcal{O}(10\mu{\rm G}).

VII Conclusions

The chameleon was first introduced to explain the possible scenario of a very light scalar field existing in the cosmos with a gravitational strength coupling to matter and yet not being detected on Earth as a fifth-force. The theory has since been extended to allow supergravitational strength couplings and different forms of the matter coupling. Recently, there has been interest in predicting the astrophysical implications of a direct coupling between chameleon-like fields and the photon Brax07 ; BurrageSN ; Burrage08 . This analysis applies not only to the chameleon model but also other chameleon-like theories such as the Olive–Pospelov model designed to explain a variation in the fine-structure constant, αem\alpha_{\rm em}.

In this paper we have specifically considered the effect of a chameleon-like scalar field on the CMB intensity and polarization in the direction of galaxy clusters. The chameleon mixes with CMB photons in the magnetic field of the intracluster medium. The resulting modification to the CMB intensity could be observed as a correction to the existing Sunyaev–Zel’dovich effect. Measurements of the CMB polarization in the direction of clusters are still waiting to be made, but the chameleon effect could potentially be significant in the polarization foregrounds as well.

Predictions of the chameleon effect are strongly dependent on the assumed structure of the intracluster magnetic field. In this work we have considered two different models for the magnetic structure: a simplistic cell model in which the cluster properties are uniform but the magnetic field has a random orientation in each of the NN cells along the light path; and a potentially more realisistic power spectrum model in which fluctuations in the magnetic field and electron density are allowed over a range of length scales, with the small-scale power spectra taken to correspond to three-dimensional Kolmogorov turbulence.

The conversion probability, 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}, in the cell model for magnetic fluctuations is given by,

𝒫(cell)(L,ν)\displaystyle\mathcal{P}^{(\rm cell)}(L,\nu) =\displaystyle= (3.2×1010)g102B10μG2n0.012\displaystyle\left(3.2\times 10^{-10}\right)g_{10}^{2}B_{10\mu{\rm G}}^{2}n_{0.01}^{-2}
L200(L1kpccoh)1ν2142,\displaystyle L_{200}(L^{\rm coh}_{1\,{\rm kpc}})^{-1}\nu_{214}^{2},

while in the Kolmogorov turbulence model it is predicted to be slightly larger with

𝒫(Kolmo)(L,ν)=(2.43.8×107)g102B10μG2n0.015/3\displaystyle\mathcal{P}^{(\rm Kolmo)}(L,\nu)=\left(2.4\text{--}3.8\times 10^{-7}\right)g_{10}^{2}B_{10\mu{\rm G}}^{2}n_{0.01}^{-5/3}
ν2145/3L200(L1kpccoh)2/3(IN2(2IN1)12).\displaystyle\nu_{214}^{5/3}L_{200}\left(L^{\rm coh}_{1\,{\rm kpc}}\right)^{-2/3}\left(\frac{I_{\rm N}^{2}(2I_{\rm N}-1)}{12}\right).

The resulting change to the CMB intensity contributing to the SZ effect is given by,

ΔICSZI0=𝒫¯γϕ(L).\displaystyle\frac{\Delta I_{\rm CSZ}}{I_{0}}=-\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}(L).

The strong dependence of the conversion probability on frequency allows us to compare measurements of the SZ effect across a range of frequencies, with our predicitions for the combined thermal SZ and chameleonic SZ effects. A maximum likelihood analysis of the SZ observations of the nearby Coma cluster leads to a constraint on the chameleon-photon conversion probability:

𝒫Coma(204GHz)<6.2×105(95%CL).\displaystyle{\mathcal{P}}_{\rm Coma}(204\,{\rm GHz})<6.2\times 10^{-5}\quad(95\%{\rm CL}).

This can be converted into a constraint on the chameleon-photon coupling strength. However this is strongly dependent on the magnetic fluctuation model assumed and also on the properties of the Coma cluster. Assuming the current available data on the Coma cluster properties Feretti95 we find,

geff(cell)<2.2×108GeV1g_{\rm eff}^{\rm(cell)}<2.2\times 10^{-8}\,{\rm GeV}^{-1}

using the cell model, and

geff(Kolmo)<(7.232.5)×1010GeV1,g_{\rm eff}^{\rm(Kolmo)}<(7.2\text{--}32.5)\times 10^{-10}\,{\rm GeV}^{-1},

assuming a Kolmogorov turbulence model. We note that other clusters such as Hydra A, a good example of a cooling-core cluster, have approximately similar conversion probabilities, since although the observed magnetic field strength at the centre of the cluster is much greater (enhances chameleon effect) the electron density is also much higher (supresses chameleon effect).

The model dependence of the effective coupling strength leads us to reevaluate the constraints given in Ref. Burrage08 . Assuming a cell model for the magnetic field fluctuations the constraint on the coupling strength from starlight polarization was found to be geff<9.1×1010GeV1g_{\rm eff}<9.1\times 10^{-10}{\rm GeV}^{-1}. From our analysis we have found that the conversion probability increases by a factor of (Δ¯/N)1/3\left(\bar{\Delta}/N\right)^{1/3} if a Kolmogorov turbulence model is assumed instead. This increases the sensitivity to geffg_{\rm eff} by approximately (Δ¯/N)1/6\left(\bar{\Delta}/N\right)^{1/6}. In our galaxy, Δ¯/N50100\bar{\Delta}/N\sim 50\text{--}100, for the objects considered in Ref. Burrage08 . Thus we expect to increase the constraint to approximately geff<4×1010GeV1g_{\rm eff}<4\times 10^{-10}{\rm GeV}^{-1} if a Kolmogorov turbulence model is used in the analysis of the starlight polarization data. We note that the current constraints coming from starlight polarization are tighter than those from SZ measurements. However for the starlight polarization the data is predominantly limited by intrinsic scatter and improvements are likely to be statistical, while there is the possibility of SZ observations away from the cluster core leading to even better SZ constraints (see below). It should be mentioned, however, that there is significant uncertainty in the SZ constraints coming from a lack of detailed knowledge about cluster magnetic fields on scales kcrit1\sim k_{\rm crit}^{-1}, whereas the starlight polarization analysis rests on knowledge of the power spectrum of the galaxy magnetic field and electron density fluctuations which are much better known.

In addition to the frequency dependence of the chameleon effect, it is possible to exploit the dependence on magnetic field strength and electron density to examine the radial dependence within the galaxy cluster. The magnetic field and electron density are expected to decrease with radius. We have assumed a simple scaling for the electron density following a β\beta-profile, ne=n0(1+r2rc2)3β/2n_{e}=n_{0}\left(1+\frac{r^{2}}{r_{\rm c}^{2}}\right)^{-3\beta/2}, with BneηB\propto n_{e}^{\eta}. In Fig. 4 we plotted both the thermal SZ radial profile and the predicted chameleonic radial profile for a hypothetical cluster with chameleon-photon conversion probability 𝒫γϕ(204GHz)=3×105\mathcal{P}_{\gamma\leftrightarrow\phi}(204\,{\rm GHz})=3\times 10^{-5} through the centre of the cluster. We found that the chameleonic effect generally dominates towards the edges of the cluster. The suggestion of a discrepancy between the inferred SZ effect from X-ray emission data and the WMAP SZ measurements ROSATvsWMAP could potentially be attributed to a chameleon, and this requires further investigation. In any case, future measurements of the SZ profile at higher frequencies would lead to even better constraints on the chameleon model.

