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Steady state in a gas of inelastic rough spheres heated by a uniform stochastic force

Francisco Vega Reyes fvega@unex.es http://www.unex.es/eweb/fisteor/fran/fvega.html    Andrés Santos andres@unex.es http://www.unex.es/eweb/fisteor/andres/Cvitae/ Departamento de Física and Instituto de Computación Científica Avanzada (ICCAEx), Universidad de Extremadura, 06071 Badajoz, Spain
(July 26, 2025)
Abstract

We study here the steady state attained in a granular gas of inelastic rough spheres that is subject to a spatially uniform random volume force. The stochastic force has the form of the so-called white noise and acts by adding impulse to the particle translational velocities. We work out an analytical solution of the corresponding velocity distribution function from a Sonine polynomial expansion that displays energy non-equipartition between the translational and rotational modes, translational and rotational kurtoses, and translational-rotational velocity correlations. By comparison with a numerical solution of the Boltzmann kinetic equation (by means of the Direct Simulation Monte Carlo method) we show that our analytical solution provides a good description that is quantitatively very accurate in certain ranges of inelasticity and roughness. We also find three important features that make the forced granular gas steady state very different from the homogeneous cooling state (attained by an unforced granular gas). First, the marginal velocity distributions are always close to a Maxwellian. Second, there is a continuous transition to the purely smooth limit (where the effects of particle rotations are ignored). And third, the angular translational-rotational velocity correlations show a preference for a quasiperpendicular mutual orientation (which is called “lifted-tennis-ball” behavior).

I Introduction

Systems composed of a large number of particles with a characteristic length bigger than about 1μm1~\mu\mathrm{m} (granular systems) are ubiquitous in naturede Gennes (1999); Bagnold (1954) and applications.Jaeger, Nagel, and Behringer (1996) Therefore, the study of the transport processes in this kind of systems (generically called granular matter) has been of interest and subject of systematic study for a long time (see, for instance, the work by ReynoldsReynolds (1885)). The most generic property of granular matter is the non-conservation of kinetic energy after contact between particles, and hence the term inelastic particles.de Gennes (1999); Jaeger, Nagel, and Behringer (1996)

Attending to the nature of the mechanical interaction among grains, granular matter may be classified into two groups: wet granular matter (grains tend to stick together after contact and they are usually called cohesive powders, since they usually predominate in the smaller range of grain sizesCastellanos et al. (1999)) and dry granular matter (grains do no not show this sticky behavior). Of course, both types of granular systems are equally relevant in industry and technology.de Gennes (1999); Rajchenbach (1990); Jaeger, Nagel, and Behringer (1996); Goldhirsch (2003) Moreover, the finding of a meaningful theoretical description also poses fundamental challenges for researchers of a number of fields.de Gennes (1999) Since the nature of particle contacts essentially determines the granular dynamics, theoretical developments frequently study granular systems as composed by only dry or only wet particles (or, at its most elaborate, simple combinations of both).

Let us focus on dry granular matter. Here, we can find persistent contacts as well, but they are always due to a high fraction of the volume occupied by grains. When this happens, available space limitations result in lasting contacts. As a consequence, mechanical force transmission throughout the system occurs;Majmudar and Behringer (2005); Goldenberg and Goldhirsch (2005) i.e., one particle may be in contact with not just one another particle but a set of them, thus propagating mechanical information to large parts of the system.Banigan et al. (2013) Correlations in this case are obviously strong, much in the same way as in atomic solid matter.Goldenberg and Goldhirsch (2005) On the contrary, in less dense systems, particles are less correlated and contacts among three or more grains tend to be statistically rare events; i.e., contacts typically become only binary.Goldhirsch (2003) At the same time, in the low density regime, those contacts between pairs of dry grains tend to be very short in time (as compared with the characteristic mean free time), and hence the term inelastic collision.Brilliantov and Pöschel (2004) Binary and instantaneous collisions are also characteristic features of low density molecular gases, for which the so-called molecular chaos assumption (Stosszahlansatz) is commonly used;Chapman and Cowling (1970); Brey, Dufty, and Santos (1997) i.e., colliding particle velocities are supposed to be uncorrelated. In those circumstances, the Boltzmann equation or, at low but finite density, the Enskog equation (properly modified in order to take into account inelasticity in the collisionsBrilliantov and Pöschel (2004); Brey, Dufty, and Santos (1997)) applies. While inelastic collisions may originate velocity correlations,Soto and Mareschal (2001) these effects tend to be more important at higher densitiesPrevost, Egolf, and Urbach (2002) and thus they can usually be ignored for low densities.Goldhirsch (2003); Brey et al. (1998); Brilliantov and Pöschel (2004) Since the theoretical approach to both the high and low density limits for granular matter is radically differentde Gennes (1999) (actually, just in the same way as it is for conventional matterChaikin and Lubensky (2000)), it is convenient to focus on just one density regime. In this case we are interested in the low density limit, the so-called granular gases.Dufty (2001)

Given that most granular particles do not have a regular shape and differ in size and mass,Garzó, Dufty, and Hrenya (2007) granular collisions (even if short in time) can be very complex events.Cercignani (2000); Kuninaka and Hayakawa (2004) It is thus important that granular collision models can accordingly capture as many features as possible, without otherwise compromising their tractability. For instance, the coefficient of normal restitution (that characterizes translational kinetic energy loss upon collisions) depends in general on the impact velocityBrilliantov and Pöschel (2004); Kuninaka and Hayakawa (2004) (a viscoelastic collision model may be used to take this into accountN. Brilliantov and Pöschel (2004)). Nevertheless, it has been found that an important set of the main features at a macroscopic level (i.e., average field behavior) can be described with models that ignore the effects of impact velocity on the restitution properties.Goldhirsch (2003) In an effort to simplify the collision process, one can sequentially describe it as (i) an impact between both colliding particles, after which they suffer a mechanical impulse that produces a linear momentum transfer; (ii) a friction process, tangent to the contact interface, generating an angular momentum transfer; and (iii) a sliding process, that describes the relative translational displacement of the colliding particles in the direction of the contact interface. All these three features were captured in previous research, that includes experimental work (see for instance Ref. Foerster et al., 1994), by using a collision model based on three collisional constant parameters: a coefficient of normal restitution, a coefficient of tangential restitution, and a friction coefficient.

In spite of the intrinsic polydispersity of granular systems in nature,Bagnold (1954) a variety of generic granular dynamics phenomena can be described by means of kinetic theory for a monodisperse granular gas. In a granular gas of identical particles, the relevance of collision models based on constant coefficients of restitution is exemplified by the correct description that the simple inelastic smooth hard-sphere model gives of the clustering instability of the so-called homogeneous cooling state (HCS), i.e., an unforced state with uniform hydrodynamic quantities and a time decaying granular temperature.Goldhirsch and Zanetti (1993); Louge (2014); Mitrano et al. (2014) Furthermore, simplifications of the collision model alleviate the involved mathematical task of integrating the Boltzmann equation, especially for states more complex than the HCS.Vega Reyes and Urbach (2009); Vega Reyes, Santos, and Garzó (2010) In turn, solutions of the Boltzmann equation have allowed for finding new fundamental properties of granular gas dynamics by means of consistent derivations of the corresponding hydrodynamic theories.Dufty (2001) Another important example of this is the inelastic rough hard-sphere model, that is able to detect correlations between the angular and translational velocity components in granular gases.Brilliantov et al. (2007); Rongali and Alam (2014) Therefore, it is fruitful to compromise between simple collision models and more sophisticated theoretical developments at a kinetic theory level, in order to discover new fundamental transport properties of granular gases.

In its basic implementation, the rough hard-sphere model neglects the effects of eventual sliding in collisions but is capable of showing a number of relevant results for the dynamics of granular gases. For instance, it has shown that energy non-equipartition between translational and rotational modes occurs,Luding et al. (1998); Santos, Kremer, and Garzó (2010); Santos (2011) and that the distribution function of particle velocities can exhibit strong non-Maxwellian effects.Goldhirsch, Noskowicz, and Bar-Lev (2005); Santos, Kremer, and dos Santos (2011); Vega Reyes, Santos, and Kremer (2014) It has also been determined that strong inelasticity or angular-translational correlations do not necessarily lead to difficulties for reaching a normal (or hydrodynamic) state. Vega Reyes, Santos, and Kremer (2014) This observation has important consequences for the development of hydrodynamic theories for granular gases.Goldhirsch (2003); Kremer, Santos, and Garzó (2014). However, most of these works addressed only the HCS. Useful and fundamental as this state may be as a reference for transport theories of granular gases,Goldhirsch, Noskowicz, and Bar-Lev (2005); Kremer, Santos, and Garzó (2014) it is hard to observe its spontaneous appearance in nature and also difficult to reproduce in laboratory experiments. In fact, granular gases are most frequently observed under a forcing that keeps the system steadily fluidized and at low density.

