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suppSupplementary References

Anderson localization of electromagnetic waves in three dimensions

Alexey Yamilov1⋆, Sergey E. Skipetrov2, Tyler W. Hughes3, Momchil Minkov3,
Zongfu Yu3,4,†, Hui Cao5∗

1Physics Department, Missouri University of Science & Technology, Rolla, Missouri 65409
2Univ. Grenoble Alpes, CNRS, LPMMC, 38000 Grenoble, France
3Flexcompute Inc, 130 Trapelo Road, Belmont, MA, 02478
4Department of Electrical & Computer Engineering, University of Wisconsin, Madison, WI, 53705
5Department of Applied Physics, Yale University, New Haven, Connecticut 06520
yamilov@mst.edu
zongfu@flexcompute.com
hui.cao@yale.edu

Anderson localization marks a halt of diffusive wave propagation in disordered systems. Despite extensive studies over the past 40 years, Anderson localization of light in three dimensions has remained elusive, leading to the question of its very existence. Recent orders-of-magnitude speed-up of finite-difference time-domain calculations allows us to conduct brute-force numerical simulations of light transport in fully disordered 3D systems with unprecedented dimension and refractive index contrast. We demonstrate three-dimensional localization of vector electromagnetic waves in random packings of metallic spheres, in sharp contrast to the absence of localization for dielectric spheres with a refractive index contrast up to 10. Our work opens a wide range of avenues in both fundamental research related to Anderson localization and potential applications using 3D localized light.

Anderson localization (AL)  (?) is an emergent phenomenon for both quantum and classical waves including electron  (?, ?, ?), cold-atom  (?, ?), electromagnetic (EM)  (?, ?, ?, ?, ?), acoustic  (?, ?), water  (?), seismic  (?), and gravity  (?) waves. Unlike in one or two dimensions, AL in three dimensions (3D) requires strong disorder  (?, ?, ?, ?). A mobility edge separating the diffuse transport regime from AL can be estimated from the Ioffe-Regel criterion keffs1k_{\text{eff}}\,\ell_{s}\sim 1, where keffk_{\text{eff}} is the effective wavenumber in the medium and s\ell_{s} is the scattering mean free path  (?). This criterion suggests two avenues to achieving localization: reduction of keffk_{\text{eff}} or s\ell_{s}. For EM waves, the former is realized by introducing partial order or spatial correlation in scatterer positions  (?, ?). In comparison, reaching localization of light in fully random photonic media by increasing scattering strength (decreasing s\ell_{s}) turns out to be much more challenging  (?, ?). Despite successful experiments in low-dimensional systems  (?, ?, ?), 3D localization remained stubbornly elusive  (?), which triggered theoretical  (?, ?) and experimental  (?) studies of the mechanisms that impede it.

Anderson himself originally proposed “a system composed essentially of random waveguides near cut-off and random resonators, such as might be realized by a random packing of metallic balls of the right size” as “the ideal system” for localization of EM radiation  (?). In practice, the absorption of metals obscures localization  (?, ?), and the experimental focus shifted to dielectric materials with low loss and high refractive index  (?, ?, ?, ?, ?). However, even for dielectric systems, experimental artifacts due to residual absorption and inelastic scattering mar the data  (?, ?). Numerically, these artifacts can be excluded, but 3D random systems of sufficiently large dimension and high refractive index contrast could not be simulated due to an extraordinarily long computational time required  (?, ?).

Recent implementation of the finite-difference time-domain (FDTD) algorithm on emerging computing hardware has brought orders of magnitude speed-up of numerical calculation  (?, ?). Using this highly-efficient hardware-optimized version of the FDTD method, we solve the Maxwell equations by brute force in 3D. It enables us to simulate sufficiently large systems and high refractive index contrast to address the following questions: can 3D AL of EM waves be achieved in fully random systems of dielectric scatterers? If not, can it occur in any other systems without aid of spatial correlations?

Answering these long-standing questions not only addresses the fundamental aspects of wave transport and localization across multiple disciplines, but also opens new research avenues and applications. For example, in topological photonics  (?), the interplay between disorder and topological phenomena may be explored beyond the limit of weak disorder in low-dimensional systems  (?). Also in cavity quantum electrodynamics with Anderson-localized modes  (?), going 3D will avoid the out-of-plane loss inherent for 2D systems and cover the full angular range of propagation directions  (?). In addition to fundamental studies, disorder and scattering has been harnessed for various photonic device applications, but mostly with diffuse waves  (?). Anderson-localized modes can be used for 3D energy confinement to enhance optical nonlinearities, light-matter interactions, and control random lasing as well as targeted energy deposition.

We first consider EM wave propagation through a 3D slab of randomly packed lossless dielectric spheres of radius r=100r=100 nm and refractive index n=3.5n=3.5. This corresponds to the highest index contrast achieved experimentally in optical range with porous GaP around the wavelength λ=650\lambda=650 nm in the vicinity of the first Mie resonance of an isolated sphere, see Supplementary Information (SI). To avoid spatial correlations, the sphere positions are chosen completely randomly, leading to spatial overlap where index is capped at the same value of nn. We compute the spatial correlation function of such structure, which reveals that the correlation vanishes beyond the particle diameter (SI). To avoid light reflection at the interfaces of the slab, we surround it by a uniform medium with the refractive index equal to the effective index of the slab, neff=[(1f)+fn2]1/2n_{\text{eff}}=[(1-f)+fn^{2}]^{1/2}, for a given dielectric volume filling fraction ff (Fig. 1a). As described in SI, for each wavelength, we compute the scattering mean free path s\ell_{s} directly from the rate of attenuation of co-polarized field with depth. This, together with the effective wavenumber keff=neff(2π/λ)k_{\text{eff}}=n_{\text{eff}}\,(2\pi/\lambda), gives the Ioffe-Regel parameter plotted in Fig. 1c. It features a minimum around λ=650\lambda=650 nm, and the smallest value of keffs0.9k_{\text{eff}}\,\ell_{s}\simeq 0.9 is reached at f=38%f=38\%. We also compute the transport mean free path t\ell_{t} from continuous wave (CW) transmittance of an optically thick slab with thickness LtL\gg\ell_{t} (SI). In Fig. 1d, kefftk_{\text{eff}}\,\ell_{t} also exhibits a dip in the same wavelength range as keffsk_{\text{eff}}\,\ell_{s}, however, the smallest kefftk_{\text{eff}}\,\ell_{t} is found at lower ff of 1818–29%, as the dependent scattering sets in at higher ff. In search for AL in this wavelength range, we numerically simulate propagation of a narrowband Gaussian pulse centered at λ0=650\lambda_{0}=650 nm with plane wavefront, and compute the transmittance through the slab T(t)T(t) as a function of arrival time tt. The diffusive propagation time τD\tau_{D} approximately corresponds to the arrival time of the peak in Fig. 1e. At tτDt\gg\tau_{D}, the decay of the transmitted flux is exponential over 1212 orders of magnitude, as expected for purely diffusive systems  (?). Rate of this exponential decay is equal to 1/τD1/\tau_{D}, which is directly related (?) to the smallest diffusion coefficient within the spectral range of the excitation pulse (SI). In Fig. 1f, the dependence of this diffusion coefficient DD on the dielectric filling fraction ff exhibits a minimum at f30%f\sim 30\%. Inset in Fig. 1e shows that the further increase of the slab thickness does not lead to any deviation from diffusive transport. Furthermore, the diffusive behavior persists in the numerical simulation with increased spatio-temporal resolution (SI). At tτDt\gg\tau_{D}, the spatial intensity distribution inside the system features a depth profile (averaged over cross-section) equal to that of the first eigenmode of the diffusion equation (Fig. 1b). We therefore rule out a possibility of AL in uncorrelated ensembles of dielectric spheres with n=3.5n=3.5.