Finally we looked at the modification to the CMB polarization. We found that the contribution to the modification from chameleon-photon mixing arising from the random component of the intra-cluster magnetic field, i.e. that tangled on scales much smaller than the size of the cluster, is severly limited by the angular and spectral resolution of the detector. We would require angular resolution on the scale of the magnetic domains in the cluster, approximately one-hundredth the size of the cluster, and frequency resolution of the order δλ/λ106\delta\lambda/\lambda\leq 10^{-6} before any effect could be detected in the CMB polarization. The contribution arising from the regular component of the magnetic field is more significant and potentially detectable. So far polarization measurements of the CMB in the direction of galaxy clusters have not been made. The upcoming SPT-pol experiment SPTelescope will change this. Assuming a Kolomogorov turbulence model, we predict the change to the fractional CMB linear polarization:

ΔQΔU\displaystyle\Delta Q\approx\Delta U \displaystyle\approx (01.5×109)g102ν2145/3B1μG2L200\displaystyle(0\text{--}1.5\times 10^{-9})g_{10}^{2}\nu_{214}^{5/3}B_{1\mu{\rm G}}^{2}L_{200}
n0.015/3(L1kpccoh)2/3,\displaystyle n_{0.01}^{-5/3}\left(L_{1\,{\rm kpc}}^{\rm coh}\right)^{-2/3},

which for some clusters is approaching the level of the intrinsic CMB polarisation.

We conclude by mentioning two points which at first may appear to be potential sources of error in our predictions. Firstly we remind the reader that the magnetic field strengths of most galaxy clusters are determined from Faraday rotation measures, looking at the degree to which the polarization plane of some background source is rotated due to the presence of the cluster magnetic field. It is feasible that the presence of a chameleon could influence the change to the polarisation angle and hence the inferred magnetic field strength of these clusters. However the Faraday RMs generally come from low frequency measurements around 10GHz10\,\mathrm{GHz} for which the chameleon interaction is greatly suppressed. Therefore we believe it is realistic to ignore the contamination when considering the cluster magnetic field strength.

Secondly, in these predictions we have neglected the contribution from our own galactic magnetic field. In Burrage08 the bound on the chameleon-photon conversion probability in our own galaxy coming from starlight polarization was found to be 𝒫¯γϕfew×106\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}\lesssim\text{few}\,\times 10^{-6} at ω=1eV\omega=1\,{\rm eV}. Assuming the probability scales as ω5/3\omega^{5/3}, then the contribution at CMB frequencies from the galactic magnetic field would be less than 𝒪(1010)\mathcal{O}(10^{-10}), which is negligble.


Acknowledgements: ACD, CAOS and DJS are supported by STFC. We are grateful to Clare Burrage, Anthony Challinor, Keith Grainge, Hiranya Peiris and Paul Shellard for extremely helpful conversations.

Appendix A Photon-Scalar Mixing

In the weak mixing limit, we saw in §II that the photon-scalar mixing can be described by a function Ai(z)A_{i}(z) where i={x,y}i=\left\{x,y\right\}, and

Ai(z)=0zdxBi(x)2Meffe2iΔ(x).\displaystyle A_{i}(z)=\int_{0}^{z}{\rm d}x\frac{B_{i}(x)}{2M_{\rm eff}}e^{2i\Delta(x)}. (54)

We assume that 𝐁\mathbf{B} has both a regular component, 𝐁reg\mathbf{B}_{\rm reg}, which we take to be constant, and a random component, δ𝐁\delta\mathbf{B}. We also found in §II that the probability of a photon converting into a scalar field, 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi}, and the induced contributions, 𝒬q\mathcal{Q}_{\rm q}, 𝒬u\mathcal{Q}_{\rm u} and 𝒬v\mathcal{Q}_{\rm v} to the Stokes parameters QQ, UU and VV, are given in terms of the AiA_{i} thus:

𝒫γϕ(z)\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}(z) =\displaystyle= 12(|Ax(z)|2+|Ay(z)|2),\displaystyle\frac{1}{2}\left(|A_{x}(z)|^{2}+|A_{y}(z)|^{2}\right),
𝒬q(z)\displaystyle\mathcal{Q}_{\rm q}(z) =\displaystyle= 12(|Ax(z)|2|Ay(z)|2),\displaystyle\frac{1}{2}\left(|A_{x}(z)|^{2}-|A_{y}(z)|^{2}\right),
𝒬u(z)\displaystyle\mathcal{Q}_{\rm u}(z) =\displaystyle= Re(Ax(z)Ay(z)),\displaystyle{\rm Re}(A_{x}^{\ast}(z)A_{y}(z)),
𝒬v(z)\displaystyle\mathcal{Q}_{\rm v}(z) =\displaystyle= Im(Ax(z)Ay(z)).\displaystyle{\rm Im}(A_{x}^{\ast}(z)A_{y}(z)).

We now evaluate these quantities in the cell and power spectrum models for the magnetic field fluctuations when z=Lz=L, where LL is the path length through the magnetic region.

A.1 The Cell Model

In the cell model for the magnetic field we assume that along the light path, 0<z<L0<z<L, the components of the random magnetic field δ𝐁\delta\mathbf{B} perpendicular to the line of sight are given by

(δ𝐁)x=Brandcosθn,\displaystyle(\delta\mathbf{B})_{x}=B_{\rm rand}\cos\theta_{n},
(δ𝐁)y=Brandsinθn,\displaystyle(\delta\mathbf{B})_{y}=B_{\rm rand}\sin\theta_{n},

in the region (n1)Lcoh<z<nLcoh(n-1)L_{\rm coh}<z<nL_{\rm coh}, where LcohL_{\rm coh} is the coherence length and θnU(0,2π]\theta_{n}\sim U(0,2\pi]. We define N=L/LcohN=L/L_{\rm coh} with nn running from 1 to NN. We take BrandB_{\rm rand} to be fixed and assume a constant value of ne=n¯en_{\rm e}=\bar{n}_{\rm e}. Thus Δ(x)=Δ¯x/L\Delta(x)=\bar{\Delta}x/L, where

Δ¯m¯eff2L4ω,\displaystyle\bar{\Delta}\equiv\frac{\bar{m}_{\rm eff}^{2}L}{4\omega},

and m¯eff2ωpl2=(4παemn¯e/me)2\bar{m}_{\rm eff}^{2}\simeq-\omega_{\rm pl}^{2}=-(4\pi\alpha_{\rm em}\bar{n}_{e}/m_{\rm e})^{2} in the cluster atmosphere. It is now straightforward to evaluate AiA_{i} and we find,

Ai(L)\displaystyle A_{i}(L) =\displaystyle= (𝐀reg)i+(δ𝐀)i,\displaystyle(\mathbf{A}_{\rm reg})_{i}+(\delta\mathbf{A})_{i},
𝐀reg\displaystyle\mathbf{A}_{\rm reg} =\displaystyle= 2𝐁regωeiΔ¯Meffmeff2sinΔ¯,\displaystyle\frac{2\mathbf{B}_{\rm reg}\omega e^{i\bar{\Delta}}}{M_{\rm eff}m_{\rm eff}^{2}}\sin\bar{\Delta},
δ𝐀\displaystyle\delta\mathbf{A} =\displaystyle= 2BrandωeiΔ¯NMeffmeff2sin(Δ¯N)r=0N1𝐧^(r)e2iΔ¯rN,\displaystyle\frac{2B_{\rm rand}\omega e^{\frac{i\bar{\Delta}}{N}}}{M_{\rm eff}m_{\rm eff}^{2}}\sin\left(\frac{\bar{\Delta}}{N}\right)\sum_{r=0}^{N-1}\hat{\mathbf{n}}^{(r)}e^{\frac{2i\bar{\Delta}r}{N}},

where 𝐧^(n)=(cosθn,sinθn,0)T\hat{\mathbf{n}}^{(n)}=(\cos\theta_{n},\sin\theta_{n},0)^{\rm T}. Taking (𝐁reg)x=Bregcosθreg(\mathbf{B}_{\rm reg})_{x}=B_{\rm reg}\cos\theta_{\rm reg} and (𝐁reg)y=Bregsinθreg(\mathbf{B}_{\rm reg})_{y}=B_{\rm reg}\sin\theta_{\rm reg}, we find