In this paper, we study the homogeneous steady state of a granular gas of rough spheres excited by a stochastic volume force that is modeled by means of the so-called white noise,Williams (1996); Williams and MacKintosh (1996); Swift et al. (1998); van Noije and Ernst (1998); Montanero and Santos (2000); Bobylev and Cercignani (2002) as usually named in statistical physics. We extend previous theoretical resultsSantos, Kremer, and dos Santos (2011) by taking into account the effects of orientational correlations in particle velocities and, in addition, by comparing the theoretical predictions with computer simulations. As we will see, even though the velocity kurtoses and correlations are still not negligible, the heated granular gas has a more Maxwellian-like distribution function for all values of the roughness parameter than the HCS.Vega Reyes, Santos, and Kremer (2014); Rongali and Alam (2014) This justifies the practical validity of our theoretical perturbation approach (truncated Sonine expansion) and its excellent agreement with simulation data. In contrast, the HCS is characterized by large deviations from the Maxwellian distribution for small roughness (especially in what concerns the angular velocity), in which case the perturbation method is valid only semi-quantitatively.Vega Reyes, Santos, and Kremer (2014) Moreover, no singularity exists in the smooth-sphere limit for the heated gas, again in contrast to what happens in the HCS.

Another important and distinctive feature that we will find is that the forced granular gas shows an average preference for quasiperpendicular relative orientation of translational and rotational particle velocities, in contrast to the behavior found in the unforced granular gas,Brilliantov et al. (2007); Kranz et al. (2009); Rongali and Alam (2014); Vega Reyes, Santos, and Kremer (2014) where quasiparallel translational and rotational particle velocities are also present. This result is of interest for a number of experimental works, where the most common situation is that of an excited granular gas (see, for instance, Ref. Losert et al., 2000).

The structure of this work is as follows. In Sec. II we write the corresponding kinetic (Boltzmann) equation. By defining adequate time and velocity units, we also derive the dimensionless counterparts of the Boltzmann equation and its derived moment equations, which are the ones we will work with. In Sec. III, a theoretical solution to the moment equations, by means of a Sonine polynomial expansion around the Maxwellian distribution function, is derived by keeping terms up to order two (fourth-degree polynomials). In this way, the state of the system is solved at all times, including the final steady state. In particular, the theoretical parameters characterizing kurtoses, correlations, and average relative orientation of translational and rotational particle velocities are analyzed. As said before, we will find that excited rough grains do not show the relevance of quasiparallel relative orientation behavior present in the HCS.Brilliantov et al. (2007); Vega Reyes, Santos, and Kremer (2014) Next, in Sec. IV we compare the theoretical results with an “exact” numerical solution of the Boltzmann equation obtained by means of the Direct Simulation Monte Carlo (DSMC) method,Bird (1994) a very good agreement being observed. Finally, the results are briefly discussed in Sec. V.

II Boltzmann equation and moment hierarchy

II.1 Collision rules

Let us consider a homogeneous dilute granular gas of identical hard spheres with mass mm, diameter σ\sigma, and moment of inertia II, subject to a stochastic volume force 𝐅wn\mathbf{F}^{\text{wn}} (also called thermostat) with the properties of a Gaussian white noise.Williams and MacKintosh (1996); Williams (1996); Swift et al. (1998); van Noije and Ernst (1998); Montanero and Santos (2000); Gradenigo et al. (2011) This kind of forcing can model, for example, the energy input to grains immersed in a gas in turbulent flow.Ojha1 et al. (2004)

We denote the translational and angular (or rotational) particle velocities with 𝐯\mathbf{v} and 𝝎\bm{\omega} respectively. Binary collisions are characterized here by two material parameters, namely the coefficient of normal restitution α\alpha and the coefficient of tangential restitution β\beta, which determine the shrinking of the normal and tangential component, respectively, of the relative velocity of the two surface points at contact. They are defined by (see, for instance, Refs. Kremer, 2010; S, 10; Kremer, Santos, and Garzó, 2014)

𝝈^𝐮=α(𝝈^𝐮),𝝈^×𝐮=β(𝝈^×𝐮).\widehat{\bm{\sigma}}\cdot\mathbf{u}^{\prime}=-\alpha(\widehat{\bm{\sigma}}\cdot\mathbf{u}),\quad\widehat{\bm{\sigma}}\times\mathbf{u}^{\prime}=-\beta(\widehat{\bm{\sigma}}\times\mathbf{u}). (1)

Here, the primes denote post-collisional values, 𝝈^\widehat{\bm{\sigma}} is the unit collision vector joining the centers of the two colliding spheres (and pointing from the center of particle 1 to the center of particle 2), and

𝐮=𝐯1𝐯2σ2𝝈^×(𝝎1+𝝎2){\mathbf{u}=\mathbf{v}_{1}-\mathbf{v}_{2}-{\frac{\sigma}{2}}\widehat{\bm{\sigma}}\times(\bm{\omega}_{1}+\bm{\omega}_{2})} (2)

is the relative velocity of the points of the spheres which are in contact during a binary encounter.

The coefficient of normal restitution α\alpha takes values between 0 (completely inelastic collision) and 11 (completely elastic collision), while the coefficient of tangential restitution takes values between 1-1 (completely smooth collision, implying that rotational velocities are unchanged) and 11 (completely rough collision).Chapman and Cowling (1970); Kremer (2010) Equation (1) supplements the linear and angular momentum conservation laws to yield the collision rules,Kremer (2010); Santos, Kremer, and dos Santos (2011); Brilliantov and Pöschel (2004); Kremer, Santos, and Garzó (2014)

m𝐯1,2=m𝐯1,2𝐐,I𝝎1,2=I𝝎1,2σ2𝝈^×𝐐,{m\mathbf{v}_{1,2}^{\prime}=m\mathbf{v}_{1,2}\mp\mathbf{Q},\quad I\bm{\omega}_{1,2}^{\prime}=I\bm{\omega}_{1,2}-{\frac{\sigma}{2}}\widehat{\bm{\sigma}}\times\mathbf{Q},} (3)

where the impulse exerted by particle 1 on particle 2 is given by

𝐐=mα~(𝝈^𝐮)𝝈^mβ~𝝈^×(𝝈^×𝐮).{\mathbf{Q}={m\widetilde{\alpha}}(\widehat{\bm{\sigma}}\cdot\mathbf{u})\widehat{\bm{\sigma}}-m\widetilde{\beta}\widehat{\bm{\sigma}}\times(\widehat{\bm{\sigma}}\times\mathbf{u}).} (4)

Here, we have introduced the abbreviations

α~1+α2,β~1+β2κκ+1,κ4Imσ2.{\widetilde{\alpha}\equiv{\frac{1+\alpha}{2}},\quad\widetilde{\beta}\equiv{\frac{1+\beta}{2}}{\frac{\kappa}{\kappa+1}},\quad\kappa\equiv{\frac{4I}{m\sigma^{2}}}.} (5)

While collisions (except if α=1\alpha=1 and β=±1\beta=\pm 1) dissipate kinetic energy (translational plus rotational), the homogeneous stochastic force 𝐅wn\mathbf{F}^{\text{wn}} injects translational kinetic energy to grains. It has properties of a Gaussian white noise, i.e.,

𝐅iwn(t)=\displaystyle\langle{\bf F}_{i}^{\text{wn}}(t)\rangle= 𝟎,\displaystyle{\bf 0}, (6a)
𝐅iwn(t)𝐅jwn(t)=\displaystyle\langle{\bf F}_{i}^{\text{wn}}(t){\bf F}_{j}^{\text{wn}}(t^{\prime})\rangle= 𝖨m2χ02δijδ(tt),\displaystyle\mathsf{I}m^{2}\chi_{0}^{2}\delta_{ij}\delta(t-t^{\prime}), (6b)

where indexes i,ji,j refer to particles, 𝖨\mathsf{I} is the 3×33\times 3 unit matrix, and χ02\chi_{0}^{2} measures the characteristic strength of the stochastic force.