At microwave frequencies, the refractive index may be even higher than n=3.5n=3.5. We therefore, perform numerical simulation of a 3D slab of dielectric spheres with n=10n=10. The main results are summarized here, and details are presented in SI. A large scattering cross section σs(λ)\sigma_{s}(\lambda) of a single sphere near the first Mie resonance leads to strong dependent scattering already at small filling fractions. We find the Ioffe-Regel parameter keffs1k_{\text{eff}}\,\ell_{s}\gtrsim 1 despite the very high refractive index contrast. This is attributed to dependent scattering that becomes significant even at relatively low dielectric filling fraction ff. The numerically calculated T(t)T(t) for L/t1L/\ell_{t}\gg 1 does not exhibit any deviation from diffusive transport: at tτDt\gg\tau_{D}, the decay of transmittance is still exponential over 10\sim 10 orders of magnitude. In addition, scaling of CW transmittance with the inverse slab thickness 1/L1/L remains linear for all ff, as expected for diffusion (SI). We therefore conclude that AL does not occur in random ensembles of dielectric spheres, thus closing the debate about the possibility of light localization in a white paint  (?, ?).

Previous studies  (?, ?) suggest that absence of AL for EM waves may be due to longitudinal waves that exist in a heterogeneous dielectric medium, where the transversality condition 𝐄(𝐫)=0\nabla\cdot\mathbf{E}(\mathbf{r})=0 does not follow from the Gauss’s law [ϵ(𝐫)𝐄(𝐫)]=0\nabla\cdot[\epsilon(\mathbf{r})\mathbf{E}(\mathbf{r})]=0, because of the position dependence of ϵ(𝐫)\epsilon(\mathbf{r}). Here, we propose to suppress the contribution of longitudinal waves to optical transport and realize AL of EM waves by using perfectly conducting spheres as scatterers. The Poynting vector is parallel to the surface of a perfect electric conductor (PEC)  (?) and EM energy flows around a PEC particle without coupling to longitudinal surface modes. The volume of PEC spheres is simply excluded from the free space and becomes unavailable for light. Thus, at high PEC volume fraction, light propagates in a random network of irregular air cavities and waveguides formed by the overlapping PEC spheres, akin to the original proposal of Anderson  (?).

Similarly to the dielectric systems above, we simulate a 3D slab composed of randomly packed, overlapping PEC spheres of radius r=50r=50 nm in air. Figure 2 shows the results of simulating an optical pulse propagating through 10 μ\mum×\times10 μ\mum×\times3.3 μ\mum slabs of various PEC fractions. T(t)T(t) displays non-exponential tails at high fractions f=41%, 48%f=41\%,\ 48\% in Fig. 2a. From the decay rate obtained via a sliding-window fit, we extract a time-dependent diffusion coefficient D(t)D(t), c.f. Fig. 2b, which shows a power-law decay with time, as predicted by the self-consistent theory of localization (?). The non-exponential decay of T(t)T(t) and the time-dependence of DD are the signatures of AL  (?, ?). In contrast, at lower PEC fractions f=8%, 15%f=8\%,\ 15\%, DD remains constant in time. Figure 2c reveals a transition from time-invariant DD to time-dependent D(t)D(t) around f=33%f=33\% where D(t)D(t) starts deviating from a constant. Using Fourier transform, we compute the spectrally resolved transmittance T(λ)T(\lambda). Figures 2d,e contrast T(λ)T(\lambda) of diffusive and localized systems. The former features smooth, gradual variations with λ\lambda due to broad overlapping resonances, whereas the latter exhibits strong resonant structures consistent with the average mode spacing exceeding the linewidth of individual modes, in accordance with Thouless criterion of localization, as the spectral narrowing of modes is intimately related to their spatial confinement  (?, ?, ?). Color maps in Figs. 2d,e show spatial intensity distributions inside the systems, I(x,y0,z;λ)x\langle I(x,y_{0},z;\lambda)\rangle_{x}, averaged over xx for a cross-section y=y0y=y_{0}. These two-dimensional maps contrast slow variation with zz and λ\lambda in the diffusive system (panel d) to the sharp features due to spatially-confined modes in the localized system (panel e). Furthermore, there exist ‘necklace’ states with multiple spatially separated intensity maxima, originally predicted for electrons in metals  (?).

Insight into the mechanism behind AL in the random ensemble of PEC spheres can be gained from the wavelength dependence of the Ioffe-Regel parameter ksk\ell_{s}. We compute it using a procedure similar to that in dielectrics (SI). Even at the volume fraction of f=8%f=8\%, s\ell_{s} is well below the prediction of independent scattering approximation (ISA), due to scattering resonances formed by two or more neighboring PEC spheres (SI). As shown in Fig. 3a, s\ell_{s} becomes essentially independent of wavelength in the range of size parameter krkr of PEC spheres. Consequently, the Ioffe-Regel parameter acquires 1/λ1/\lambda dependence as seen in Fig. 3b. It drops below the value of unity within the excitation pulse bandwidth λ650\lambda\simeq 650 nm ±\pm 45 nm for ff between 25%25\% and 33%33\%, in agreement with Fig. 2. We further conduct a finite-size scaling study, after computing the dependence of CW transmittance TT on the slab thickness LL (SI). Figure 3c shows the logarithmic derivative dlog(T)/dlog(L)d\log(T)/d\log(L) as a function of ksk\ell_{s}. In the diffusive regime, Ohm’s law T1/LT\propto 1/L is expected, leading to a scaling power of 1-1, as indeed observed for ks>1k\ell_{s}>1. Around ks1k\ell_{s}\sim 1 we see a departure from 1/L1/L scaling of transmittance. Note that the scaling theory of localization (?) predicts a single-parameter scaling with the dimensionless conductance gg but not with ksk\,\ell_{s}. By estimating the number of transverse modes as N=2π(L/λ)2(1f)2/3N=2\pi(L/\lambda)^{2}(1-f)^{2/3} for L×LL\times L area of the slab, we compute g=TNg=TN (?) and β(g)dlog(g)/dlog(L)\beta(g)\equiv d\log(g)/d\log(L). Figure 3d shows a good agreement between the numerical data and the model function β(g)=2(1+g)log(1+g1)\beta(g)=2-(1+g)\log(1+g^{-1}) (?). In diffusive regime g>1g>1, β(g)1\beta(g)\rightarrow 1; whereas in the localized regime g<1g<1, β(g)log(g)\beta(g)\propto\log(g). The latter is a manifestation of the negative exponential scaling of gg with LL in the regime of Anderson localization.

To obtain the ultimate confirmation of AL of light in PEC composites, we simulate dynamics of the transverse spreading of a tightly focused pulse—a measurement that has been widely adopted in localization experiments (?, ?, ?). A pulse centered at λ=650\lambda=650 nm with a bandwidth of 90 nm is focused to a small spot of area 0.5\simeq 0.5 μm2\mu\rm{m}^{2} at the front surface of a wide 3D slab of dimensions 33 μ\mum×\times33 μ\mum×\times3.3 μ\mum, c.f. Fig. 4a. We compute the transverse extent of intensity distribution I(x,y,z=L;t)I(x,y,z=L;t) at the back surface of the slab. For a diffusive PEC slab with f=15%f=15\%, we observe a rapid transverse spreading of light with time in Fig. 4b, which approaches the lateral boundary of the slab within \sim 2 ps. In sharp contrast, in the localized system in Fig. 4c (f=48f=48%), the transmitted intensity profile remains transversely confined even after 20 ps. This time corresponds to a free space propagation of 6 mm, which is 2000\sim 2000 times longer than the actual thickness of the slab. Figure 4d quantifies this time evolution with the output beam diameter d(t)=2[PR(t)/π]1/2d(t)=2[\text{PR}(t)/\pi]^{1/2}, where PR(t)=[I(x,y,L;t)𝑑x𝑑y]2/I(x,y,L;t)2𝑑x𝑑y\text{PR}(t)=[\int\int I(x,y,L;t)dxdy]^{2}/\int\int I(x,y,L;t)^{2}dxdy is the intensity participation ratio. For a diffusive slab, d(t)t1/2d(t)\propto t^{1/2}, while in the localized regime, d(t)d(t) saturates at a value of the order of slab thickness LL. Such an arrest of the transverse spreading in the localized PEC systems persists with increased spatio-temporal resolution of the numerical simulation (SI). Further evidence of AL include non-linear depth profile and strong non-Gaussian fluctuations of intensity inside the system (SI). We also confirm our results by repeating calculations for 3D slabs of PEC spheres with larger radius r=100r=100 nm, and obtaining similar scaling behavior (SI), as in Figs. 3cd.