𝒫γϕ(L)=𝒫reg+𝒫cross+𝒫rand,\displaystyle\mathcal{P}_{\gamma\leftrightarrow\phi}(L)=\mathcal{P}^{\rm reg}+\mathcal{P}^{\rm cross}+\mathcal{P}^{\rm rand},
𝒬i(L)=𝒬ireg+𝒬icross+𝒬irand,\displaystyle\mathcal{Q}_{i}(L)=\mathcal{Q}^{\rm reg}_{i}+\mathcal{Q}^{\rm cross}_{i}+\mathcal{Q}^{\rm rand}_{i},

where the regular components are given by:

𝒫reg\displaystyle\mathcal{P}^{\rm reg} =\displaystyle= 12(2BregωMeffmeff2)2sin2Δ¯,\displaystyle\frac{1}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},
𝒬qreg\displaystyle\mathcal{Q}^{\rm reg}_{\rm q} =\displaystyle= cos2θreg2(2BregωMeffmeff2)2sin2Δ¯,\displaystyle\frac{\cos 2\theta_{\rm reg}}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},
𝒬ureg\displaystyle\mathcal{Q}^{\rm reg}_{\rm u} =\displaystyle= sin2θreg2(2BregωMeffmeff2)2sin2Δ¯,\displaystyle\frac{\sin 2\theta_{\rm reg}}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta},
𝒬vreg\displaystyle\mathcal{Q}^{\rm reg}_{\rm v} =\displaystyle= 0.\displaystyle 0.

Similarly the cross-terms are given by:

𝒫cross\displaystyle\mathcal{P}^{\rm cross} =\displaystyle= (2ωMeffmeff2)2BregBrandsinΔ¯sin(Δ¯N)\displaystyle\left(\frac{2\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}B_{\rm reg}B_{\rm rand}\sin\bar{\Delta}\sin\left(\frac{\bar{\Delta}}{N}\right)
r=0N1cos(θrθreg)cos(Δ¯N(2r+1N)),\displaystyle\sum_{r=0}^{N-1}\cos(\theta_{r}-\theta_{\rm reg})\cos\left(\frac{\bar{\Delta}}{N}(2r+1-N)\right),
𝒬qcross\displaystyle\mathcal{Q}^{\rm cross}_{\rm q} =\displaystyle= (2ωMeffmeff2)2BregBrandsinΔ¯sin(Δ¯N)\displaystyle\left(\frac{2\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}B_{\rm reg}B_{\rm rand}\sin\bar{\Delta}\sin\left(\frac{\bar{\Delta}}{N}\right)
r=0N1cos(θr+θreg)cos(Δ¯N(2r+1N)),\displaystyle\sum_{r=0}^{N-1}\cos(\theta_{r}+\theta_{\rm reg})\cos\left(\frac{\bar{\Delta}}{N}(2r+1-N)\right),
𝒬ucross\displaystyle\mathcal{Q}^{\rm cross}_{\rm u} =\displaystyle= (2ωMeffmeff2)2BregBrandsinΔ¯sin(Δ¯N)\displaystyle\left(\frac{2\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}B_{\rm reg}B_{\rm rand}\sin\bar{\Delta}\sin\left(\frac{\bar{\Delta}}{N}\right)
r=0N1sin(θr+θreg)cos(Δ¯N(2r+1N)),\displaystyle\sum_{r=0}^{N-1}\sin(\theta_{r}+\theta_{\rm reg})\cos\left(\frac{\bar{\Delta}}{N}(2r+1-N)\right),
𝒬vcross\displaystyle\mathcal{Q}^{\rm cross}_{\rm v} =\displaystyle= (2ωMeffmeff2)2BregBrandsinΔ¯sin(Δ¯N)\displaystyle\left(\frac{2\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}B_{\rm reg}B_{\rm rand}\sin\bar{\Delta}\sin\left(\frac{\bar{\Delta}}{N}\right)
r=0N1sin(θrθreg)sin(Δ¯N(2r+1N)).\displaystyle\sum_{r=0}^{N-1}\sin(\theta_{r}-\theta_{\rm reg})\sin\left(\frac{\bar{\Delta}}{N}(2r+1-N)\right).

Finally the terms due entirely to the random component of the magnetic field are:

𝒫rand\displaystyle\mathcal{P}^{\rm rand} =\displaystyle= 12(2BrandωMeffmeff2)2sin2(Δ¯N)\displaystyle\frac{1}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right)
s=0N1r=0N1cos(θrθs)cos(2Δ¯N(rs)),\displaystyle\sum_{s=0}^{N-1}\sum_{r=0}^{N-1}\cos(\theta_{r}-\theta_{s})\cos\left(\frac{2\bar{\Delta}}{N}(r-s)\right),
𝒬qrand\displaystyle\mathcal{Q}^{\rm rand}_{\rm q} =\displaystyle= 12(2BrandωMeffmeff2)2sin2(Δ¯N)\displaystyle\frac{1}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right)
s=0N1r=0N1cos(θr+θs)cos(2Δ¯N(rs)),\displaystyle\sum_{s=0}^{N-1}\sum_{r=0}^{N-1}\cos(\theta_{r}+\theta_{s})\cos\left(\frac{2\bar{\Delta}}{N}(r-s)\right),
𝒬urand\displaystyle\mathcal{Q}^{\rm rand}_{\rm u} =\displaystyle= 12(2BrandωMeffmeff2)2sin2(Δ¯N)\displaystyle\frac{1}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right)
s=0N1r=0N1sin(θr+θs)cos(2Δ¯N(rs)),\displaystyle\sum_{s=0}^{N-1}\sum_{r=0}^{N-1}\sin(\theta_{r}+\theta_{s})\cos\left(\frac{2\bar{\Delta}}{N}(r-s)\right),
𝒬vrand\displaystyle\mathcal{Q}^{\rm rand}_{\rm v} =\displaystyle= 12(2BrandωMeffmeff2)2sin2(Δ¯N)\displaystyle\frac{1}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right)
s=0N1r=0N1sin(θrθs)sin(2Δ¯N(rs)).\displaystyle\sum_{s=0}^{N-1}\sum_{r=0}^{N-1}\sin(\theta_{r}-\theta_{s})\sin\left(\frac{2\bar{\Delta}}{N}(r-s)\right).

Taking an average over many lines of sight through the cluster is equivalent to averaging over the θn\theta_{n}. Doing this it is straightforward to check that the average values of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} are given by,

𝒫¯γϕ𝒫γϕ\displaystyle\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}\equiv\left\langle\mathcal{P}_{\gamma\leftrightarrow\phi}\right\rangle =\displaystyle= 12(2BregωMeffmeff2)2sin2Δ¯\displaystyle\frac{1}{2}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\bar{\Delta}
+N2(2BrandωMeffmeff2)2sin2(Δ¯N),\displaystyle+\frac{N}{2}\left(\frac{2B_{\rm rand}\omega}{M_{\rm eff}m_{\rm eff}^{2}}\right)^{2}\sin^{2}\left(\frac{\bar{\Delta}}{N}\right),
𝒬¯i𝒬i\displaystyle\bar{\mathcal{Q}}_{i}\equiv\left\langle\mathcal{Q}_{i}\right\rangle =\displaystyle= 𝒬ireg.\displaystyle\mathcal{Q}^{\rm reg}_{i}.

We can also calculate the variance of the 𝒬i\mathcal{Q}_{i} over many lines of sight. Assuming |Δ¯|/N1|\bar{\Delta}|/N\gg 1, N1N\gg 1 and remembering Brand𝒪(Breg)B_{\rm rand}\sim\mathcal{O}(B_{\rm reg}), we find

σi2\displaystyle\sigma_{i}^{2} =\displaystyle= 𝒬i2𝒬¯i212𝒫¯γϕ2.\displaystyle\left\langle\mathcal{Q}_{i}^{2}\right\rangle-\bar{\mathcal{Q}}_{i}^{2}\approx\frac{1}{2}\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}\,.