II.2 Boltzmann equation

In homogeneous states, the Boltzmann equation corresponding to the stochastic external force 𝐅wn\mathbf{F}^{\text{wn}} becomesvan Noije and Ernst (1998); Montanero and Santos (2000)

f(𝐯,𝝎;t)tχ022(𝐯)2f(𝐯,𝝎;t)=J[𝐯,𝝎|f(t)],\frac{\partial f(\mathbf{v},\bm{\omega};t)}{\partial t}-\frac{\chi_{0}^{2}}{2}\left(\frac{\partial}{\partial\mathbf{v}}\right)^{2}f(\mathbf{v},\bm{\omega};t)={J[\mathbf{v},\bm{\omega}|f(t)]}, (7)

where f(𝐯,𝝎;t)f(\mathbf{v},\bm{\omega};t) is the velocity distribution function and J[𝐯,𝝎|f]J[\mathbf{v},\bm{\omega}|f] is the collision integral in the (inelastic) Boltzmann equation for rough spheres, which accounts for the collision rules (3) and (4).

Given a certain function A(𝐯,𝝎)A(\mathbf{v},\bm{\omega}), we define its average as

A(t)=1n𝑑𝐯𝑑𝝎A(𝐯,𝝎)f(𝐯,𝝎;t),n=𝑑𝐯𝑑𝝎f(𝐯,𝝎;t),\langle A(t)\rangle=\frac{1}{n}\int d\mathbf{v}\int d\bm{\omega}\,A(\mathbf{v},\bm{\omega})f(\mathbf{v},\bm{\omega};t),\quad n=\int d\mathbf{v}\int d\bm{\omega}\,f(\mathbf{v},\bm{\omega};t), (8)

where nn is the number density. By Galilean invariance, we choose 𝐯=𝟎\langle\mathbf{v}\rangle=\mathbf{0}. Moreover, we assume isotropic states, so that 𝝎=𝟎\langle\bm{\omega}\rangle=\mathbf{0}.Kremer, Santos, and Garzó (2014) Thus, the basic quantities are the translational (TtT_{t}), rotational (TrT_{r}), and total (TT) granular temperatures:

Tt=m3v2,Tr=I3ω2,T=Tt+Tr2=Tt1+θ2.{T_{t}={\frac{m}{3}}\langle v^{2}\rangle,\quad T_{r}={\frac{I}{3}}\langle\omega^{2}\rangle,\quad\quad T=\frac{T_{t}+T_{r}}{2}=T_{t}\frac{1+\theta}{2}.} (9)

where the temperature ratio θTr/Tt\theta\equiv T_{r}/T_{t} is an important quantity in this system because, as we will see, its steady-state value is independent of the level of forcing (χ02\chi_{0}^{2}).

The evolution equations for the granular temperatures TtT_{t} and TrT_{r} are obtained by just multiplying both sides of Eq. (7) by the particle translational and rotational kinetic energies, respectively, and integrating over all velocity values. This gives

tTtmχ02=ξtTt,tTr=ξrTr,tTmχ022=ζT\partial_{t}T_{t}-{m\chi_{0}^{2}}=-\xi_{t}T_{t},\quad{\partial_{t}T_{r}=-\xi_{r}T_{r}},\quad\partial_{t}T-\frac{m\chi_{0}^{2}}{2}=-\zeta T (10)

Here, the translational (ξt\xi_{t}) and rotational (ξr\xi_{r}) production rates and the cooling rate (ζ\zeta) are defined by the collision integralsSantos, Kremer, and dos Santos (2011); Kremer, Santos, and Garzó (2014)

ξt=m3nTt𝑑𝐯𝑑𝝎v2J[𝐯,𝝎|f],ξr=I3nTr𝑑𝐯𝑑𝝎ω2J[𝐯,𝝎|f],\displaystyle\xi_{t}=-{\frac{m}{3nT_{t}}}\int d\mathbf{v}\int d\bm{\omega}\,v^{2}{J[\mathbf{v},\bm{\omega}|f]},\quad\xi_{r}=-{\frac{I}{3nT_{r}}}\int d\mathbf{v}\int d\bm{\omega}\,\omega^{2}{J[\mathbf{v},\bm{\omega}|f]}, (11a)
ζ=ξtTt+ξrTr2T=ξt+ξrθ1+θ.\displaystyle\zeta=\frac{\xi_{t}T_{t}+\xi_{r}T_{r}}{2T}=\frac{\xi_{t}+\xi_{r}{\theta}}{1+\theta}. (11b)

II.3 Reduced variables and velocity moments

For convenience, let us rewrite the Boltzmann equation (7) in dimensionless form. For this, we first define the reduced velocity distribution function

ϕ(𝐜,𝐰;τ)1n(4Tt(t)Tr(t)mI)3/2f(𝐯,𝝎;t),\phi(\mathbf{c},\mathbf{w};\tau)\equiv\frac{1}{n}\left(\frac{4T_{t}(t)T_{r}(t)}{mI}\right)^{3/2}f(\mathbf{v},\bm{\omega};t), (12)

where the reduced particle velocities are

𝐜(t)𝐯2Tt(t)/m,𝐰(t)𝝎2Tr(t)/I.\mathbf{c}(t)\equiv\frac{\mathbf{v}}{\sqrt{2T_{t}(t)/m}},\quad\mathbf{w}(t)\equiv\frac{\bm{\omega}}{\sqrt{2T_{r}(t)/I}}. (13)

In addition, time is measured by the parameter τ\tau defined by

τ(t)=0t𝑑tν(t),ν(t)=2nσ2πTt(t)/m,{\tau(t)=\int_{0}^{t}dt^{\prime}\,\nu(t^{\prime}),\quad\nu(t)=2n\sigma^{2}\sqrt{\pi T_{t}(t)/m},} (14)

where ν(t)\nu(t) is the (time-dependent) collision frequency. Thus, τ(t)\tau(t) measures the accumulated number of collisions per particle up to time tt. With this time scale, we can measure relaxation times to the steady state that are physically meaningful, since they coincide with the aging times to hydrodynamics.Vega Reyes, Santos, and Kremer (2014)

The moments of the reduced distribution function ϕ(𝐜,𝐰;τ)\phi(\mathbf{c},\mathbf{w};\tau) are

Mpq(r)(τ)cpwq(𝐜𝐰)r=𝑑𝐜𝑑𝐰cpwq(𝐜𝐰)rϕ(𝐜,𝐰;τ),M_{pq}^{(r)}(\tau)\equiv\langle c^{p}w^{q}(\mathbf{c}\cdot\mathbf{w})^{r}\rangle=\int d\mathbf{c}\int d\mathbf{w}\,c^{p}w^{q}(\mathbf{c}\cdot\mathbf{w})^{r}\phi(\mathbf{c},\mathbf{w};\tau), (15)

with p,q,r=evenp,q,r=\text{even}, by symmetry. Note that Mpq(r)M_{pq}^{(r)} is a moment of degree p+q+2rp+q+2r and M0,0(0)=1M_{0,0}^{(0)}=1, M2,0(0)=M0,2(0)=32M_{2,0}^{(0)}=M_{0,2}^{(0)}=\frac{3}{2}. The dimensionless measure of the noise intensity is defined by

γ(τ)32χ02ν(t)Tt(t)/m=3χ024πnσ2[Tt(t)/m]3/2.\gamma(\tau)\equiv\frac{3}{2}\frac{\chi_{0}^{2}}{\nu(t)T_{t}(t)/m}=\frac{3\chi_{0}^{2}}{4\sqrt{\pi}n\sigma^{2}[T_{t}(t)/m]^{3/2}}. (16)

Notice that, although χ02\chi_{0}^{2} is a constant, its dimensionless counterpart γ\gamma is time-dependent due to the scaling with the temperature TtT_{t}. Of course, once a steady state is reached, γ\gamma becomes constant too. Note also that γ2/3\gamma^{-2/3} can be seen as the translational temperature TtT_{t} in units of a reference temperature Tref=m(3χ02/4πnσ2)2/3T_{\text{ref}}=m(3\chi_{0}^{2}/4\sqrt{\pi}n\sigma^{2})^{2/3} defined from the white noise parameter χ02\chi_{0}^{2}.