The striking difference between light propagation in dense random ensembles of dielectric and PEC spheres cannot be accounted for by the Ioffe-Regel parameter, as both reach keffs1k_{\text{eff}}\,\ell_{s}\sim 1 for similar values of the size parameter krkr (Figs. 1c, 3b). AL in 3D PEC composites with uncorrelated disorder reveals a localization mechanism that is unique for PEC. In contrast to a dielectric system where light propagates everywhere (both inside and outside the scatterers), the propagation is restricted to the voids between scatterers in the PEC system. AL takes place when the typical size of voids becomes smaller than the wavelength, and light can no longer ‘squeeze’ through them. This qualitative model correctly predicts both AL in the long-wavelength regime and the increase of the critical volume fraction ff for localization with the scatterer size rr (SI).

Finally, we test AL in real-metal aggregates. In the microwave spectral region, the skin depth of crystalline metals like silver, aluminum and copper is several orders of magnitude shorter than the wavelength λ\lambda and the scatterer size rr in the regime of kr1kr\sim 1. Since the microwave barely penetrates into the metallic scatterers, our simulation results are almost identical to those for PEC. To account for the imperfections due to polycrystallinity, surface defects, oxide layers etc., we lower the metal conductivity to match the experimentally measured absorption rate in aggregates of aluminum spheres  (?). Simulations unambiguously show the arrest of transverse spreading of a focused pulse (Fig. 4e), demonstrating AL in 3D random aggregates of aluminum spheres. Additional evidence of AL is presented in SI. Moreover, even at optical frequencies, where realistic metals deviate notably from PEC, the arrest of transverse spreading persists in 3D silver nanocomposites, as shown in SI. Possible light localization in 3D nanoporous metals will have a profound impact on their applications in photo-catalysis, optical sensing, energy conversion and storage.

In summary, our large-scale microscopic simulations of EM wave propagation in 3D uncorrelated random ensembles of spheres show no signs of Anderson localization for dielectric spheres with refractive indices n=3.5n=3.5–10. This may explain multiple failed attempts of experimental observation of AL of light in 3D dielectric systems over the last three decades  (?, ?, ?, ?, ?). At the same time, we report the first numerical evidence of EM wave localization in random ensembles of PEC spheres over a broad spectral range. Localization is confirmed by eight criteria: the Ioffe-Regel criterion, the Thouless criterion, non-exponential decay of transmittance under pulsed excitation, vanishing of the diffusion coefficient, existence of spatially localized states, scaling of conductance, arrest of the transverse spreading of a narrow beam, and enhanced non-Gaussian fluctuations of intensity. Our study calls for renewed experimental efforts to be directed at low-loss metallic random systems  (?). In the SI, we propose a realistic microwave experiment that avoids experimental pitfalls  (?) and provides a tell-tale sign of Anderson localization.

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Refer to caption
Figure 1: Absence of non-diffusive transport in random dielectric systems with index contrast of 3.5. a, 3D slab filled with dielectric spheres at random uncorrelated positions (radius r=100r=100 nm, refractive index n=3.5n=3.5) in air. The slab cross-section is 10 μ\mum×\times10 μ\mum = 100 μ\mum2 and thickness is L=3.3L=3.3 μ\mum. b, 3D distribution of light intensity inside the slab (dielectric filling fraction f=29f=29%, L/t=33L/\ell_{t}=33) at long delay time after a short pulse of plane wave front is incident on the front surface. Red curve with shading shows the average depth profile. c, Spectral dependence of the Ioffe-Regel parameter keffsk_{\text{eff}}\,\ell_{s} for different volume filling fractions of dielectric spheres, showing enhancement of scattering around single-sphere Mie resonances. The horizontal dashed line marks the Ioffe-Regel criterion keffs=1k_{\text{eff}}\,\ell_{s}=1 for 3D localization. d, Transport mean free path t\ell_{t} (in units of 1/keff1/k_{\text{eff}}) as a function of wavelength, revealing a saturation by dependent scattering at high dielectric filling fractions. The vertical dashed lines mark spectral width (33 nm) of the excitation pulse in b and e. e, Transmittance of the 3D slab for a pulsed excitation, showing exponential decay in time for all dielectric filling fractions, in agreement with diffusive transport. Inset shows persistence of diffusion when L/tL/\ell_{t} is increased from 33 to 60 for f=38%f=38\%, c.f. green line. f, Dependence of the minimum diffusion coefficient within the pulse bandwidth on the dielectric filling fraction ff, exhibiting a minimum value of 3.6 m2/s at f30%f\simeq 30\%.
Refer to caption
Figure 2: Anderson localization of light in 3D disordered PEC. a, Transmittance T(t)T(t) of an optical pulse through a 3D slab (10 μ\mum ×\times 10 μ\mum ×\times 3.3 μ\mum) of randomly packed PEC spheres with radius r=50r=50 nm and volume filling fractions ff from 8% to 48%. b, Time-resolved diffusion coefficient D(t)D(t) extracted from the decay rate of T(t)T(t) in panel a, decreasing with time as 1/t1/t at high ff. c, Short-time DD (dots) and the interval of variation of DD with time (bars) at different ff. d,e, Continuous-wave transmittance spectrum T(λ)T(\lambda) in diffusive (d, f=15%f=15\%, blue line) and localized (e, f=48%f=48\%, red line) PEC slabs. Color map: depth profile of average intensity I(x,y0,z;λ)x\langle I(x,y_{0},z;\lambda)\rangle_{x} inside the slab at different wavelengths, highlighting the localized and necklace-like states for f=48f=48%.
Refer to caption
Figure 3: Transition from diffusion to Anderson localization in 3D disordered PEC. a, Scattering mean free path s\ell_{s} for PEC volume filling fractions ff from 8% to 48%. s\ell_{s} is nearly flat over broad spectral range. b, Spectral dependence of Ioffe-Regel parameter ksk\ell_{s}, exhibiting 1/λ1/\lambda dependence (dashed lines). c, Scaling of the continuous-wave (CW) transmittance TT with slab thickness LL versus Ioffe-Regel parameter ksk\ell_{s}, revealing diffusion-localization transition at ks1k\ell_{s}\sim 1. Blue dashed line denotes diffusive scaling TL1T\propto L^{-1}; red dashed line marks ks=1k\ell_{s}=1. d, Single-parameter scaling of dimensionless conductance gg for diffusion-localization transition (solid black line), in agreement with numerical data for 6 PEC filling fractions. Blue and red dashed lines denote diffusive and localized scalings gLg\propto L and gexp(L/ξ)g\propto\exp(-L/\xi) respectively, where ξ\xi is the localization length.
Refer to caption
Figure 4: Arrest of transverse spreading of transmitted beam in 3D localized PEC systems. a, Schematic of transverse spreading of a tightly-focused pulse propagating through a diffusive slab of cross section 33 μ\mum×\times33 μ\mum and thickness L=3.3L=3.3 μ\mum. b, 2D intensity distribution at the output surface (normalized to the maximum) for different delay times, showing a lateral expansion of the beam in the diffusive slab of PEC filling fraction f=15%f=15\%. c, Absence of transverse spreading for f=48%f=48\%, due to Anderson localization. d, Lateral diameter of the transmitted beam d(t)d(t) increases as t\sqrt{t} in the diffusive slab (blue dots), but it saturates to a constant value in the localized slab (red dots). e, Same as d but for a slab (L=6L=6 cm) of aluminum spheres (r=0.28r=0.28 cm, f=35%f=35\% and 60%60\%) with realistic conductivity σ0=3.8×104\sigma_{0}=3.8\times 10^{4} Ω1/m{\rm\Omega^{-1}/m} at microwave frequency 20\sim 20 GHz.

Acknowledgments

This work is supported by the National Science Foundation under Grant Nos. DMR-1905465, DMR-1905442, and the Office of Naval Research (ONR) under Grant No. N00014-20-1-2197. We thank Shanhui Fan and Bart van Tiggelen for enlightening discussions.

Conflict of interest statement

TWH, MM, ZY have financial interest in Flexcompute Inc., which develops the software Tidy3D used in this work.