This assumes that measurements of the Stokes parameters, and hence the 𝒬i\mathcal{Q}_{i}, are exactly monochromatic. The observable σi2\sigma_{i}^{2} can be greatly suppressed relative to the above estimate when, as is always the case in practice, measurements actually comprise an average of the observable quantity over a frequency band about the desired measurement frequency. We discuss this further in §A.3 below.

A.2 The Power Spectrum Model

In the power spectrum model, we assume that fluctuations in 𝐁\mathbf{B} occur on all spatial scales, and we describe the magnitude of the fluctuations on different scales by a power spectrum, PB(k)P_{\rm B}(k). We also allow fluctuations in the electron number density, nen_{\rm e}, which are described by another power spectrum, PN(k)P_{\rm N}(k). We define ne(z)=n¯e(1+δn(z))n_{\rm e}(z)=\bar{n}_{\rm e}(1+\delta_{\rm n}(z)), where n¯e\bar{n}_{e} is the average electron density along the path through the magnetic region. We also define,

δ¯n(z)=1z0zδn(x)dx.\bar{\delta}_{\rm n}(z)=\frac{1}{z}\int_{0}^{z}\delta_{\rm n}(x){\rm d}x\,.

Note δ¯n(L)=0\bar{\delta}_{\rm n}(L)=0. With AiA_{i} defined by Eq. (54), we define Z=(1+δ¯n(z))zZ=(1+\bar{\delta}_{\rm n}(z))z and Δ¯=m¯eff2L/4ωn¯eL/4ω\bar{\Delta}=\bar{m}_{\rm eff}^{2}L/4\omega\propto-\bar{n}_{\rm e}L/4\omega. It follows that Δ(z)=Δ¯Z/L\Delta(z)=\bar{\Delta}Z/L. We assume that |δ¯n(z)|1|\bar{\delta}_{\rm n}(z)|\ll 1 along the majority of the path, and so Bi(z)Bi(Z)B_{i}(z)\approx B_{i}(Z). We then have,

Ai(Δ¯)0LdZBi(Z𝐳^)2Meff(1+δn(Z𝐳^))e2iΔ¯ZL.\displaystyle A_{i}(\bar{\Delta})\approx\int_{0}^{L}{\rm d}Z\,\frac{B_{i}(Z\hat{\mathbf{z}})}{2M_{\rm eff}(1+\delta_{\rm n}(Z\hat{\mathbf{z}}))}e^{\frac{2i\bar{\Delta}Z}{L}}.

To calculate the expected values of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i}, we must calculate the correlation at different frequencies:

𝒜ij(Δ¯1,Δ¯2)Ai(Δ¯1)Aj(Δ¯2)\displaystyle\mathcal{A}_{ij}(\bar{\Delta}_{1},\bar{\Delta}_{2})\equiv\left\langle A_{i}(\bar{\Delta}_{1})A_{j}^{\ast}(\bar{\Delta}_{2})\right\rangle
=14Meff20Ldx0LdyRijtot((xy)𝐳^)e2i(Δ¯1xΔ¯2y)/L\displaystyle=\frac{1}{4M_{\rm eff}^{2}}\int_{0}^{L}{\rm d}x\int_{0}^{L}{\rm d}yR_{ij}^{\rm tot}((x-y)\hat{\mathbf{z}})e^{2i(\bar{\Delta}_{1}x-\bar{\Delta}_{2}y)/L} ,

where the correlation function is defined,

Rijtot(x𝐳^)Bi(y𝐳^)Bj((y+x)𝐳^)(1+δn(y𝐳^)(1+δn((y+x)𝐳^).R_{ij}^{\rm tot}(x\hat{\mathbf{z}})\equiv\left\langle\frac{B_{i}(y\hat{\mathbf{z}})B_{j}((y+x)\hat{\mathbf{z}})}{(1+\delta_{\rm n}(y\hat{\mathbf{z}})(1+\delta_{\rm n}((y+x)\hat{\mathbf{z}})}\right\rangle.

We split the magnetic field into a regular and turbulent component: 𝐁=𝐁reg+δ𝐁\mathbf{B}=\mathbf{B}_{\rm reg}+\delta\mathbf{B}. Assuming isotropy of the fluctuations in 𝐁\mathbf{B} and nen_{\rm e}, we rewrite RijtotR_{ij}^{\rm tot} thus,

Rijtot(x𝐳^)\displaystyle R_{ij}^{\rm tot}(x\hat{\mathbf{z}}) =\displaystyle= BiregBjreg\displaystyle B^{\rm reg}_{i}B^{\rm reg}_{j}
(1+δn(y𝐳^))1(1+δn((y+x)𝐳^))1\displaystyle\cdot\left\langle(1+\delta_{\rm n}(y\hat{\mathbf{z}}))^{-1}(1+\delta_{\rm n}((y+x)\hat{\mathbf{z}}))^{-1}\right\rangle
+δij3δ𝐁(y𝐳^)δ𝐁((y+x)𝐳^)(1+δn(y𝐳^)(1+δn((y+x)𝐳^)).\displaystyle+\frac{\delta_{ij}}{3}\left\langle\frac{\delta\mathbf{B}(y\hat{\mathbf{z}})\cdot\delta\mathbf{B}((y+x)\hat{\mathbf{z}})}{(1+\delta_{\rm n}(y\hat{\mathbf{z}})(1+\delta_{\rm n}((y+x)\hat{\mathbf{z}}))}\right\rangle.

We note that isotropy of the magnetic fluctuations implies that the off-diagonal components of RijtotR_{ij}^{\rm tot} are sourced only by the regular magnetic field. We define a combined power spectrum Pijtot(k)P^{\rm tot}_{ij}(k) by,

Rijtot(x𝐳^)\displaystyle R_{ij}^{\rm tot}(x\hat{\mathbf{z}}) =\displaystyle= 14πd3kPijtot(k)e2πix𝐤𝐳^.\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}k\,P_{ij}^{\rm tot}(k)e^{2\pi ix\mathbf{k}\cdot\hat{\mathbf{z}}}.

We then have,

𝒜ij=L24Meff2ei(Δ¯1Δ¯2)0k2Pijtot(k)K(πkL;Δ¯1,Δ¯2)dk,\displaystyle\mathcal{A}_{ij}=\frac{L^{2}}{4M_{\rm eff}^{2}}e^{i(\bar{\Delta}_{1}-\bar{\Delta}_{2})}\int_{0}^{\infty}k^{2}P_{ij}^{\rm tot}(k)K(\pi kL;\bar{\Delta}_{1},\bar{\Delta}_{2}){\rm d}k,

where,

K(πkL;Δ¯1,Δ¯2)=01ds\displaystyle K(\pi kL;\bar{\Delta}_{1},\bar{\Delta}_{2})=\int_{0}^{1}{\rm d}s sin(2πkLs)2πkLssin(2Δ¯(1s))Δ¯\displaystyle\frac{\sin(2\pi kLs)}{2\pi kLs}\frac{\sin(2\bar{\Delta}_{-}(1-s))}{\bar{\Delta}_{-}}
cos(2Δ¯+s),\displaystyle\cdot\cos(2\bar{\Delta}_{+}s),

and we have defined 2Δ¯±Δ¯2±Δ¯12\bar{\Delta}_{\pm}\equiv\bar{\Delta}_{2}\pm\bar{\Delta}_{1}. This integral may be evaluated explicitly in terms of the functions:

Cin(x)\displaystyle{\rm Cin}(x) =\displaystyle= 0xsin2(y/2)y/2dy,\displaystyle\int_{0}^{x}\frac{\sin^{2}(y/2)}{y/2}{\rm d}y,
Si(x)\displaystyle{\rm Si}(x) =\displaystyle= 0xsinyydy.\displaystyle\int_{0}^{x}\frac{\sin y}{y}{\rm d}y.