Let us finally define the reduced collisional moments

μpq(r)(τ)𝑑𝐜𝑑𝐰cpwq(𝐜𝐰)r𝒥[𝐜,𝐰|ϕ(τ)],\mu_{pq}^{(r)}(\tau)\equiv-\int d\mathbf{c}\int d\mathbf{w}\,c^{p}w^{q}(\mathbf{c}\cdot\mathbf{w})^{r}{\mathcal{J}[\mathbf{c},\mathbf{w}|\phi(\tau)]}, (17)

where

𝒥[𝐜,𝐰|ϕ(τ)]=1nν(t)[4Tt(t)Tr(t)mI]3/2J[𝐯,𝝎|f(t)]\mathcal{J}[\mathbf{c},\mathbf{w}|\phi(\tau)]=\frac{1}{n\nu(t)}\left[\frac{4T_{t}(t)T_{r}(t)}{mI}\right]^{3/2}J[\mathbf{v},\bm{\omega}|f(t)] (18)

is the dimensionless form of the collision integral. From the definitions (11a) and (17), it is easy to see that ξt=23νμ20(0)\xi_{t}=\frac{2}{3}\nu\mu_{20}^{(0)}, ξr=23νμ02(0)\xi_{r}=\frac{2}{3}\nu\mu_{02}^{(0)}. The evolution equations for the temperature ratio θ(τ)\theta(\tau) and the reduced noise strength γ(τ)\gamma(\tau) can be obtained from Eq. (10) as

lnθ(τ)τ=23[μ20(0)(τ)μ02(0)(τ)γ(τ)],lnγ(τ)τ=μ20(0)(τ)γ(τ).\frac{\partial\ln\theta(\tau)}{\partial\tau}=\frac{2}{3}\left[\mu_{20}^{(0)}(\tau)-\mu_{02}^{(0)}(\tau)-\gamma(\tau)\right],\quad\frac{\partial\ln\gamma(\tau)}{\partial\tau}=\mu_{20}^{(0)}(\tau)-\gamma(\tau). (19)

Note that, since 𝐯\mathbf{v} and 𝝎\bm{\omega} are scaled each with a different temperature in Eq. (13), the collision rules (3) and (4), when expressed in terms of 𝐜\mathbf{c} and 𝐰\mathbf{w}, depend parametrically on θ\theta.Santos, Kremer, and dos Santos (2011) This dependence is obviously transferred to the collisional moments (17).

Taking into account the previous dimensionless quantities, and making use again of the temperature evolution equations (10), one can obtain the dimensionless version of the Boltzmann equation (7) as

ϕ(𝐜,𝐰;τ)τ\displaystyle\frac{\partial\phi(\mathbf{c},\mathbf{w};\tau)}{\partial\tau} +μ20(0)(τ)γ(τ)3𝐜[𝐜ϕ(𝐜,𝐰;τ)]+μ02(0)(τ)3𝐰[𝐰ϕ(𝐜,𝐰;τ)]\displaystyle+\frac{\mu_{20}^{(0)}(\tau)-\gamma(\tau)}{3}\frac{\partial}{\partial\mathbf{c}}\cdot\left[\mathbf{c}\phi(\mathbf{c},\mathbf{w};\tau)\right]+\frac{\mu_{02}^{(0)}(\tau)}{3}\frac{\partial}{\partial\mathbf{w}}\cdot\left[\mathbf{w}\phi(\mathbf{c},\mathbf{w};\tau)\right]
γ(τ)6(𝐜)2ϕ(𝐜,𝐰;τ)=𝒥[𝐜,𝐰|ϕ(τ)].\displaystyle-\frac{\gamma(\tau)}{6}\left(\frac{\partial}{\partial\mathbf{c}}\right)^{2}\phi(\mathbf{c},\mathbf{w};\tau)={\mathcal{J}[\mathbf{c},\mathbf{w}|\phi(\tau)]}. (20)

Multiplying both sides by cpwq(𝐜𝐰)rc^{p}w^{q}(\mathbf{c}\cdot\mathbf{w})^{r} and integrating over 𝐜\mathbf{c} and 𝐰\mathbf{w}, we get the moment hierarchy

lnMpq(r)(τ)τ=\displaystyle\frac{\partial\ln M_{pq}^{(r)}(\tau)}{\partial\tau}= p+r3[μ20(0)(τ)γ(τ)]+q+r3μ02(0)(τ)μpq(r)(τ)Mpq(r)(τ)\displaystyle\frac{p+r}{3}\left[\mu_{20}^{(0)}(\tau)-\gamma(\tau)\right]+\frac{q+r}{3}{\mu_{02}^{(0)}}(\tau)-\frac{\mu_{pq}^{(r)}(\tau)}{M_{pq}^{(r)}(\tau)}
+γ(τ)6p(p+1+2r)Mp2,q(r)(τ)+r(r1)Mp,q+2(r2)(τ)Mpq(r)(τ).\displaystyle+\frac{\gamma(\tau)}{6}\frac{p(p+1+2r)M_{p-2,q}^{(r)}(\tau)+r(r-1)M_{p,q+2}^{(r-2)}(\tau)}{M_{pq}^{(r)}(\tau)}. (21)

This equation must be supplemented with Eq. (19). As will be seen later, the steady-state distribution function is independent of the precise value of the stochastic force intensity χ02\chi_{0}^{2} or, equivalently, of the initial value γ(0)\gamma(0), although of course the transient states are dependent on it.

II.4 Exact Sonine expansion

In principle, the reduced distribution function ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) would be a function of six velocity components. On the other hand, since we restrict ourselves to isotropic states, ϕ\phi is actually a function of three scalar quantities: the norms c2c^{2} and w2w^{2}, and the squared dot product (𝐜,𝐰)2(\mathbf{c},\mathbf{w})^{2}.Santos, Kremer, and dos Santos (2011) Thus, it makes sense to represent ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) as an expansion in a complete set {Ψjk()(𝐜,𝐰)}\{\Psi_{jk}^{(\ell)}(\mathbf{c},\mathbf{w})\} of orthogonal polynomials,

ϕ(𝐜,𝐰;τ)=ϕM(c,w)j=0k=0=0ajk()(τ)Ψjk()(𝐜,𝐰),ϕM(c,w)π3ec2w2,\phi(\mathbf{c},\mathbf{w};\tau)=\phi_{M}(c,w)\sum_{j=0}^{\infty}\sum_{k=0}^{\infty}\sum_{\ell=0}^{\infty}a_{jk}^{(\ell)}(\tau)\Psi_{jk}^{(\ell)}(\mathbf{c},\mathbf{w}),\quad\phi_{M}(c,w)\equiv\pi^{-3}e^{-c^{2}-w^{2}}, (22)

where

Ψjk()(𝐜,𝐰)Lj(2+12)(c2)Lk(2+12)(w2)(c2w2)P2(cosϑ),cosϑ𝐜𝐰cw,\Psi_{jk}^{(\ell)}(\mathbf{c},\mathbf{w})\equiv L_{j}^{(2\ell+\frac{1}{2})}(c^{2})L_{k}^{(2\ell+\frac{1}{2})}(w^{2})\left(c^{2}w^{2}\right)^{\ell}P_{2\ell}(\cos\vartheta),\quad\cos\vartheta\equiv\frac{\mathbf{c}\cdot\mathbf{w}}{cw}, (23)

where Lj(2+12)(x)L_{j}^{(2\ell+\frac{1}{2})}(x) and P2(x)P_{2\ell}(x) are the Laguerre and Legendre polynomials, respectively.Abramowitz and Stegun (1972) Defining the scalar product of two arbitrary isotropic (real) functions Φ1(𝐜,𝐰)\Phi_{1}(\mathbf{c},\mathbf{w}) and Φ2(𝐜,𝐰)\Phi_{2}(\mathbf{c},\mathbf{w}) as

Φ1|Φ2𝑑𝐜𝑑𝐰ϕM(c,w)Φ1(𝐜,𝐰)Φ2(𝐜,𝐰),\langle\Phi_{1}|\Phi_{2}\rangle\equiv\int d\mathbf{c}\int d\mathbf{w}\,\phi_{M}(c,w)\Phi_{1}(\mathbf{c},\mathbf{w})\Phi_{2}(\mathbf{c},\mathbf{w}), (24)

one can obtain the orthogonality relation

Ψjk()|Ψjk()=𝒩jk()δj,jδk,kδ,,𝒩jk()Γ(j+2+32)Γ(k+2+32)(π/4)(4+1)j!k!.\langle\Psi_{jk}^{(\ell)}|\Psi_{j^{\prime}k^{\prime}}^{(\ell^{\prime})}\rangle=\mathcal{N}_{jk}^{(\ell)}\delta_{j,j^{\prime}}\delta_{k,k^{\prime}}\delta_{\ell,\ell^{\prime}},\quad\mathcal{N}_{jk}^{(\ell)}\equiv\frac{\Gamma(j+2\ell+\frac{3}{2})\Gamma(k+2\ell+\frac{3}{2})}{(\pi/4)(4\ell+1)j!k!}. (25)