Author contributions

A.Y. performed numerical simulations, analyzed the data and compiled all results. S.E.S. conducted theoretical study and guided data interpretation. T.W.H. and M.M. implemented the hardware-accelerated FDTD method and aided in the setup of the numerical simulations. Z.Y. and H.C. initiated this project and supervised the research. A.Y. wrote the first draft, S.E.S. and H.C. revised the content and scope, T.W.H. and M.M. and Z. Y. edited the manuscript. All co-authors discussed and approved the content.

Supplementary Information:
Anderson localization of electromagnetic waves in three dimensions

Alexey Yamilov1⋆, Sergey E. Skipetrov2, Tyler W. Hughes3, Momchil Minkov3,
Zongfu Yu3,4,†, Hui Cao5∗
 
1Physics Department, Missouri University of Science & Technology,Rolla, Missouri 65409
2Univ. Grenoble Alpes, CNRS, LPMMC, 38000 Grenoble, France
3Flexcompute Inc, 130 Trapelo Road, Belmont, MA, 02478
4Dept. of Electrical & Computer Engineering, University of Wisconsin, Madison, WI, 53705
5Department of Applied Physics, Yale University, New Haven, Connecticut 06520
yamilov@mst.edu
zongfu@flexcompute.com
hui.cao@yale.edu
 

1 Methods

1.1 Numerical method

Over the years, various techniques have been developed for large-scale 3D computations. One efficient method for simulating light scattering in large inhomogeneous media is based on Born series \citesupposnabrugge2016convergent, kruger2017solution. This method, however, is limited to small contrast in refractive index between the scatterers and the host medium. To achieve 3D localization, a large refractive-index contrast is needed to enhance light scattering, which makes it necessary to include many terms of the Born series. This greatly increases the computational complexity, worsening the convergence of such an iterative algorithm.

Another family of approaches for simulating wave transport in 3D aggregates of spherical particles is based on iterative multi-sphere scattering expansions, e.g., the generalized multi-particle-Mie (GMM) formalism \citesupp2001_Xu_GMM, 2007_Pellegrini_GMM, 2022_Egel_GMM, the multi-sphere T-matrix (MSTM) \citesupp2011_Mackowski_MSTM, and the fast multipole method (FMM) \citesuppgumerov2005computation. The latest, and the most advanced implementation, deployed on GPUs for speedup, is capable of simulating up to 10510^{5} dielectric spheres \citesupp2017_Wiersma_3D_simulations, (?). But the state-of-the-art algorithm (CELES) has not been used for index contrast higher than 22. This is because the Mie resonances of high-index spheres can have very long lifetimes and strong internal fields, leading to an extremely slow convergence of the iterative algorithm or even its failure. Moreover, the spheres cannot touch or overlap, which would invalidate the Mie solution for isolated spheres. If two spheres are very close to each other, the near-field effects will excite high-order multipoles, causing slow or failed convergence. Therefore, these methods require a minimum distance between densely-packed spheres, which introduces spatial correlations of the scattering structures  (?) that are known to affect Anderson localization \citesupp2008_Conti_AL_laser, (?).

The finite-difference time-domain (FDTD) method directly solves the Maxwell’s equations in space and time \citesupp2005_Taflove. It does not make any physical approximations, and is capable of simulating large-refractive-index, spatially-overlapping or touching particles with high filling fraction. The effects of spatial correlations of scattering structures that could contribute to Anderson localization \citesupp2008_Conti_AL_laser, (?), are avoided by completely-random placement of individual scatterers in our study, as shown in Sec. 1.4 below.

The ability of simulating refractive-index contrast of 3.5–10 in our study is the key to demonstrate that increasing index contrast will not precipitate Anderson localization. However, simulating such high refractive-index particles requires very fine spatial and temporal resolution, leading to an extremely long computational time. Previous FDTD simulations were limited to small 3D structures containing 10310^{3}10410^{4} particles  (?), (?). Our hardware-accelerated implementation of the FDTD method  (?) reduces the computational time by several orders of magnitude, allowing us to simulate a 3D system with 6×1066\times 10^{6} scatterers in about 40 min.

The orders-of-magnitude reduction in computational time is essential to search for Anderson localization in 3D PEC and real-metal composites, because it allows to repeat the simulations many times with varying parameters like particle size, volume fraction, dielectric function and conductivity, lateral dimension and thickness of simulated systems, etc. Moreover, our time-domain simulation can extract the fields at more than 10001000 discrete frequencies from a single run, by Fourier transform. In contrast, the frequency-domain methods based on Born series and GMM/MSTM simulate only one frequency per run. Using such methods to simulate time-dependent transport, particularly at long delay time, requires repeating the calculations at many closely-spaced frequencies so that the Fourier transform will give the long-time behavior.

1.2 System geometry and dimension

Unless otherwise specified, our simulations are carried out on disordered systems in the slab geometry Lx=LyLL_{x}=L_{y}\gg~{}L (Fig. 1a). A plane wave with the electric field polarized along xx-axis is incident on the front surface of the slab. The bandwidth of a Gaussian pulse, Δλ=\Delta\lambda= 90 nm, is chosen such that t\ell_{t} remains nearly invariant with wavelength. Periodic boundary conditions are applied along xx and yy axes. To ensure that the periodicity would not affect the results presented in this manuscript, we make the transverse dimensions Lx,LyL_{x},L_{y} of the simulated slabs much larger than the thickness LL. In the transmission simulations such as those in Fig. 1, the ratio is Lx/L=Ly/L=3L_{x}/L=L_{y}/L=3, so that any effect induced by periodic boundary conditions occurs on a length scale much larger than any relevant transport or localization scales. For the simulations of the transverse spreading (Figs. 4,S2,S12), we simulate much wider slabs having Lx/L=Ly/L=10L_{x}/L=L_{y}/L=10 to avoid any edge effect.

The slab is sandwiched between homogeneous layers of refractive index nBn_{B} and thickness Δ0\Delta_{0}, which in turn are surrounded by perfectly matched layers of thickness ΔPML\Delta_{PML}. These thicknesses are chosen as ΔB=ΔPML=2λ0,λ0,2λ0\Delta_{B}=\Delta_{PML}=2\lambda_{0},\lambda_{0},2\lambda_{0} for the slabs of dielectric spheres with refractive index n=3.5,10n=3.5,10 and PEC spheres, respectively. For the dielectric slabs, n0n_{0} is equal to the effective index neffn_{\text{eff}} found by averaging the dielectric constant, while for PEC n0=1n_{0}=1. λ0=650\lambda_{0}=650 nm is the central wavelength of optical pulses in all simulations. The spatial discretization step of the FDTD algorithm is λ0/20\lambda_{0}/20 for n=3.5n=3.5 and PEC, and λ0/60\lambda_{0}/60 for n=10n=10. This corresponded to time steps of dt56×1018dt\simeq 56\times 10^{-18} s and dt19×1018dt\simeq 19\times 10^{-18} s, respectively.

1.3 Numerical accuracy and scaling

Tidy3D solver (?) is an implementation of the standard FDTD method, which does not make any physical approximation or impose any constraint of the scattering structures. The remaining numerical issue in FDTD simulation is sufficient discretization of space and time \citesupp2005_Taflove. We have carefully tested spatio-temporal resolution of FDTD simulations to ensure consistency of our numerical results so that the conclusions of our study are robust and independent of the discretization. We present two examples of such tests below.

(i) One key evidence for the absence of AL in 3D dielectric random media is the exponential decay of transmitted flux T(t)T(t), shown in Fig. 1e of the main text. This result is obtained with the spatial grid size of λ0/20\lambda_{0}/20. When the spatial grid is reduced to λ0/40\lambda_{0}/40 and the temporal step size is also halved, the exponential decay of T(t)T(t) persists over 12 orders of magnitude in Fig. S1, which confirms the diffusive transport.