We define δCin(x,y)=Cin(x+y)Cin(xy)\delta{\rm Cin}(x,y)={\rm Cin}(x+y)-{\rm Cin}(x-y) and δSi(x,y)=Si(x+y)Si(xy)\delta{\rm Si}(x,y)={\rm Si}(x+y)-{\rm Si}(x-y). We then have,

4xK(x;Δ¯1,Δ¯2)\displaystyle 4xK(x;\bar{\Delta}_{1},\bar{\Delta}_{2}) =\displaystyle= cos2Δ¯2Δ¯[δCin(2Δ¯1,2x)\displaystyle\frac{\cos 2\bar{\Delta}_{-}}{2\bar{\Delta}_{-}}\left[\delta{\rm Cin}(2\bar{\Delta}_{1},2x)\right.
δCin(2Δ¯2,2x)]\displaystyle\left.-\delta{\rm Cin}(2\bar{\Delta}_{2},2x)\right]
+sin2Δ¯2Δ¯[δSi(2Δ¯1,2x)\displaystyle+\frac{\sin 2\bar{\Delta}_{-}}{2\bar{\Delta}_{-}}\left[\delta{\rm Si}(2\bar{\Delta}_{1},2x)\right.
+δSi(2Δ¯2,2x)].\displaystyle\left.+\delta{\rm Si}(2\bar{\Delta}_{2},2x)\right].

We are concerned with CMB radiation, for which ω105103eV\omega\sim 10^{-5}\text{--}10^{-3}\,{\rm eV}, propagating over distances of the order of 100kpc100\,{\rm kpc} through clusters. It is easy to see that for such a scenario |Δ¯|1|\bar{\Delta}|\gg 1. We evaluate K(x;Δ¯1,Δ¯2)K(x;\bar{\Delta}_{1},\bar{\Delta}_{2}) in the asymptotic limit where |Δ¯1|,|Δ¯2|1|\bar{\Delta}_{1}|,|\bar{\Delta}_{2}|\gg 1. When min(|Δ¯1|,|Δ¯2|)1\min(|\bar{\Delta}_{1}|,|\bar{\Delta}_{2}|)\gg 1 and xmin(|Δ¯1|,|Δ¯2|)x\ll\min(|\bar{\Delta}_{1}|,|\bar{\Delta}_{2}|) we have,

4xK(x;Δ¯1,Δ¯2)\displaystyle 4xK(x;\bar{\Delta}_{1},\bar{\Delta}_{2}) \displaystyle\simeq 2xcos2Δ¯Δ¯1Δ¯2\displaystyle\frac{2x\cos 2\bar{\Delta}_{-}}{\bar{\Delta}_{1}\bar{\Delta}_{2}}
sin2xcos2Δ¯+Δ¯1Δ¯2,\displaystyle-\frac{\sin 2x\cos 2\bar{\Delta}_{+}}{\bar{\Delta}_{1}\bar{\Delta}_{2}},

and when xmin(|Δ¯1|,|Δ¯2|)x\gg\min(|\bar{\Delta}_{1}|,|\bar{\Delta}_{2}|), we have

4xK(x;Δ¯1,Δ¯2)\displaystyle 4xK(x;\bar{\Delta}_{1},\bar{\Delta}_{2}) \displaystyle\simeq 2πsin2Δ¯2Δ¯2cos2Δ¯x.\displaystyle\frac{2\pi\sin 2\bar{\Delta}_{-}}{2\bar{\Delta}_{-}}-\frac{2\cos 2\bar{\Delta}_{-}}{x}.

We define ki=|Δ¯i|/πLk_{i}=|\bar{\Delta}_{i}|/\pi L. We assume that the fluctuations in 𝐁\mathbf{B} and nen_{\rm e} are such that Pijtot(k)P^{\rm tot}_{ij}(k) drops off faster than k3k^{-3} for all k>kk>k_{\ast} where kmin(ki)k_{\ast}\ll\min(k_{i}). This is equivalent to assuming that the dominant contribution to Rijtot(0)R^{\rm tot}_{ij}(0) comes from spatial scales than are much larger than ki1k_{i}^{-1}. We expect that this dominant contribution will come from scales of the order of the coherence lengths of the magnetic field and electron density fluctuations (LBL_{\rm B} and LNL_{\rm N} respectively) and so we are assuming that ki1LB,LNk_{i}^{-1}\ll L_{\rm B},\,L_{\rm N}. With this assumption, in the limit of large |Δ¯i||\bar{\Delta}_{i}|, we have to leading order,

e2iΔ¯4Meff2𝒜ij\displaystyle e^{2i\bar{\Delta}_{-}}4M_{\rm eff}^{2}\mathcal{A}_{ij} \displaystyle\simeq L2cos2Δ¯2Δ¯1Δ¯20k2Pijtot(k)dk\displaystyle\frac{L^{2}\cos 2\bar{\Delta}_{-}}{2\bar{\Delta}_{1}\bar{\Delta}_{2}}\int_{0}^{\infty}k^{2}P_{ij}^{\rm tot}(k){\rm d}k
Lcos2Δ¯+4πΔ¯1Δ¯20ksin(2πkL)Pijtot(k)dk\displaystyle-\frac{L\cos 2\bar{\Delta}_{+}}{4\pi\bar{\Delta}_{1}\bar{\Delta}_{2}}\int_{0}^{\infty}k\sin(2\pi kL)P_{ij}^{\rm tot}(k){\rm d}k
+Lsin2Δ¯8Δ¯[k1kPijtot(k)dk\displaystyle+\frac{L\sin 2\bar{\Delta}_{-}}{8\bar{\Delta}_{-}}\left[\int_{k_{1}}^{\infty}kP_{ij}^{\rm tot}(k){\rm d}k\right.
+k2kPijtot(k)dk].\displaystyle+\left.\int_{k_{2}}^{\infty}kP_{ij}^{\rm tot}(k){\rm d}k\right].

We define,

Wij(k)=kqPijtot(q)dq,W_{ij}(k)=\int_{k}^{\infty}qP_{ij}^{\rm tot}(q){\rm d}q,

and we can then rewrite 𝒜ij\mathcal{A}_{ij} as,

e2iΔ¯𝒜ij\displaystyle e^{2i\bar{\Delta}_{-}}\mathcal{A}_{ij} \displaystyle\simeq 4ω1ω22Meff2m¯eff4Rijtot(0)cos2Δ¯\displaystyle\frac{4\omega_{1}\omega_{2}}{2M_{\rm eff}^{2}\bar{m}_{\rm eff}^{4}}R_{ij}^{\rm tot}(0)\cos 2\bar{\Delta}_{-}
4ω1ω22Meff2m¯eff4Rijtot(L𝐳^)cos2Δ¯+\displaystyle-\frac{4\omega_{1}\omega_{2}}{2M_{\rm eff}^{2}\bar{m}_{\rm eff}^{4}}R_{ij}^{\rm tot}(L\hat{\mathbf{z}})\cos 2\bar{\Delta}_{+}
+Lsin2Δ¯32Meff2Δ¯[Wij(k1)+Wij(k2)].\displaystyle+\frac{L\sin 2\bar{\Delta}_{-}}{32M_{\rm eff}^{2}\bar{\Delta}_{-}}\left[W_{ij}(k_{1})+W_{ij}(k_{2})\right].

For simplicity, we assume that fluctuations in the magnetic field and electron density are uncorrelated. Thus

δ𝐁(𝐲)δ𝐁(𝐲+𝐱)(1+δn(𝐲))(1+δn(𝐱+𝐲))=δ𝐁(𝐲)δ𝐁(𝐲+𝐱)\displaystyle\left\langle\frac{\delta\mathbf{B}(\mathbf{y})\cdot\delta\mathbf{B}(\mathbf{y}+\mathbf{x})}{(1+\delta_{\rm n}(\mathbf{y}))(1+\delta_{\rm n}(\mathbf{x}+\mathbf{y}))}\right\rangle=\left\langle\delta\mathbf{B}(\mathbf{y})\cdot\delta\mathbf{B}(\mathbf{y}+\mathbf{x})\right\rangle
(1+δn(𝐲))1(1+δn(𝐲+𝐱))1.\displaystyle\cdot\left\langle(1+\delta_{\rm n}(\mathbf{y}))^{-1}(1+\delta_{\rm n}(\mathbf{y}+\mathbf{x}))^{-1}\right\rangle.