As a consequence, the coefficients in the expansion (22) are

ajk()=\displaystyle a_{jk}^{(\ell)}= Ψjk()𝒩jk()\displaystyle\frac{\langle\Psi_{jk}^{(\ell)}\rangle}{\mathcal{N}_{jk}^{(\ell)}}
=\displaystyle= j1=0jk1=0k1=0(1)j1+k1+1(π/4)j!k!(4+1)(4211)!!M2(j1+1),2(k1+1)(221)j1!(jj1)!Γ(j1+2+32)k1!(kk1)!Γ(k1+2+32)211!(221)!,\displaystyle\sum_{j_{1}=0}^{j}\sum_{k_{1}=0}^{k}\sum_{\ell_{1}=0}^{\ell}\frac{(-1)^{j_{1}+k_{1}+\ell_{1}}(\pi/4)j!k!(4\ell+1)(4\ell-2\ell_{1}-1)!!M_{2(j_{1}+\ell_{1}),2(k_{1}+\ell_{1})}^{(2\ell-2\ell_{1})}}{j_{1}!(j-j_{1})!\Gamma\left(j_{1}+2\ell+\frac{3}{2}\right)k_{1}!(k-k_{1})!\Gamma\left(k_{1}+2\ell+\frac{3}{2}\right)2^{\ell_{1}}\ell_{1}!(2\ell-2\ell_{1})!}, (26)

where in the second step use has been made of the explicit expressions of the Laguerre and Legendre polynomials.Abramowitz and Stegun (1972) We observe that ajk()a_{jk}^{(\ell)} is a linear combination of the moments Mpq(r)M_{pq}^{(r)} with p,q,r=evenp,q,r=\text{even} and degree 2p+q+2r2(j+k+2)2\ell\leq p+q+2r\leq 2(j+k+2\ell). By normalization, a00(0)=1a_{00}^{(0)}=1, a10(0)=a01(0)=0a_{10}^{(0)}=a_{01}^{(0)}=0. Therefore, the first nontrivial coefficients are those associated with moments of degree four, namely

a20(0)=415c41,a02(0)=415w41,a_{20}^{(0)}=\frac{4}{15}\langle c^{4}\rangle-1,\quad a_{02}^{(0)}=\frac{4}{15}\langle w^{4}\rangle-1, (27a)
a11(0)=49c2w21,a00(1)=815[(𝐜𝐰)213c2w2].a_{11}^{(0)}=\frac{4}{9}\langle c^{2}w^{2}\rangle-1,\quad{a_{00}^{(1)}=\frac{8}{15}\left[\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle-\frac{1}{3}\langle c^{2}w^{2}\rangle\right]}. (27b)

These are the fourth-degree cumulants, which measure the basic deviations of the velocity distribution function ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) from the (two-temperaure) Maxwellian ϕM(c,w)\phi_{M}(c,w). While a20(0)a_{20}^{(0)} and a02(0)a_{02}^{(0)} measure the kurtosis of the (marginal) translational and rotational velocity distribution functions, respectively, the coefficient a11(0)a_{11}^{(0)} characterizes the scalar translational-rotational correlations, i.e., c2w2c2w2\langle c^{2}w^{2}\rangle\neq\langle c^{2}\rangle\langle w^{2}\rangle. Finally, a00(1)a_{00}^{(1)} informs us about the possible existence of orientational correlations, i.e., c2w2cos2ϑc2w2cos2ϑ\langle c^{2}w^{2}\cos^{2}\vartheta\rangle\neq\langle c^{2}w^{2}\rangle\langle\cos^{2}\vartheta\rangle and cos2ϑ13\langle\cos^{2}\vartheta\rangle\neq\frac{1}{3}. To disentangle the latter two effects, let us define the quantities

h58[(𝐜𝐰)2c2w2cos2ϑ1],b103(cos2ϑ13).{h\equiv\frac{5}{8}\left[\frac{\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle}{\langle c^{2}w^{2}\rangle\langle\cos^{2}\vartheta\rangle}-1\right]},\quad b\equiv\frac{10}{3}\left(\langle\cos^{2}\vartheta\rangle-\frac{1}{3}\right). (28)

The parameters hh, bb, a11(0)a_{11}^{(0)}, and a00(1)a_{00}^{(1)} are related by

h=11625a00(1)9b(1+a11(0))(1+910b)(1+a11(0)).{h=\frac{1}{16}\frac{25a_{00}^{(1)}-9b\left(1+a_{11}^{(0)}\right)}{\left(1+\frac{9}{10}b\right)\left(1+a_{11}^{(0)}\right)}.} (29)

In previous works,Brilliantov et al. (2007); Kranz et al. (2009); Rongali and Alam (2014) the angle ϑ\vartheta between translational and rotational particle velocities has been used for measuring orientational correlations in a granular gas of rough spheres, by tracking the quantity cos2ϑ\langle\cos^{2}\vartheta\rangle or, equivalently, bb. The use of bb has the advantage over a00(1)a_{00}^{(1)} of being more intuitive (since it directly refers to the angle between translational and rotational particle velocities). However, it has the disadvantage that, since cosϑ=𝐜𝐰/cw\cos\vartheta=\mathbf{c}\cdot\mathbf{w}/cw is not a polynomial, the parameter bb involves an infinite number of coefficients in the expansion (22). More specifically, it is easy to find

b=j=0k=0ajk(1).b=\sum_{j=0}^{\infty}\sum_{k=0}^{\infty}a_{jk}^{(1)}. (30)

Analogously, the quantity hh also involves an infinite number of coefficients. For this reason, we prefer instead to use the single coefficient a00(1)a_{00}^{(1)} for measuring the orientational correlations in a granular gas of rough spheres.Vega Reyes, Santos, and Kremer (2014)

Taking into account the general moment hierarchy (21), the evolution equations for the fourth-degree cumulants are

ln[1+a20(0)(τ)]τ=43μ20(0)(τ)43γ(τ)415μ40(0)(τ)5γ(τ)1+a20(0)(τ),\frac{\partial\ln\left[1+a_{20}^{(0)}(\tau)\right]}{\partial\tau}=\frac{4}{3}\mu_{20}^{(0)}(\tau)-\frac{4}{3}\gamma(\tau)-\frac{4}{15}\frac{\mu_{40}^{(0)}(\tau)-5\gamma(\tau)}{1+a_{20}^{(0)}(\tau)}, (31a)
ln[1+a02(0)(τ)]τ=43μ02(0)(τ)415μ04(0)(τ)1+a02(0)(τ),\frac{\partial\ln\left[1+a_{02}^{(0)}(\tau)\right]}{\partial\tau}=\frac{4}{3}\mu_{02}^{(0)}(\tau)-\frac{4}{15}\frac{\mu_{04}^{(0)}(\tau)}{1+a_{02}^{(0)}(\tau)}, (31b)
ln[1+a11(0)(τ)]τ=23μ20(0)(τ)+23μ02(0)(τ)23γ(τ)49μ22(0)(τ)32γ(τ)1+a11(0)(τ),\frac{\partial\ln\left[1+a_{11}^{(0)}(\tau)\right]}{\partial\tau}=\frac{2}{3}\mu_{20}^{(0)}(\tau)+\frac{2}{3}\mu_{02}^{(0)}(\tau)-\frac{2}{3}\gamma(\tau)-\frac{4}{9}\frac{\mu_{22}^{(0)}(\tau)-\frac{3}{2}\gamma(\tau)}{1+a_{11}^{(0)}(\tau)}, (31c)
ln[1+a11(0)(τ)+52a00(1)(τ)]τ=23μ20(0)(τ)+23μ02(0)(τ)23γ(τ)43μ00(2)(τ)12γ(τ)1+a11(0)(τ)+52a00(1)(τ).\frac{\partial\ln\left[1+a_{11}^{(0)}(\tau)+\frac{5}{2}a_{00}^{(1)}(\tau)\right]}{\partial\tau}=\frac{2}{3}\mu_{20}^{(0)}(\tau)+\frac{2}{3}\mu_{02}^{(0)}(\tau)-\frac{2}{3}\gamma(\tau)-\frac{4}{3}\frac{\mu_{00}^{(2)}(\tau)-\frac{1}{2}\gamma(\tau)}{1+a_{11}^{(0)}(\tau)+\frac{5}{2}a_{00}^{(1)}(\tau)}. (31d)