(ii) A tell-tale sign of AL in PEC composites is the arrest of transverse spreading of the transmitted beam, when an incident pulse is focused to a slab, as shown in Fig. 4c,d of the main text. This result is obtained with numerical resolution of λ0/20\lambda_{0}/20. To test the robustness of this result, we vary the resolution from λ0/10\lambda_{0}/10 to λ0/40\lambda_{0}/40. Fig. S2a shows the result with λ0/40\lambda_{0}/40 resolution: the transverse diameter of transmitted beam d(t)d(t) saturates to a constant value in time, consistent with the result of λ0/20\lambda_{0}/20 resolution in Fig. 4d. The asymptotic beam diameter dd_{\infty} is plotted versus the numerical resolution in Fig. S2b. It confirms the consistency of our numerical results: the arrest of transverse spreading persists in all simulations performed on the progressively finer meshes. Notably, the arrest is already seen in simulation with λ0/10\lambda_{0}/10 resolution, despite a slight difference in the value of dd_{\infty}.

Since the Tidy3D implements the standard FDTD algorithm, the scaling of computing time with system size is the same as the standard FDTD method \citesupp2005_Taflove. More specifically, the computing time scales as NxNyNzNtN_{x}\,N_{y}\,N_{z}\,N_{t}, where NxN_{x}, NyN_{y}, NzN_{z} denote the number of spatial grid points in xx, yy, zz dimensions, NtN_{t} is the total number of time steps. Typically the spatial grid size along xx, yy, zz is identical, and it is proportional to the time step.

We note that the finite discretization introduces slight anisotropy and dispersion to the simulated system. To mitigate such effects, the spatio-temporal resolution could be further increased according to the system size, which would affect the scaling of computing time \citesuppkruger2017solution. However, this is not necessary in our simulations of random ensembles of dielectric or metal spheres, because the statistical properties like scattering and transport mean free paths are barely modified. By varying the spatio-temporal grid size, we find the small effects caused by finite discretization are simply equivalent to a tiny change of the refractive index nn of the medium and/or a tiny change of the volume filling fraction ff. As shown in the manuscript, AL is absent in the dielectric systems for a broad range of nn’s, whereas AL persists in a broad range of ff’s in the PEC systems.

Our extensive tests of the numerical procedure and accuracy confirm the consistency and robustness of the results and conclusions in this manuscript.

1.4 Spatial correlation function

In order to avoid any residual spatial correlation of scattering structures, we adopt a uniform random distribution of scatterer centers. The structure factor obtained from Fourier transform of center positions is equal to unity \citesupp2018_Torquato_review. The spheres with center spacing smaller than their diameter will overlap in space, and the overlapping region is assigned the refractive index equal to that of an isolated sphere.

We calculate the spatial correlation function C(Δ)=h(𝝆)h(𝝆+𝚫)/h(𝝆)21C(\Delta)=\langle h(\boldsymbol{\rho})\,h(\boldsymbol{\rho}+{\bf\Delta})\rangle/\langle h(\boldsymbol{\rho})\rangle^{2}-1, where, 𝝆\boldsymbol{\rho} denotes the spatial position, h(𝝆)h(\boldsymbol{\rho}) is a binary function equal to 11 inside the dielectric/PEC/metal scatterers and 0 outside, and \langle...\rangle denotes averaging over 𝝆\boldsymbol{\rho}, direction of 𝚫{\bf\Delta}, and random ensemble. Fig. S3 shows the normalized C(Δ)/C(0)C(\Delta)/C(0) with h(𝝆)h(\boldsymbol{\rho}) obtained from the discretized structures in the actual FDTD calculations of systems with particle radii r=50r=50 nm and 100100 nm, and the PEC volume fractions of f15%f\sim 15\% and 50%\sim 50\%. In all cases, the spatial correlation extends over the range Δ\Delta of one particle diameter 2r2r, as expected for a random arrangement of spherical particles.

1.5 Scattering mean free path

Scattering mean free path s\ell_{s} measures the average distance traveled between two consecutive scattering events. Its value in Figs. 1c and 3a is extracted from the attenuation of the coherent component of the incident field. We simulate systems with dimension Lx=100λ0,Ly=L=2λ0L_{x}=100\lambda_{0},L_{y}=L=2\lambda_{0} for n=3.5n=3.5 and PEC, Lx=100λ0,Ly=L=λ0L_{x}=100\lambda_{0},L_{y}=L=\lambda_{0} in the n=10n=10 case. The quantity Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x} is computed by averaging over the long dimension (along xx-axis) of the system for one particular cross section y=y0y=y_{0}. Average co-polarized field amplitude |Ex(x,y0,z;λ)x||\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x}| decays exponentially at a rate 1/(2s)1/(2\ell_{s}), from which s\ell_{s} is obtained for each wavelength. The phase of Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x} gives keffk_{\text{eff}}.

Figures S4S5S6 show the amplitude and phase of coherent field Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x}, as well as its real and imaginary parts, in random aggregates of dielectric spheres and PEC spheres. In the dielectric systems, spectral regions with strong attenuation, i.e. short scattering mean free path, are concentrated in the vicinity of Mie resonances of the constituent spherical particles. In contrast, in the PEC systems, scattering mean free path does not exhibit notable spectral features in Fig. 3a. In Figs. S6a,e, this can be seen from a constant attenuation rate of the field amplitude.

1.6 Transport mean free path

Transport mean free path t\ell_{t} corresponds to the average travel distance that is required to completely randomize the propagation direction. Transmittance of a continuous wave (CW) at wavelength λ\lambda through a diffusive slab of thickness LL is T(λ)=(5/3)t(λ)/[L+2z0(λ)]T(\lambda)=(5/3)\ell_{t}(\lambda)/[L+2z_{0}(\lambda)], where z0(λ)z_{0}(\lambda) is the extrapolation length  (?). The value of z0(λ)z_{0}(\lambda) can be estimated from the CW depth profile of internal intensity I(z,λ)I(z,\lambda) by linear extrapolation I(z=L+z0,λ)=0I(z=L+z_{0},\lambda)=0 (Fig. S9c). Then the value of t(λ)\ell_{t}(\lambda) is extracted from T(λ)T(\lambda) with known z0(λ)z_{0}(\lambda).

Typically, z0z_{0} depends on the refractive-index mismatch between the slab and the surrounding medium  (?). However, our choice of the refractive index neffn_{\text{eff}} for the surrounding layers eliminates this mismatch for a dielectric slab, leading to z0=(2/3)tz_{0}=(2/3)\ell_{t}  (?). Our numerical data suggest that this relation approximately holds for PEC composites embedded in air as well.

1.7 Diffusion coefficient

Diffusion coefficient D=tvE/3D=\ell_{t}v_{E}/3 depends on both the transport mean free path t\ell_{t} and the energy velocity vEv_{E} \citesupp1996_Lagendijk. The propagation of an optical pulse in a slab geometry makes it possible to directly extract DD from the decay of the transmittance, T(t)exp[t/tD]T(t)\propto\exp[-t/t_{D}], where 1/tD=π2D/(L+2z0)21/t_{D}=\pi^{2}D/(L+2z_{0})^{2}. In the localized slabs such as those in Fig. 2, the decay rate, 1/tD1/t_{D}, changes with time. To obtain D(t)D(t) in Fig. 2b, we use an exponential fit within a time window [t2τD,t+2τD][t-2\tau_{D},t+2\tau_{D}], where τD\tau_{D} is the arrival time of the peak of transmitted flux.

1.8 Scaling functions

To obtain the scaling function dlog(T)/dlog(L)d\log(T)/d\log(L) for the PEC slabs, we compute the logarithmic derivative of CW transmittance TT with respect to slab thickness LL for a range of values of ksk\ell_{s}. First, we use the wavelength dependence of ksk\ell_{s} in Fig. 3a to map ksk\ell_{s} to λ\lambda for each ff. Next, we compute T(λ)T(\lambda) for two systems with different thicknesses L1=2λ0L_{1}=2\lambda_{0} and L2=5λ0L_{2}=5\lambda_{0}, where λ0=650\lambda_{0}=650 nm denotes the center of the wavelength range of interest. Finally, we approximate dlog(T)/dlog(L)d\log(T)/d\log(L) by the finite difference [log(T2)log(T1)]/[log(L2)log(L1)][\log(T_{2})-\log(T_{1})]/[\log(L_{2})-\log(L_{1})] for all λ\lambda and all ff. After eliminating λ\lambda, we obtain the dependence of dlog(T)/dlog(L)d\log(T)/d\log(L) on the Ioffe-Regel parameter ksk\ell_{s} shown in Fig. 3c.