This implies that,

Rijtot(0)(BiregBjreg+13δijδ𝐁2)n¯e2ne2.\displaystyle R_{ij}^{\rm tot}(0)\approx\left(B_{i}^{\rm reg}B_{j}^{\rm reg}+\frac{1}{3}\delta_{ij}\left\langle\delta\mathbf{B}^{2}\right\rangle\right)\left\langle\frac{\bar{n}_{\rm e}^{2}}{n_{\rm e}^{2}}\right\rangle.

We assume that fluctuations in nen_{\rm e} follow an approximately log-normal distribution, and hence

n¯e2ne2ne2n¯e23IN3.\displaystyle\left\langle\frac{\bar{n}_{\rm e}^{2}}{n_{\rm e}^{2}}\right\rangle\approx\left\langle\frac{n_{\rm e}^{2}}{\bar{n}_{\rm e}^{2}}\right\rangle^{3}\equiv I_{\rm N}^{3}\,.

We assume, as is the case in the situations we consider, that LL is much larger than the correlation length of the magnetic and electron density fluctuations. This implies that the only contribution to Rijtot(L𝐳^)R^{\rm tot}_{ij}(L\hat{\mathbf{z}}) which may result in a leading order contribution to 𝒜ij\mathcal{A}_{ij} is,

Rijtot(L𝐳^)BiregBjreg.\displaystyle R_{ij}^{\rm tot}(L\hat{\mathbf{z}})\sim B_{i}^{\rm reg}B_{j}^{\rm reg}.

Finally, we must evaluate Wij(k)W_{ij}(k) in terms of the magnetic and electron density power spectra. We define,

Rδ(𝐱)\displaystyle R_{\delta}(\mathbf{x}) =\displaystyle= (1+δn(𝐲))1(1+δn(𝐲+𝐱))1,\displaystyle\left\langle(1+\delta_{\rm n}(\mathbf{y}))^{-1}(1+\delta_{\rm n}(\mathbf{y}+\mathbf{x}))^{-1}\right\rangle,
RB(𝐱)\displaystyle R_{\rm B}(\mathbf{x}) =\displaystyle= δ𝐁(𝐲)δ𝐁(𝐲+𝐱).\displaystyle\left\langle\delta\mathbf{B}(\mathbf{y})\cdot\delta\mathbf{B}(\mathbf{y}+\mathbf{x})\right\rangle.

We define PB(k)P_{\rm B}(k) and Pδ(k)P_{\rm\delta}(k) relative to RBR_{\rm B} and RδR_{\delta} by the relation,

R(𝐱)=14πd3kP(k)e2πi𝐤𝐱.\displaystyle R(\mathbf{x})=\frac{1}{4\pi}\int{\rm d}^{3}k\,P(k)e^{2\pi i\mathbf{k}\cdot\mathbf{x}}.

We also define,

RN(𝐱)\displaystyle R_{\rm N}(\mathbf{x}) =\displaystyle= δne(𝐲)δne(𝐲+𝐱),\displaystyle\left\langle\delta n_{\rm e}(\mathbf{y})\delta n_{\rm e}(\mathbf{y}+\mathbf{x})\right\rangle,

and corresponding Fourier transform, PNP_{\rm N}. We separate the fluctuations in nen_{\rm e} into short and long wavelength fluctuations, δs\delta_{s} and δl\delta_{l} respectively, and assume they are approximately independent. Thus ne=n¯e(1+δl)(1+δs)n_{\rm e}=\bar{n}_{\rm e}(1+\delta_{l})(1+\delta_{s}). This parameterisation is consistent with the assumption that ne/n¯en_{\rm e}/\bar{n}_{\rm e} has an approximately log-normal distribution. We assume that the short wavelength fluctuations are linear up to some cut-off scale klin1k_{\rm lin}^{-1}. Above this spatial scale we have the long wavelength fluctuations, which are not necessarily linear. We then have that over small spatial scales, klin1\ll k^{-1}_{\rm lin},

Rδ(𝐱)\displaystyle R_{\delta}(\mathbf{x}) \displaystyle\approx n¯e2ne2(1+δs(𝐲))1(1+δs(𝐲+𝐱))1,\displaystyle\left\langle\frac{\bar{n}_{\rm e}^{2}}{n_{\rm e}^{2}}\right\rangle\left\langle(1+\delta_{s}(\mathbf{y}))^{-1}(1+\delta_{s}(\mathbf{y}+\mathbf{x}))^{-1}\right\rangle,
\displaystyle\approx n¯e2ne2ne2n¯e21[1+ne2RN(𝐱)],\displaystyle\left\langle\frac{\bar{n}_{\rm e}^{2}}{n_{\rm e}^{2}}\right\rangle\left\langle\frac{n_{\rm e}^{2}}{\bar{n}_{\rm e}^{2}}\right\rangle^{-1}\left[1+n_{\rm e}^{-2}R_{\rm N}(\mathbf{x})\right],
=\displaystyle= IN2[1+n¯e2RN(𝐱)].\displaystyle I_{\rm N}^{2}\left[1+\bar{n}_{\rm e}^{-2}R_{\rm N}(\mathbf{x})\right].

It follows that for kklink\gg k_{\rm lin} we have approximately,

Pδ(k)IN2n¯e2PN(k).\displaystyle P_{\delta}(k)\approx I_{\rm N}^{2}\bar{n}_{\rm e}^{-2}P_{\rm N}(k).

We assume that klink1,k2k_{\rm lin}\ll k_{1},\,k_{2}. Finally we define,

PBδ(k)=PBδ(𝐤)\displaystyle P_{\rm B\delta}(k)=P_{\rm B\delta}(\mathbf{k}) =\displaystyle= 14πd3pPδ(p)PB(𝐤𝐩).\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}pP_{\delta}(p)P_{\rm B}(\|\mathbf{k}-\mathbf{p}\|).

We note that,

14πd3kPBδ(k)e2πi𝐤𝐱=δ𝐁(𝐲)δ𝐁(𝐲+𝐱)\displaystyle\frac{1}{4\pi}\int{\rm d}^{3}kP_{\rm B\delta}(k)e^{2\pi i\mathbf{k}\cdot\mathbf{x}}=\left\langle\delta\mathbf{B}(\mathbf{y})\cdot\delta\mathbf{B}(\mathbf{y}+\mathbf{x})\right\rangle
(1+δn(𝐲))1(1+δn(𝐲+𝐱))1.\displaystyle\cdot\left\langle(1+\delta_{n}(\mathbf{y}))^{-1}(1+\delta_{n}(\mathbf{y}+\mathbf{x}))^{-1}\right\rangle.

From the definition of PijtotP_{ij}^{\rm tot} and Wij(k)W_{ij}(k) we have,

Wij(k)\displaystyle W_{ij}(k) =\displaystyle= BiregBjregkqPδ(q)dq\displaystyle B_{i}^{\rm reg}B_{j}^{\rm reg}\int_{k}^{\infty}qP_{\delta}(q){\rm d}q
+13δijkqPBδ(q)dq.\displaystyle+\frac{1}{3}\delta_{ij}\int_{k}^{\infty}qP_{B\delta}(q){\rm d}q.