In the steady state (τ0\partial_{\tau}\to 0), Eqs. (10) and (31) imply the conditions

γ=μ20(0),μ02(0)=0,\gamma=\mu_{20}^{(0)},\quad\mu_{02}^{(0)}=0, (32a)
15μ40(0)=23μ22(0)=2μ00(2)=μ20(0),μ04(0)=0.\frac{1}{5}\mu_{40}^{(0)}=\frac{2}{3}\mu_{22}^{(0)}=2\mu_{00}^{(2)}=\mu_{20}^{(0)},\quad\mu_{04}^{(0)}=0. (32b)

Before closing this section, and for further use, let us define the marginal distributions ϕc(c)\phi_{c}(c), ϕw(w)\phi_{w}(w), ϕcw(c2w2)\phi_{cw}(c^{2}w^{2}), ϕ𝐜𝐰((𝐜𝐰)2)\phi_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2}), and ϕϑ(cos2ϑ)\phi_{\vartheta}(\cos^{2}\vartheta) from the joint velocity distribution function ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) as

ϕc(c)=4πc2𝑑𝐰ϕ(𝐜,𝐰),ϕw(w)=4πw2𝑑𝐜ϕ(𝐜,𝐰),\phi_{c}(c)=4\pi c^{2}\int d\mathbf{w}\,\phi(\mathbf{c},\mathbf{w}),\quad\phi_{w}(w)=4\pi w^{2}\int d\mathbf{c}\,\phi(\mathbf{c},\mathbf{w}), (33a)
ϕcw(c2w2)=𝑑𝐜𝑑𝐰δ(c2w2c2w2)ϕ(𝐜,𝐰),\phi_{cw}(c^{2}w^{2})=\int d\mathbf{c}^{\prime}\int d\mathbf{w}^{\prime}\,\delta(c^{\prime 2}w^{\prime 2}-c^{2}w^{2})\phi(\mathbf{c}^{\prime},\mathbf{w}^{\prime}), (33b)
ϕ𝐜𝐰((𝐜𝐰)2)=𝑑𝐜𝑑𝐰δ((𝐜𝐰)2(𝐜𝐰)2)ϕ(𝐜,𝐰),\phi_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})=\int d\mathbf{c}^{\prime}\int d\mathbf{w}^{\prime}\,\delta((\mathbf{c}^{\prime}\cdot\mathbf{w}^{\prime})^{2}-(\mathbf{c}\cdot\mathbf{w})^{2})\phi(\mathbf{c}^{\prime},\mathbf{w}^{\prime}), (33c)
ϕϑ(cos2ϑ)=𝑑𝐜𝑑𝐰δ(cos2ϑcos2ϑ)ϕ(𝐜,𝐰).\phi_{\vartheta}(\cos^{2}\vartheta)=\int d\mathbf{c}^{\prime}\int d\mathbf{w}^{\prime}\,\delta(\cos^{2}\vartheta^{\prime}-\cos^{2}\vartheta)\phi(\mathbf{c}^{\prime},\mathbf{w}^{\prime}). (33d)

The less conventional marginal distribution functions (33b)–(33d) are directly related to the scalar and orientational correlations between the translational and rotational particle velocities. More specifically,

c2w2=0𝑑xxϕcw(x),(𝐜𝐰)2=0𝑑xxϕ𝐜𝐰(x),cos2ϑ=01𝑑xxϕϑ(x).\langle c^{2}w^{2}\rangle=\int_{0}^{\infty}dx\,x\phi_{cw}(x),\quad\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle=\int_{0}^{\infty}dx\,x\phi_{\mathbf{c}\cdot\mathbf{w}}(x),\quad\langle\cos^{2}\vartheta\rangle=\int_{0}^{1}dx\,x\phi_{\vartheta}(x). (34)

III Approximate solution from a truncated Sonine expansion

All of the equations in Sec. II are formally exact. On the other hand, the collisional moments μ20(0)\mu_{20}^{(0)}, μ02(0)\mu_{02}^{(0)}, μ40(0)\mu_{40}^{(0)}, μ04(0)\mu_{04}^{(0)}, μ220)\mu_{22}^{0)}, and μ00(2)\mu_{00}^{(2)}, defined by the general expression (17), are functionals of ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}), and thus they depend on the whole set of expansion coefficient {ajk()}\{a_{jk}^{(\ell)}\}. They also depend on the temperature ratio θ\theta through the collision rules. Therefore, Eqs. (19) and (31) do not make a closed set of equations.

Nevertheless, the expansion (22) is especially useful for states with a distribution function close to the Maxwellian ϕM(c,w)\phi_{M}(c,w), in which case an approximate closure can be applied. In a previous work,Vega Reyes, Santos, and Kremer (2014) we used the expansion (22) for describing the HCS distribution function. We found that the HCS is very far from the Maxwellian for a certain range of values of the roughness parameter β\beta, thus limiting the practical validity of this kind of theoretical description for the unforced gas. However, we can expect that the white noise thermostat keeps the distribution function closer to the Maxwellian, in analogy with what happens in the smooth-sphere case.Montanero and Santos (2000) If so, a better accuracy of the expansion (22) can be expected in the present case. We will confirm this property in Sec. IV.

III.1 Maxwellian approximation

The simplest approximation consists in neglecting all the cumulants ajk()a_{jk}^{(\ell)}, j+k+22j+k+2\ell\geq 2, in Eq. (22), i.e., ϕ(𝐜,𝐰)ϕM(c,w)\phi(\mathbf{c},\mathbf{w})\simeq\phi_{M}(c,w). This Maxwellian approximation is of course unable to account for the evolution and steady-state values of the cumulants. However, it can capture the main features of the temperature ratio θ(τ)\theta(\tau) and the reduced noise intensity γ(τ)\gamma(\tau). When ϕ(𝐜,𝐰)ϕM(c,w)\phi(\mathbf{c},\mathbf{w})\simeq\phi_{M}(c,w) is inserted into Eq. (17), one obtains

μ20,M(0)=1α2+κ(1+β)(1+κ)2[2+κ(1β)θ(1+β)],\mu_{20,M}^{(0)}=1-\alpha^{2}+\frac{\kappa(1+\beta)}{(1+\kappa)^{2}}\left[2+\kappa(1-\beta)-\theta(1+\beta)\right], (35a)
μ02,M(0)=κ(1+β)(1+κ)2[2+κ1(1β)θ1(1+β)].\mu_{02,M}^{(0)}=\frac{\kappa(1+\beta)}{(1+\kappa)^{2}}\left[2+\kappa^{-1}(1-\beta)-\theta^{-1}(1+\beta)\right]. (35b)

Using these expressions in (19), one gets a closed set of two coupled nonlinear differential equations that can be numerically solved for arbitrary initial values θ(0)\theta(0) and γ(0)\gamma(0). Regardless of the values of θ(0)\theta(0) and γ(0)\gamma(0), common steady-state values are reached after a few collisions per particle. They are explicitly obtained from Eq. (32a) as

θM=1+β2+κ1(1β),γM=1α2+2(1β2)2+κ1(1β).\theta_{M}=\frac{1+\beta}{2+\kappa^{-1}(1-\beta)},\quad\gamma_{M}=1-\alpha^{2}+\frac{2(1-\beta^{2})}{2+\kappa^{-1}(1-\beta)}. (36)

It is interesting to note that the Maxwellian prediction for the steady-state value of the temperature ratio is independent of the coefficient of normal restitution α\alpha. Moreover, θM\theta_{M} is always smaller than unity (i.e., Tr<TtT_{r}<T_{t}), except in the limit of completely rough spheres (β=1\beta=1), where θM=1\theta_{M}=1. In the case of the reduced noise intensity, we can observe that γM\gamma_{M} monotonically decreases as α\alpha increases at fixed β\beta, as a consequence of a progressively smaller cooling effect. Because of the same reason, γM\gamma_{M} presents a non-monotonic behavior with respect to β\beta at fixed α\alpha, reaching a maximum value γM,max=1α2+4κ(1+2κ2κ+κ2)\gamma_{M,\max}=1-\alpha^{2}+4\kappa(1+2\kappa-2\sqrt{\kappa+\kappa^{2}}) at β=12(κ+κ2κ)\beta=1-2(\sqrt{\kappa+\kappa^{2}}-\kappa). However, as we will see in Sec. IV, θ\theta actually depends on α\alpha but much more weakly than it depends on β\beta. Also, θ\theta can reach values slightly larger than unity if β\beta is very close to 11 and α\alpha is small enough. In any case, as shown later, the Maxwellian expressions (36) are indeed rather accurate.