2 Absence of light localization in 3D dielectric systems with refractive-index contrast of 1010

This section reports the results of numerical simulation for a 3D slab of dielectric spheres with n=10n=10. For ease of comparison, we adjust the sphere radius to r=32r=32 nm, so that the first Mie resonance occurs at a wavelength similar to that for n=3.5n=3.5 sphere (compare Figs S4a and S5a). Scattering cross section of a single sphere of n=10n=10 is exceedingly large (Fig. S7a), leading to strong dependent scattering already at small volume filling fractions, and limiting Ioffe-Regel parameter to keffs1k_{\text{eff}}\,\ell_{s}\gtrsim 1 in Fig. S7b. The minimal value of keffsk_{\text{eff}}\,\ell_{s} is almost identical for f=2.5%, 5%, 9%f=2.5\%,\,5\%,\,9\%, and starts to increase for f=18%f=18\% due to dependent scattering. The dependent scattering also results in less variation of the normalized transport mean free path kefftk_{\text{eff}}\,\ell_{t} with λ\lambda in Fig. S7c, similar to the scattering mean free path in Fig. S7b.

Diffusive nature of wave propagation in n=10n=10 dielectric systems can be seen from scaling of the CW transmittance with slab thickness LL. In Fig. S7d we plot transmittance multiplied by LL in the f=2.5%, 5%, 9%, 18%f=2.5\%,\,5\%,\,9\%,\,18\% slabs with three different values of L/λ0=1,2,4L/\lambda_{0}=1,2,4. The largest slab thickness L/λ0=4L/\lambda_{0}=4 corresponds to L/t>361L/\ell_{t}>36\gg 1 for all ff. The overlap between the curves with different LL in the spectral range of the first Mie resonance is a direct manifestation of the diffusive scaling T1/LT\propto 1/L.

Furthermore, we numerically calculate dynamic transmittance under pulsed excitation, T(t)T(t). For thick slabs (L/t1L/\ell_{t}\gg 1), it does not exhibit deviation from the diffusive transport: at tτDt\gg\tau_{D}, the decay is still exponential (Fig. S7e).

The above results confirm light transport is diffusive in 3D dielectric random systems with n=10n=10 spheres.

3 Difference between PEC and dielectric scattering

Besides the absence of longitudinal fields in PEC composites, additional differences with respect to dielectric media facilitate Anderson localization in PEC:

  1. 1.

    Isolated PEC spheres have strong backscattering  (?). It results in a highly anisotropic angular scattering pattern, making t<s\ell_{t}<\ell_{s}. This is very different from the dielectric spheres.

  2. 2.

    Collective scattering resonances are created by two or more adjacent PEC spheres. The spatial arrangement of scatterers in this work lacks spatial correlations in sphere positions, creating a random distribution of distance between them. Even at the PEC volume fraction of f=8%f=8\%, the gap in-between two PEC spheres can be much narrower than λ=650\lambda=650 nm, and the field intensity in the vicinity of the gap is strongly enhanced, as seen in Figs. S8a. Such an enhancement persists at λ=1080\lambda=1080 nm in Figs. S8b, despite the wavelength is much greater than the particle radius rr = 50 nm, leading to a small size parameter kr0.3<1kr\simeq 0.3<1. Already for volume fraction of f=8%f=8\%, a sufficiently broad distribution of gap sizes creates a large number of red-shifted resonances, enhancing the overall scattering at longer wavelengths in Fig. 3a, and making s\ell_{s} well below the prediction \citesupp1999_van_Rossum of the independent scattering approximation (ISA) s=[ρsca(f)σsca(λ)]1\ell_{s}=[\rho_{sca}(f)\,\sigma_{sca}(\lambda)]^{-1}, where ρsca(f)\rho_{sca}(f) is the number density of scatterers and σsca(λ)\sigma_{sca}(\lambda) is the scattering cross section of a single PEC sphere. With an increase of ff to 15%15\% in Figs. S8c,d, additional voids formed by three or more PEC spheres create even a larger variety of scattering resonances at different wavelengths rendering s\ell_{s} nearly constant with λ\lambda.

  3. 3.

    At high volume fraction ff of PEC scatterers, light propagation through air voids is suppressed. In contrast to a dielectric composite which becomes transparent when the dielectric volume fraction approaches 100%, a PEC composite with ff approaching 100% becomes a perfect mirror, as air voids no longer percolate through the system. In our simulations, Anderson localization takes place at PEC volume fractions well below the air percolation threshold (96.6%) \citesupp1981_Percolation_of_spheres,1984_Elam_Percolation_of_spheres. The air voids are still connected by narrow channels through which light may propagate. However, when the typical size of air voids between the PEC scatterers is on the order of the wavelength, light can no longer ‘squeeze’ through the narrow channels. Thus AL occurs at the wavelength comparable to or larger than the typical size aa of air voids between PEC scatterers.

    For a given PEC volume fraction ff, air void size aa is proportional to PEC sphere radius rr. A random system with smaller spheres have a larger number of voids, but the voids themselves have smaller sizes, since the total volume of all voids is fixed by ff. The smaller voids make it harder for light to propagate through a system with smaller spheres, and localization will take place at lower ff. This prediction agrees to our numerical results of lower critical ff for AL with r=50r=50 nm PEC spheres than r=100r=100 nm spheres. The above argument is for fixed wavelength λ\lambda. In a PEC system with given rr and ff, the typical void size aa is fixed, increasing λ\lambda will make it more difficult for light to ‘squeeze’ through voids, facilitating AL at long wavelengths. Consequently, for a given rr, the localization condition of aλa\sim\lambda is fulfilled at a smaller ff at longer λ\lambda, which agrees to our numerical results.

4 Additional evidence for Anderson localization in PEC system

We have examined the intensity distributions inside 3D slabs of PEC spheres with r=50r=50 nm in dynamical simulations. Fig. S9a shows the cross-section averaged depth profiles at very long delay times, I(x,y,z;t)x,y\langle I(x,y,z;t\rightarrow\infty)\rangle_{x,y}, for PEC filling fractions of 15%15\% and 48%48\%. In the diffusive slab of f=15%f=15\%, the asymptotic depth profile matches the first eigenmode of the diffusion equation, sin[π(z+z0)/(L+2z0)]\sin[\pi(z+z_{0})/(L+2z_{0})]. In contrast, the cross-section averaged intensity inside the localized slab with f=48%f=48\% exhibits much larger variation with depth zz. The faster decay towards the surfaces reflects stronger confinement of energy near the center of the slab.

Fluctuation of intensity or transmission coefficients is a powerful criterion of localization  (?). Fig. S9b depicts spectral fluctuation of the cross-section average intensity I(z,λ)=I(x,y,z;λ)x,yI(z,\lambda)=\langle I(x,y,z;\lambda)\rangle_{x,y}, within the wavelength range of 600–700 nm. The normalized variance
varλ[I(z,λ)]/I(z,λ)λ2{\rm var}_{\lambda}[I(z,\lambda)]/\langle I(z,\lambda)\rangle_{\lambda}^{2} corresponds to the magnitude of long-range correlation C2C_{2} \citesupp2014_Sarma_Cofz. In the PEC slab of f=15%f=15\%, C21C_{2}\ll 1, typical of a diffusive system. When ff increases to 48%48\%, C21C_{2}\geq 1, as expected for localized systems\citesupp1999_van_Rossum,2004_Yamilov_passive_corr, (?).

Inside a diffusive system, the CW intensity decays linearly with the depth  (?), and exhibits low fluctuations from realization to realization. This is confirmed in Fig. S9c by comparing I(z,λ)λ\langle I(z,\lambda)\rangle_{\lambda} and exp[log[I(z,λ)]λ]\exp[\langle\log[I(z,\lambda)]\rangle_{\lambda}], which indeed agree well in the PEC slab of f=15%f=15\%. In contrast, in the PEC slab of f=48%f=48\%, these two quantities are markedly different owning to the fact that strong intensity fluctuations lead to log-normal distribution for localized systems \citesupp2000_Mirlin. The depth profile exhibits a roughly exponential decay, as a result of AL.