All that remains is to evaluate,

kqPBδ(q)dq=d3pPδ(p)4πVk(𝐩)d3rPB(r)4π𝐫+𝐩,\displaystyle\int_{k}^{\infty}qP_{\rm B\delta}(q){\rm d}q=\int{\rm d}^{3}p\frac{P_{\delta}(p)}{4\pi}\int_{V_{k}(\mathbf{p})}{\rm d}^{3}r\frac{P_{\rm B}(r)}{4\pi\|\mathbf{r}+\mathbf{p}\|},

where Vk(𝐩)V_{k}(\mathbf{p}) is defined by 𝐫+𝐩>k\|\mathbf{r}+\mathbf{p}\|>k. We approximate this integral using 𝐫+𝐩p\|\mathbf{r}+\mathbf{p}\|\approx p in 0<r<p0<r<p and 𝐫+𝐩r\|\mathbf{r}+\mathbf{p}\|\approx r in 0<p<r0<p<r, and find

kqPBδ(q)dq\displaystyle\int_{k}^{\infty}qP_{B\delta}(q){\rm d}q \displaystyle\approx δ𝐁2kqPδ(q)dq\displaystyle\left\langle\delta\mathbf{B}^{2}\right\rangle\int_{k}^{\infty}qP_{\delta}(q){\rm d}q
+IN3kqPB(q)dq.\displaystyle+I_{N}^{3}\int_{k}^{\infty}qP_{B}(q){\rm d}q.

Defining,

WB/N(k)=kqdqPB/N(q),\displaystyle W_{\rm B/N}(k)=\int_{k}^{\infty}q{\rm d}qP_{\rm B/N}(q),

we have for 𝒜ij\mathcal{A}_{ij},

e2iΔ¯𝒜ij(Δ¯1,Δ¯2)\displaystyle e^{2i\bar{\Delta}_{-}}\mathcal{A}_{ij}(\bar{\Delta}_{1},\bar{\Delta}_{2}) \displaystyle\simeq 4IN3Bij2ω1ω22Meff2m¯eff4cos2Δ¯\displaystyle\frac{4I_{N}^{3}B_{ij}^{2}\omega_{1}\omega_{2}}{2M_{\rm eff}^{2}\bar{m}_{\rm eff}^{4}}\cos 2\bar{\Delta}_{-}
4BiregBjregω1ω22Meff2m¯eff4cos2Δ¯+\displaystyle-\frac{4B_{i}^{\rm reg}B_{j}^{\rm reg}\omega_{1}\omega_{2}}{2M_{\rm eff}^{2}\bar{m}_{\rm eff}^{4}}\cos 2\bar{\Delta}_{+}
+Bij2IN2Lsinc2Δ¯16Meff2n¯e2[WN(k1)+WN(k2)]\displaystyle+\frac{B_{ij}^{2}I_{\rm N}^{2}L{\rm sinc}2\bar{\Delta}_{-}}{16M_{\rm eff}^{2}\bar{n}_{e}^{2}}\left[W_{N}(k_{1})+W_{N}(k_{2})\right]
+δijIN3Lsinc2Δ¯48Meff2[WB(k1)+WB(k2)],\displaystyle+\frac{\delta_{ij}I_{\rm N}^{3}L{\rm sinc}2\bar{\Delta}_{-}}{48M_{\rm eff}^{2}}\left[W_{B}(k_{1})+W_{B}(k_{2})\right],

where Bij2=BiregBjreg+δijδ𝐁2/3B^{2}_{ij}=B_{i}^{\rm reg}B_{j}^{\rm reg}+\delta_{ij}\left\langle\delta\mathbf{B}^{2}\right\rangle/3. It is now straightforward to calculate the expectations of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} and the 𝒬i\mathcal{Q}_{i} at a single frequency corresponding to Δ¯\bar{\Delta}, since

𝒫¯γϕ\displaystyle\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} =\displaystyle= 12(𝒜xx(Δ¯,Δ¯)+𝒜yy(Δ¯,Δ¯)),\displaystyle\frac{1}{2}\left(\mathcal{A}_{xx}(\bar{\Delta},\bar{\Delta})+\mathcal{A}_{yy}(\bar{\Delta},\bar{\Delta})\right),
𝒬¯q\displaystyle\bar{\mathcal{Q}}_{\rm q} =\displaystyle= 12(𝒜xx(Δ¯,Δ¯)𝒜yy(Δ¯,Δ¯)),\displaystyle\frac{1}{2}\left(\mathcal{A}_{xx}(\bar{\Delta},\bar{\Delta})-\mathcal{A}_{yy}(\bar{\Delta},\bar{\Delta})\right),
𝒬¯u\displaystyle\bar{\mathcal{Q}}_{\rm u} =\displaystyle= 12(𝒜xy(Δ¯,Δ¯)+𝒜yx(Δ¯,Δ¯)),\displaystyle\frac{1}{2}\left(\mathcal{A}_{xy}(\bar{\Delta},\bar{\Delta})+\mathcal{A}_{yx}(\bar{\Delta},\bar{\Delta})\right),
𝒬¯v\displaystyle\bar{\mathcal{Q}}_{\rm v} =\displaystyle= i2(𝒜xy(Δ¯,Δ¯)𝒜yx(Δ¯,Δ¯)).\displaystyle\frac{i}{2}\left(\mathcal{A}_{xy}(\bar{\Delta},\bar{\Delta})-\mathcal{A}_{yx}(\bar{\Delta},\bar{\Delta})\right).

Note that this implies 𝒬¯v=0\bar{\mathcal{Q}}_{\rm v}=0. It follows that,

𝒫¯γϕ\displaystyle\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} \displaystyle\approx 12(2BeffωMeffm¯eff2)2IN3\displaystyle\frac{1}{2}\left(\frac{2B_{\rm eff}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}I_{\rm N}^{3}
14(2BregωMeffm¯eff2)2cos(2Δ¯)\displaystyle-\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}\cos\left(2\bar{\Delta}\right)
+Beff2L8Meff2n¯e2IN2WN(kcrit)+L24Meff2IN3WB(kcrit),\displaystyle+\frac{B_{\rm eff}^{2}L}{8M_{\rm eff}^{2}\bar{n}_{\rm e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit})+\frac{L}{24M_{\rm eff}^{2}}I_{\rm N}^{3}W_{\rm B}(k_{\rm crit}),

where Beff2Breg2/2+δ𝐁2/3B_{\rm eff}^{2}\equiv B_{\rm reg}^{2}/2+\left\langle\delta\mathbf{B}^{2}\right\rangle/3, and kcrit=|Δ¯|/πLk_{\rm crit}=|\bar{\Delta}|/\pi L. Similarly,

𝒬¯q\displaystyle\bar{\mathcal{Q}}_{\rm q} \displaystyle\approx 𝒬0cos2θreg,\displaystyle\mathcal{Q}_{0}\cos 2\theta_{\rm reg},
𝒬¯u\displaystyle\bar{\mathcal{Q}}_{\rm u} \displaystyle\approx 𝒬0sin2θreg,\displaystyle\mathcal{Q}_{0}\sin 2\theta_{\rm reg},

where,

𝒬0\displaystyle\mathcal{Q}_{0} \displaystyle\equiv 14(2BregωMeffm¯eff2)2IN3\displaystyle\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}I_{\rm N}^{3}
14(2BregωMeffm¯eff2)2cos(2Δ¯)\displaystyle-\frac{1}{4}\left(\frac{2B_{\rm reg}\omega}{M_{\rm eff}\bar{m}_{\rm eff}^{2}}\right)^{2}\cos\left(2\bar{\Delta}\right)
+Breg2L16Meff2n¯e2IN2WN(kcrit).\displaystyle+\frac{B_{\rm reg}^{2}L}{16M_{\rm eff}^{2}\bar{n}_{\rm e}^{2}}I_{\rm N}^{2}W_{\rm N}(k_{\rm crit}).