The marginal distribution functions defined by (33) adopt simple forms in the Maxwellian approximation,

ϕc,M(c)=4πc2ec2,ϕw,M(c)=4πw2ew2,\phi_{c,M}(c)=\frac{4}{\sqrt{\pi}}c^{2}e^{-c^{2}},\quad\phi_{w,M}(c)=\frac{4}{\sqrt{\pi}}w^{2}e^{-w^{2}}, (37a)
ϕcw,M(c2w2)=8cwπK0(2cw),ϕ𝐜𝐰,M((𝐜𝐰)2)=4πK1(2|𝐜𝐰|),ϕϑ,M(cos2ϑ)=12|cosϑ|,\phi_{cw,M}(c^{2}w^{2})=\frac{8cw}{\pi}K_{0}(2cw),\quad\phi_{\mathbf{c}\cdot\mathbf{w},M}((\mathbf{c}\cdot\mathbf{w})^{2})=\frac{4}{\pi}K_{1}(2|\mathbf{c}\cdot\mathbf{w}|),\quad\phi_{\vartheta,M}(\cos^{2}\vartheta)=\frac{1}{2|\cos\vartheta|}, (37b)

where Kn(x)K_{n}(x) is a modified Bessel function of the second kind.Abramowitz and Stegun (1972) Upon deriving (37b) use has been made of the mathematical properties δ(c2w2x)=δ(wx/c)/2c2w\delta(c^{\prime 2}w^{\prime 2}-x)=\delta(w^{\prime}-\sqrt{x}/c^{\prime})/2c^{\prime 2}w^{\prime}, δ((𝐜𝐰)2x)=δ(|cosϑ|x/cw)/2c2w2|cosϑ|\delta((\mathbf{c}^{\prime}\cdot\mathbf{w}^{\prime})^{2}-x)=\delta(|\cos\vartheta|-\sqrt{x}/cw)/2c^{2}w^{2}|\cos\vartheta|, and δ(cos2ϑx)=δ(|cosϑ|x)/2|cosϑ|\delta(\cos^{2}\vartheta-x)=\delta(|\cos\vartheta|-\sqrt{x})/2|\cos\vartheta|, respectively. Apart from c4=w4=154\langle c^{4}\rangle=\langle w^{4}\rangle=\frac{15}{4}, it is straightforward to check from Eqs. (34) and (37b) that c2w2=94\langle c^{2}w^{2}\rangle=\frac{9}{4}, (𝐜𝐰)2=34\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle=\frac{3}{4}, and cos2ϑ=13\langle\cos^{2}\vartheta\rangle=\frac{1}{3} in the Maxwellian approximation, as expected.

III.2 Truncated Sonine approximation

As a much more elaborate approximation that captures the most important non-Maxwellian features of the velocity distribution function, we truncate the exact expansion (22) after j+k+2=2j+k+2\ell=2, i.e.Vega Reyes, Santos, and Kremer (2014)

ϕ(𝐜,𝐰)ϕM(c,w)\displaystyle\frac{\phi(\mathbf{c},\mathbf{w})}{\phi_{M}(c,w)}\simeq 1+a20(0)Ψ20(0)(𝐜,𝐰)+a02(0)Ψ02(0)(𝐜,𝐰)+a11(0)Ψ11(0)(𝐜,𝐰)+a00(1)Ψ00(1)(𝐜,𝐰)\displaystyle{1+}a_{20}^{(0)}\Psi_{20}^{(0)}(\mathbf{c},\mathbf{w})+a_{02}^{(0)}\Psi_{02}^{(0)}(\mathbf{c},\mathbf{w})+a_{11}^{(0)}\Psi_{11}^{(0)}(\mathbf{c},\mathbf{w})+a_{00}^{(1)}\Psi_{00}^{(1)}(\mathbf{c},\mathbf{w})
=\displaystyle= 1+a20(0)1520c2+4c48+a02(0)1520w2+4w48+a11(0)(32c2)(32w2)4\displaystyle 1+{a_{20}^{(0)}}\frac{{15}-20c^{2}+4c^{4}}{8}+{a_{02}^{(0)}}\frac{{15}-20w^{2}+4w^{4}}{8}+{a_{11}^{(0)}}\frac{\left(3-2c^{2}\right)\left(3-2w^{2}\right)}{4}
+a00(1)3(𝐜𝐰)2c2w22.\displaystyle+{a_{00}^{(1)}}\frac{3(\mathbf{c}\cdot\mathbf{w})^{2}-c^{2}w^{2}}{2}. (38)

This approximation differs from that considered in Ref. Santos, Kremer, and dos Santos, 2011 by the addition of the term headed by the coefficient a00(1)a_{00}^{(1)}. The associated marginal distributions are

ϕc(c)ϕc,M(c)=1+a20(0)1520c2+4c48,ϕw(w)ϕw,M(w)=1+a02(0)1520w2+4w48,\frac{\phi_{c}(c)}{\phi_{c,M}(c)}=1+a_{20}^{(0)}\frac{{15}-20c^{2}+4c^{4}}{8},\quad\frac{\phi_{w}(w)}{\phi_{w,M}(w)}=1+a_{02}^{(0)}\frac{{15}-20w^{2}+4w^{4}}{8}, (39a)
ϕcw(c2w2)ϕcw,M(c2w2)=\displaystyle\frac{\phi_{cw}(c^{2}w^{2})}{\phi_{cw,M}(c^{2}w^{2})}= 1+a20(0)+a02(0)8[15+4c2w216cwK1(2cw)K0(2cw)]\displaystyle 1+\frac{a_{20}^{(0)}+a_{02}^{(0)}}{8}\left[15+4c^{2}w^{2}-16cw\frac{K_{1}(2cw)}{K_{0}(2cw)}\right]
+a11(0)4[9+4c2w212cwK1(2cw)K0(2cw)],\displaystyle+\frac{a_{11}^{(0)}}{4}\left[9+4c^{2}w^{2}-12cw\frac{K_{1}(2cw)}{K_{0}(2cw)}\right], (39b)
ϕ𝐜𝐰((𝐜𝐰)2)ϕ𝐜𝐰,M((𝐜𝐰)2)=\displaystyle\frac{\phi_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})}{\phi_{\mathbf{c}\cdot\mathbf{w},M}((\mathbf{c}\cdot\mathbf{w})^{2})}= 1+a20(0)+a02(0)8[3+4(𝐜𝐰)212|𝐜𝐰|K0(2|𝐜𝐰|)K1(2|𝐜𝐰|)]\displaystyle 1+\frac{a_{20}^{(0)}+a_{02}^{(0)}}{8}\left[3+4(\mathbf{c}\cdot\mathbf{w})^{2}-12|\mathbf{c}\cdot\mathbf{w}|\frac{K_{0}(2|\mathbf{c}\cdot\mathbf{w}|)}{K_{1}(2|\mathbf{c}\cdot\mathbf{w}|)}\right]
+a11(0)4[1+4(𝐜𝐰)28|𝐜𝐰|K0(2|𝐜𝐰|)K1(2|𝐜𝐰|)]\displaystyle+\frac{a_{11}^{(0)}}{4}\left[1+4(\mathbf{c}\cdot\mathbf{w})^{2}-8|\mathbf{c}\cdot\mathbf{w}|\frac{K_{0}(2|\mathbf{c}\cdot\mathbf{w}|)}{K_{1}(2|\mathbf{c}\cdot\mathbf{w}|)}\right]
a00(1)2[12(𝐜𝐰)2+|𝐜𝐰|K0(2|𝐜𝐰|)K1(2|𝐜𝐰|)],\displaystyle-\frac{a_{00}^{(1)}}{2}\left[1-2(\mathbf{c}\cdot\mathbf{w})^{2}+|\mathbf{c}\cdot\mathbf{w}|\frac{K_{0}(2|\mathbf{c}\cdot\mathbf{w}|)}{K_{1}(2|\mathbf{c}\cdot\mathbf{w}|)}\right], (39c)
ϕϑ(cos2ϑ)ϕϑ,M(cos2ϑ)=1+9a00(1)8(3cos2ϑ1).\frac{\phi_{\vartheta}(\cos^{2}\vartheta)}{\phi_{\vartheta,M}(\cos^{2}\vartheta)}=1+\frac{9a_{00}^{(1)}}{8}\left(3\cos^{2}\vartheta-1\right). (39d)