To further confirm AL in PEC slabs, we repeat the calculations reported in Fig. 3c,d for another system with larger PEC spheres (r=100r=100 nm). Figure S10 demonstrates that transmittance and conductance exhibit similar scaling behaviors as for the PEC slabs of rr = 50 nm in Fig. 3c,d. Although the diffusion-localization transition occurs at a different volume filling fraction ff of PEC spheres, the scaling behaviors with respect to the Ioffe-Regel parameter ksk\,\ell_{s} and to the dimensionless conductance gg are reproduced.

5 Anderson localization in real metals

To demonstrate the possibility of AL in realistic metallic systems, we simulate real metals using parameters reported in literature. The dielectric constant of a metal is related to the conductivity σ(ω)\sigma(\omega) via ϵ(ω)=1+iσ(ω)/ωϵ0\epsilon(\omega)=1+i\sigma(\omega)/\omega\epsilon_{0}, where ϵ0\epsilon_{0} is electric permittivity of vacuum. In the Drude model, the conductivity of a metal is given by σ(ω)=σ0/(1iωτ)\sigma(\omega)=\sigma_{0}/(1-i\omega\tau), where σ0\sigma_{0} is the static conductivity and τ\tau is the relaxation time.

5.1 Microwave regime

At microwave frequencies, ω1/τ\omega\ll 1/\tau and ϵ(ω)4πσ0i/ω\epsilon(\omega)\simeq 4\pi\sigma_{0}i/\omega. The penetration depth of electric field into the metal is characterized by the skin depth (λ0/2π)(ω/2πσ0)1/2\sim(\lambda_{0}/2\pi)\,(\omega/2\pi\sigma_{0})^{1/2}. Common metals like silver, aluminum, and copper have low loss and large conductivity at microwave frequencies, and their skin depth is much shorter than the wavelength. For example, at 2020 GHz where the wavelength is 1.51.5 cm, the skin depth is less than 1μ1\ \mu\citesupp2017_Yi_Plasmonics_book.

To simulate microwave transport in 3D aggregates of metallic spheres, we generate random arrangements of overlapping spheres using the same procedure as for the PEC systems. The sphere diameter of 0.560.56 cm is four orders of magnitude larger than the skin depth of crystalline metals like silver, aluminum, copper. Thus the microwave barely penetrates into the metallic scatterers, and the absorption loss is negligible. When we use the conductivity σ0=3.8×107\sigma_{0}=3.8\times 10^{7} Ω1/m{\rm\Omega^{-1}/m} of crystalline aluminum reported in literature \citesupp2017_Yi_Plasmonics_book, the simulation results barely deviate from those for PEC.

However, experimentally fabricated metallic structures have additional loss due to polycrystallinity, surface defects, oxide layers, etc. To take these into account, we lower the conductivity σ0\sigma_{0} so that the simulated transport properties match the experimental values in Ref.  (?). Specifically, we simulate dynamic transmittance in a diffusive slab of aluminum spheres with same volume fraction f=35%f=35\% and slab thickness LL = 6 cm as in the experiment. When the conductivity is reduced to σ0=3.8×104\sigma_{0}=3.8\times 10^{4} Ω1/m{\rm\Omega^{-1}/m}, our simulated diffusion coefficient D=1.9×109D=1.9\times 10^{9} cm2/s and absorption coefficient α=(Dτa)10.2\alpha=(D\tau_{a})^{-1}\simeq 0.2 cm-1 both agree to the experimental values at 20 GHz. Using these realistic parameters, we simulate 3D metallic composites with high volume fraction of f=60%f=60\%. As shown in Fig. S11a, the apparent diffusion coefficient, obtained from the temporal decay of the transmittance without taking absorption into account, decreases in time as 1/t1/t, similarly to its behavior in PEC, until it reaches the value set by the absorption. The simulated field intensity distribution inside the system, in Fig. S11b, provides evidence of spatial confinement of microwave, similar to the result for PEC in Fig. 2e. The most conclusive evidence of AL is the arrest of transverse spreading of transmitted wave field. It is insensitive to absorption and is shown in the main text in Fig. 4e.

We believe the tell-tale experimental sign of AL is the arrest of transverse spreading of transmitted wave with a focused incident pulse. The potential pitfalls are background signals or possible emission by the metal upon microwave excitation. However, these signals are typically broadband and incoherent with the incident wave. If the incident microwave has a narrow spectral band, the transmitted field may be measured coherently, e.g., using the homodyne technique common for microwaves, and those background and incoherent signals will be discarded. Hence, we propose an experiment with a frequency-tunable narrowband microwave source: focus the incident microwave to the front surface of a slab and scan the frequency, perform an interferometric measurement of transmitted field distribution near the slab back surface at each frequency (using a local oscillator), finally Fourier transform the spectral fields to reconstruct the temporal evolution of transmitted field for an incident short pulse in order to observe the arrest of transverse spreading.

5.2 Optical regime

Here we investigate the possibility of AL of visible light in 3D metallic nanostructures. Even for low-loss metals like gold and silver, the skin depth is 25\sim 25 nm at λ=650\lambda=650 nm \citesupp2017_Yi_Plasmonics_book, comparable to the nanoparticle diameter of 100–200 nm. A significant penetration of light field inside the metal particles makes them deviate from the PEC, which expels the fields completely. Another consequence of the penetration is a notable loss. We simulate silver, which is widely used in nano-plasmonics and meta-materials, using realistic parameters reported in the literature. We adopt the Drude model of ϵ(ω)\epsilon(\omega) with σ06.1×107\sigma_{0}\simeq 6.1\times 10^{7} Ω1/m{\rm\Omega^{-1}/m} and τ3.7×1014\tau\simeq 3.7\times 10^{-14} s from Ref. \citesupp1985_Ordal_Drude_model_parameters. Despite absorption and deviation from PEC, we still observe the arrest of transverse spreading in Fig. S12.

Compared to 2D nanostructures, 3D nanoporous metals have a much larger (internal) surface area, leading to a wide range of applications in photo-catalysis \citesupplinic2011plasmonic, optical sensing \citesuppchen2009nanoporous, energy conversion and storage \citesuppmascaretti2019plasmon. Metallic nanostructures have been widely explored to enhance Raman scattering, second-harmonic generation, etc., because they can produce ‘hot spots’ (giant local fields) to boost optical nonlinearities. Also metallic nanoparticles have been used for random lasing, as their strong scattering of light improves optical feedback \citesuppwang2017nanolasers, gomes2021recent. Our simulation results suggest the possibility of AL in 3D metallic nanostructures at optical frequencies. Light localization in such structures will have a significant impact on optical nonlinear, lasing, photochemical processes and related applications.