We can also calculate the variance of the QiQ_{i}. We define,

σi2(Δ¯1,Δ¯2)=𝒬i(Δ¯1)𝒬i(Δ¯2)𝒬¯i(Δ¯1)𝒬¯i(Δ¯2),\displaystyle\sigma_{i}^{2}(\bar{\Delta}_{1},\bar{\Delta}_{2})=\left\langle\mathcal{Q}_{i}(\bar{\Delta}_{1})\mathcal{Q}_{i}(\bar{\Delta}_{2})\right\rangle-\bar{\mathcal{Q}}_{i}(\bar{\Delta}_{1})\bar{\mathcal{Q}}_{i}(\bar{\Delta}_{2}),

and find that,

4σq2\displaystyle 4\sigma_{\rm q}^{2} =\displaystyle= 𝒜xx(Δ¯1,Δ¯2)2+𝒜xx(Δ¯1,Δ¯2)2\displaystyle\|\mathcal{A}_{xx}(\bar{\Delta}_{1},\bar{\Delta}_{2})\|^{2}+\|\mathcal{A}_{xx}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\|^{2}
+\displaystyle+ 𝒜yy(Δ¯1,Δ¯2)2+𝒜yy(Δ¯1,Δ¯2)2\displaystyle\|\mathcal{A}_{yy}(\bar{\Delta}_{1},\bar{\Delta}_{2})\|^{2}+\|\mathcal{A}_{yy}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\|^{2}
\displaystyle- 𝒜xy(Δ¯1,Δ¯2)2𝒜xy(Δ¯1,Δ¯2)2\displaystyle\|\mathcal{A}_{xy}(\bar{\Delta}_{1},\bar{\Delta}_{2})\|^{2}-\|\mathcal{A}_{xy}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\|^{2}
\displaystyle- 𝒜yx(Δ¯1,Δ¯2)2𝒜yx(Δ¯1,Δ¯2)2,\displaystyle\|\mathcal{A}_{yx}(\bar{\Delta}_{1},\bar{\Delta}_{2})\|^{2}-\|\mathcal{A}_{yx}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\|^{2},
4σu2\displaystyle 4\sigma_{\rm u}^{2} =\displaystyle= 2Re(𝒜xx(Δ¯1,Δ¯2)𝒜yy(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xx}^{\ast}(\bar{\Delta}_{1},\bar{\Delta}_{2})\mathcal{A}_{yy}(\bar{\Delta}_{1},\bar{\Delta}_{2})\right)
+\displaystyle+ 2Re(𝒜xx(Δ¯1,Δ¯2)𝒜yy(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xx}^{\ast}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\mathcal{A}_{yy}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\right)
+\displaystyle+ 2Re(𝒜xy(Δ¯1,Δ¯2)𝒜yx(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xy}^{\ast}(\bar{\Delta}_{1},\bar{\Delta}_{2})\mathcal{A}_{yx}(\bar{\Delta}_{1},\bar{\Delta}_{2})\right)
+\displaystyle+ 2Re(𝒜xy(Δ¯1,Δ¯2)𝒜yx(Δ¯1,Δ¯2)),\displaystyle 2{\rm Re}\left(\mathcal{A}_{xy}^{\ast}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\mathcal{A}_{yx}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\right),
4σv2\displaystyle 4\sigma_{\rm v}^{2} =\displaystyle= 2Re(𝒜xx(Δ¯1,Δ¯2)𝒜yy(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xx}^{\ast}(\bar{\Delta}_{1},\bar{\Delta}_{2})\mathcal{A}_{yy}(\bar{\Delta}_{1},\bar{\Delta}_{2})\right)
\displaystyle- 2Re(𝒜xx(Δ¯1,Δ¯2)𝒜yy(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xx}^{\ast}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\mathcal{A}_{yy}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\right)
\displaystyle- 2Re(𝒜xy(Δ¯1,Δ¯2)𝒜yx(Δ¯1,Δ¯2))\displaystyle 2{\rm Re}\left(\mathcal{A}_{xy}^{\ast}(\bar{\Delta}_{1},\bar{\Delta}_{2})\mathcal{A}_{yx}(\bar{\Delta}_{1},\bar{\Delta}_{2})\right)
+\displaystyle+ 2Re(𝒜xy(Δ¯1,Δ¯2)𝒜yx(Δ¯1,Δ¯2)).\displaystyle 2{\rm Re}\left(\mathcal{A}_{xy}^{\ast}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\mathcal{A}_{yx}(\bar{\Delta}_{1},-\bar{\Delta}_{2})\right).

Note that we have assumed that the AiA_{i} have an approximately Gaussian distribution so that the expectation of four AiA_{i} can be written in terms of the expectation of two AiA_{i}. If we take Δ¯1=Δ¯2=Δ¯\bar{\Delta}_{1}=\bar{\Delta}_{2}=\bar{\Delta} then when 𝒫¯γϕ\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi} is dominated by the terms proportional to WNW_{\rm N}, we have

σq2\displaystyle\sigma_{\rm q}^{2} \displaystyle\approx 12𝒫¯γϕ2+12𝒬02cos4θreg,\displaystyle\frac{1}{2}\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}+\frac{1}{2}\mathcal{Q}_{0}^{2}\cos 4\theta_{\rm reg},
σu2\displaystyle\sigma_{\rm u}^{2} \displaystyle\approx 12𝒫¯γϕ212𝒬02cos4θreg,\displaystyle\frac{1}{2}\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}-\frac{1}{2}\mathcal{Q}_{0}^{2}\cos 4\theta_{\rm reg},
σv2\displaystyle\sigma_{\rm v}^{2} \displaystyle\approx 12𝒫¯γϕ212𝒬02.\displaystyle\frac{1}{2}\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}-\frac{1}{2}\mathcal{Q}_{0}^{2}\,.

We note that in the cell model we had σi2𝒫¯γϕ/2\sigma_{i}^{2}\approx\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}/2.

A.3 Measurement Issues

The above evaluation for the cell and power spectrum models is appropriate if measurements of the Stokes parameters and hence 𝒬i\mathcal{Q}_{i} probe only a single frequency at a time, i.e. they are precisely monochromatic. In practice, a measurement at a nominal frequency ω¯\bar{\omega}, will generally be an average over some frequency band with width δω\delta\omega. We call δω/ω¯\delta\omega/\bar{\omega} the spectral resolution. We define 2δΔ2\delta\Delta to be the difference in the value of Δ\Delta across the frequency band. When measurements of the Stokes parameters are made over a finite frequency band, the observable variance in the 𝒬i\mathcal{Q}_{i} is no longer given by the σi2\sigma_{i}^{2} expressions presented above but, in the (more general) case of the power spectrum model, by

σ^i2(Δ¯)=1(2δΔ)2δΔδΔdΔ1δΔδΔdΔ2σi2(Δ1,Δ2).\displaystyle\hat{\sigma}^{2}_{i}(\bar{\Delta})=\frac{1}{(2\delta\Delta)^{2}}\int_{-\delta\Delta}^{\delta\Delta}{\rm d}\Delta_{1}\int_{-\delta\Delta}^{\delta\Delta}{\rm d}\Delta_{2}\sigma_{i}^{2}(\Delta_{1},\Delta_{2}).

We find that for both the cell model and power spectrum model the largest term in σ^i2\hat{\sigma}_{i}^{2} when δΔ=0\delta\Delta=0 is proportional to 1/δΔ1/\delta\Delta when δΔ1\delta\Delta\gg 1. If δΔ1\delta\Delta\gg 1, then σ¯i2𝒫¯γϕ2\bar{\sigma}_{i}^{2}\ll\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2}. Similarly the variance of 𝒫γϕ\mathcal{P}_{\gamma\leftrightarrow\phi} is also much smaller than 𝒫¯γϕ2\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}^{2} when δΔ1\delta\Delta\gg 1 so that, to a good approximation, we have 𝒫γϕ=𝒫¯γϕ\mathcal{P}_{\gamma\leftrightarrow\phi}=\bar{\mathcal{P}}_{\gamma\leftrightarrow\phi}.

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