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Figure S1: Confirmation of the absence of Anderson localization in random dielectric media with refractive-index contrast of 3.53.5 with increased numerical resolution. Transmittance T(t)T(t) of an optical pulse through a 3D slab of thickness L=3.3L=3.3 μ\mum, filled with dielectric spheres at random uncorrelated positions (radius r=100r=100 nm, refractive index n=3.5n=3.5, volume filling fraction f=38%f=38\%) in air. Numerical simulation is performed with the spatio-temporal discretization corresponding to λ0/40\lambda_{0}/40, which is twice finer than that used to produce Fig. 1e in the main text. Pure exponential decay of T(t)T(t) in time, over 12 orders of magnitude, is a hallmark of diffusive transport in the dielectric random system.
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Figure S2: Robustness of the arrest of transverse spreading of transmitted beam in localized PEC systems against numerical discretization. The simulation is schematically depicted in Fig. 4a of the main text, and the structure parameters (sphere radius r=50r=50 nm, volume filling fraction f=48%f=48\%) are identical to those in Fig. 4d. a, Transverse diameter of the transmitted beam d(t)d(t), obtained from numerical simulation (slab thickness L=1.3L=1.3 μ\mum) with λ0/40\lambda_{0}/40 resolution, exhibits a saturation consistent with the result with λ0/20\lambda_{0}/20 resolution in Fig. 4d. b, Arrest of the transverse spreading is observed in all simulations performed with numerical resolution from λ0/10\lambda_{0}/10 to λ0/40\lambda_{0}/40 with a consistent asymptotic transverse beam diameter dd_{\infty}. Symbols and error-bars represent the mean value and standard deviation of d(t)d(t) in the time interval 11 ps <t<2<t<2 ps (gray area in panel a).
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Figure S3: Spatial correlation in PEC composites. Normalized spatial correlation function C(Δ)/C(0)C(\Delta)/C(0) for random aggregates of overlapping spheres with radii r=50r=50 nm, 100100 nm and volume filling fractions f15%,50%f\simeq 15\%,50\%. Spatial correlation vanishes beyond one sphere diameter 2r2r.
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Figure S4: Extinction of coherent field in a dielectric slab of n=3.5n=3.5 spheres. a, Scattering cross section of a single dielectric sphere of radius r=100r=100 nm and refractive index n=3.5n=3.5 in air. The spectral peaks correspond to Mie resonances. b,c,d,e, amplitude (b), phase (c), real (d) and imaginary (e) parts of coherent field Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x} versus depth zz and wavelength λ\lambda for dielectric filling fraction f=29%f=29\%. White lines represent z=mλeffz=m\lambda_{\text{eff}}, where mm is an integer and λeff=λ0/neff\lambda_{\text{eff}}=\lambda_{0}/n_{\text{eff}}. The coherent field amplitude experiences an enhanced extinction in the wavelength range 500–700 nm due to hybridized Mie resonances.
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Figure S5: Extinction of coherent field in a dielectric slab of n=10n=10 spheres. a, Scattering cross section of a single dielectric sphere of radius r=32r=32 nm and refractive index n=10n=10 in air. The peak represents the first Mie resonance. b,c,d,e, amplitude (b), phase (c), real (d) and imaginary (e) parts of coherent field Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x} versus depth zz and wavelength λ\lambda for dielectric filling fraction f=29%f=29\%. White lines represent z=mλeffz=m\lambda_{\text{eff}}, where mm is an integer and λeff=λ0/neff\lambda_{\text{eff}}=\lambda_{0}/n_{\text{eff}}. The coherent field amplitude experiences an enhanced extinction in the spectral range 630–660 nm in the vicinity of the first Mie resonance.
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Figure S6: Comparison of coherent fields in diffusive and localized slabs of PEC spheres. Amplitude (a,e), phase (b,f), real (c,g) and imaginary (d,h) parts of coherent field Ex(x,y0,z;λ)x\langle E_{x}(x,y_{0},z;\lambda)\rangle_{x} versus depth zz and wavelength λ\lambda for PEC filling fraction f=15%f=15\% (a,b,c,d) and 48%48\% (e,f,g,h). White lines represent z=mλz=m\lambda, where mm is an integer. In the localized slab (f=48%f=48\%), extinction of coherent field is much stronger and nearly independent of wavelength.
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Figure S7: Resonant scattering and diffusion in random ensembles of n=10n=10 dielectric spheres. a, Scattering cross section of a single dielectric sphere of radius r=32r=32 nm and refractive index n=10n=10. The vertical dotted lines mark spectral width of the excitation pulse in panel e. b, Resonantly enhanced scattering mean free path s\ell_{s} in the spectral vicinity of the first Mie resonance of single-particle scattering. The dielectric filling fraction f=2.5%f=2.5\% (blue), f=5%f=5\% (red), 9%9\% (green) and 18%18\% (brown). The minimum Ioffe-Regel parameter keffs2k_{\text{eff}}\,\ell_{s}\sim 2. The horizontal dashed line marks the Ioffe-Regel criterion keffs=1k_{\text{eff}}\,\ell_{s}=1 for 3D localization. c, Normalized transport mean free path kefftk_{\text{eff}}\,\ell_{t} in the spectral vicinity of the first Mie resonance, reflecting saturation by dependent scattering between f=2.5%f=2.5\% and 18%18\%. d, CW transmittance T(λ)T(\lambda) for three slab thicknesses L/λ0=1,2,4L/\lambda_{0}=1,2,4 (solid, dashed, and dotted lines). T(λ)T(\lambda) multiplied by L/λ0L/\lambda_{0} remains nearly independent of LL at wavelengths around minimum transmission, reflecting the diffusive scaling of T1/LT\propto 1/L. Results are color-coded as in panels b,c. For f=5%f=5\%, 9% and 18%, the curves are shifted up vertically by one, two and three decades for legibility. e, Transmittance of 3D slabs with thickness L=2×λ0L=2\times\lambda_{0} for pulsed excitation, showing an exponential decay (dashed lines) in time at long delay. The decay rate is determined by the minimum diffusion coefficient within the pulse bandwidth. Legend shows values of L/tL/\ell_{t} in each system. For f=5%f=5\%, 9% and 18%, the curves are shifted down vertically by two, four and six decades for legibility.
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Figure S8: Spatial intensity distribution inside disordered PEC system. Field intensity at a (y,z)(y,z) cross-section inside a random ensemble of PEC spheres with radius r=50r=50 nm. PEC filling fraction is f=8%f=8\% in panels a,b and f=15%f=15\% in panels c,d. λ=650\lambda=650 nm in panels a,c and 1080 nm in panels b,d. Bottom row shows a magnified view of each distribution in the top row, revealing strong intensity enhancement in air voids between PEC particles due to coupled resonances. The size of the voids can be much smaller than wavelength λ\lambda indicated by the white scale bar.
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Figure S9: Additional evidence for Anderson localization in disordered PEC. a, Depth profile I(x,y,z;t)x,y\langle I(x,y,z;t\rightarrow\infty)\rangle_{x,y} inside the PEC slab of f=15%f=15\% (blue solid line) and 48%48\% (red solid line). The lowest-order diffusive mode profile (black dashed line) matches that of f=15%f=15\% (blue). b, Normalized variance of cross-section integrated intensity, showing two orders of magnitude enhancement of intensity fluctuations for f=48%f=48\% over f=15%f=15\%. c,d, CW intensity depth profiles I(z,λ)λ\langle I(z,\lambda)\rangle_{\lambda} (solid lines) and exp[log[I(z,λ)]λ]\exp[\langle\log[I(z,\lambda)]\rangle_{\lambda}] (dashed lines), compared to linear decay for f=15%f=15\% and exponential decay for f=48%f=48\% (black dashed lines).
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Figure S10: Diffusion-localization transition in another PEC system with larger spheres. The scaling behavior reported in Fig. 3b,c is reproduced for a system of larger PEC spheres with radius r=100r=100 nm, despite the diffusion-localization transition occurs at a different volume filling fraction ff of PEC spheres. In a, blue dashed line denotes diffusive scaling TL1T\propto L^{-1}; red dashed line marks ks=1k\ell_{s}=1. In b, blue and red dashed lines denote diffusive and localized scaling gLg\propto L and gexp(L/ξ)g\propto\exp(-L/\xi) respectively, where ξ\xi is the localization length.
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Figure S11: Localization of microwaves in a 3D real-metal composite. A random aggregate of aluminum spheres with radius r=0.28r=0.28 cm, realistic conductivity σ0=3.8×104\sigma_{0}=3.8\times 10^{4} Ω1/m{\rm\Omega^{-1}/m}, and volume filling fraction f=60%f=60\% localizes microwave of frequency around 2020 GHz in a slab of thickness LL = 6 cm. a, Time-resolved apparent diffusion coefficient D(t)D(t), extracted from the temporal decay rate of T(t)T(t), decreases as 1/t1/t, due to Anderson localization. Eventually it saturates to the value set by metal absorption. b, Wavelength-resolved transmittance T(λ)T(\lambda) (red line) exhibits fluctuations. Color map: depth profile of average intensity I(x,y0,z;λ)x\langle I(x,y_{0},z;\lambda)\rangle_{x} inside the slab at different wavelengths, highlighting spatially localized and necklace-like states.
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Figure S12: Arrest of transverse spreading of visible light in 3D random aggregates of silver particles. Transverse diameter of the transmitted light d(t)d(t), with a tightly-focused incident pulse of center wavelength λ0=650\lambda_{0}=650 nm, increases as t\sqrt{t} in the diffusive slab (f=15%f=15\%, blue dots), but it saturates to a constant value in the localized slab (f=48%f=48\%, red dots). The slab thickness LL = 2 μ\mum. Silver spheres have radius rr = 50 nm, σ06.1×107\sigma_{0}\simeq 6.1\times 10^{7} Ω1/m{\rm\Omega^{-1}/m} and τ3.7×1014\tau\simeq 3.7\times 10^{-14} s.