This yields c4=154(1+a20(0))\langle c^{4}\rangle=\frac{15}{4}(1+a_{20}^{(0)}), w4=154(1+a02(0))\langle w^{4}\rangle=\frac{15}{4}(1+a_{02}^{(0)}), c2w2=94(1+a11(0))\langle c^{2}w^{2}\rangle=\frac{9}{4}(1+a_{11}^{(0)}), (𝐜𝐰)2=34(1+a11(0)+52a00(1))\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle=\frac{3}{4}(1+a_{11}^{(0)}+\frac{5}{2}a_{00}^{(1)}), and cos2ϑ=13(1+910a00(1))\langle\cos^{2}\vartheta\rangle=\frac{1}{3}(1+\frac{9}{10}a_{00}^{(1)}), as expected. The latter equality implies b=a00(1)b=a_{00}^{(1)}, in consistency with the neglect of ajk()a_{jk}^{(\ell)} with j+k+23j+k+2\ell\geq 3 in Eq. (30). If, additionally, terms nonlinear in the cumulants are neglected in Eq. (29), we have

hba00(1){h\simeq b\simeq a_{00}^{(1)}} (40)

in the Sonine approximation (38). Thus, if a00(1)<0a_{00}^{(1)}<0 (as will be seen to be the case for most values of α\alpha and β\beta in the case of uniform spheres), we can expect that cos2ϑ<13\langle\cos^{2}\vartheta\rangle<\frac{1}{3}. This implies a tendency of the vectors 𝐜\mathbf{c} and 𝐰\mathbf{w} to favor quasinormal mutual orientations (“lifted-tennis-ball” effect).

If Eq. (38) is inserted into Eq. (17) and terms nonlinear in ajk()a_{jk}^{(\ell)} are neglected, one obtains explicit (yet not exact) expressions of μpq(r)\mu_{pq}^{(r)} with p+q+2r=2p+q+2r=2 and 44. Those expressions were first displayed in the Supplemental material of Ref. Vega Reyes, Santos, and Kremer, 2014 but, for the sake of completion, they can be found here in the Appendix. Once Eqs. (42)–(47) are introduced into Eqs.  (19) and (31), the resulting closed set of six equations can be numerically solved for arbitrary initial values to get the time-dependent functions θ(τ)\theta(\tau), γ(τ)\gamma(\tau), a20(0)(τ)a_{20}^{(0)}(\tau), a02(0)(τ)a_{02}^{(0)}(\tau), a11(0)(τ)a_{11}^{(0)}(\tau), and a00(1)(τ)a_{00}^{(1)}(\tau).not We will include in Sec. IV graphs of those functions and compare them with the “exact” numerical solution of the Boltzmann equation obtained by means of the DSMC method.Bird (1994)

As for the steady state, by applying the state-state conditions (32) and the Sonine expressions (42)–(47), we are able to obtain fully analytical explicit expressions for the temperature ratio θ\theta, the dimensionless noise intensity γ\gamma, and the four cumulants a20(0)a_{20}^{(0)}, a02(0)a_{02}^{(0)}, a11(0)a_{11}^{(0)}, and a00(1)a_{00}^{(1)}. The method is quite simple.not First, the relations in Eq. (32b) are used to express the four cumulants in terms of the yet unknown quantity θ\theta. Inserting those expressions into μ02(0)=0\mu_{02}^{(0)}=0, one gets a closed quartic equation for θ\theta, whose physical solution is identified as the one closer to θM\theta_{M} [see Eq. (36)]. Finally, γ\gamma is obtained from γ=μ20(0)\gamma=\mu_{20}^{(0)}.

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Figure 1: Density plots, for uniform spheres (κ=25\kappa=\frac{2}{5}), of the steady-state values of (a) the temperature ratio θ=Tr/Tt\theta=T_{r}/T_{t}, (b) the dimensionless noise intensity γ\gamma [see Eq. (16)], (c) the translational kurtosis a20(0)a_{20}^{(0)} [see Eq. (27a)], (d) the rotational kurtosis a02(0)a_{02}^{(0)} [see Eq. (27a)], (e) the scalar correlation cumulant a11(0)a_{11}^{(0)} [see Eq. (27b)], and (f) the orientational correlation cumulant a00(1)a_{00}^{(1)} [see Eq. (27b)]. The contour lines correspond to (a) θ=0.1,0.2,,0.9\theta=0.1,0.2,\ldots,0.9, (b) γ=0.1,0.2,,1.5\gamma=0.1,0.2,\ldots,1.5, (c) a20(0)=0.01,0.00,,0.09a_{20}^{(0)}=-0.01,0.00,\ldots,0.09, (d) a02(0)=0.00,0.01,,0.05a_{02}^{(0)}=0.00,0.01,\ldots,0.05, (e) a11(0)=0.00,0.01,,0.09a_{11}^{(0)}=0.00,0.01,\ldots,0.09, and (f) a00(1)=0.07,0.06,,0.00a_{00}^{(1)}=-0.07,-0.06,\ldots,0.00.

Figure 1 presents density plots of the steady-state values for uniform spheres (κ=25\kappa=\frac{2}{5}) of θ\theta, γ\gamma, a20(0)a_{20}^{(0)}, a02(0)a_{02}^{(0)}, a11(0)a_{11}^{(0)}, and a00(1)a_{00}^{(1)}. In Fig. 1(a) we may point out that iso-θ\theta curves are almost perpendicular to the β\beta axis, indicating that θ\theta depends almost entirely on the coefficient of tangential restitution and hardly on α\alpha, as anticipated by the Maxwellian approximation θM\theta_{M} in Eq. (36). Also, θ<1\theta<1, except, and this is not visible in Fig. 1(a), if β>0.994 336\beta>0.994\,336 and 0α<α1(β)0\leq\alpha<\alpha_{1}(\beta), where α1(0.994 336)=0\alpha_{1}(0.994\,336)=0 and α1(1)=1/2\alpha_{1}(1)=1/\sqrt{2}. The maximum value θmax=1.009 85\theta_{\max}=1.009\,85 takes place at α=0\alpha=0 and β=1\beta=1, i.e., in the completely inelastic and rough limit. The behavior of γ\gamma observed in Fig. 1(b) is in good agreement with the one expected from the Maxwellian approximation γM\gamma_{M} in Eq. (36). The latter predicts, at fixed α\alpha, a maximum value γM,max1.4853α2\gamma_{M,\max}\simeq 1.4853-\alpha^{2} at β0.3033\beta\simeq 0.3033. In the Sonine approximation, we find that the location and value of the maximum slightly changes from β0.301\beta\simeq 0.301 and γmax+α21.512\gamma_{\max}+\alpha^{2}\simeq 1.512 at α=0\alpha=0 to β0.304\beta\simeq 0.304 and γmax+α21.486\gamma_{\max}+\alpha^{2}\simeq 1.486 at α=1\alpha=1.

Since θ\theta and γ\gamma are well represented by the Maxwellian approximation (36), the most interesting panels in Fig. 1 are those related to the cumulants. The first feature to be noted is that all of them have a relatively small magnitude |ajk()|<0.1|a_{jk}^{(\ell)}|<0.1, implying that a good performance of the Sonine approximation (38), and hence the validity of (40), can be expected. This expectation will be confirmed in Sec. IV. We can also see that, at given α\alpha, the maximum value of |ajk()||a_{jk}^{(\ell)}| is typically reached in the region of intermediate roughness (β0\beta\sim 0), which differs from the behavior detected for the HCS, where the maximum values (which are also much larger than here) occur in the region close to the smooth limit.Vega Reyes, Santos, and Kremer (2014)

Figure 1(c) shows that the translational kurtosis a20(0)a_{20}^{(0)} takes negative values in the top and bottom right corners of the map. In contrast, the region where the rotational kurtosis a02(0)a_{02}^{(0)} is negative reduces to a small top-right corner (α,β1\alpha,\beta\lesssim 1) [see Fig. 1(d)]. The analogous top-right corners where a11(0)<0a_{11}^{(0)}<0 and a00(1)>0a_{00}^{(1)}>0, respectively, are even smaller in the cases of the correlation cumulants a11(0)a_{11}^{(0)} and, especially, a00(1)a_{00}^{(1)} [see Figs. 1(e) and 1(f)].

Therefore, the typical non-Maxwellian features of the joint velocity distribution function ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) that can be extracted from Figs. 1(c)–1(f) are: (i) platykurtic translational (a20(0)>0c4>154a_{20}^{(0)}>0\Rightarrow\langle c^{4}\rangle>\frac{15}{4}) and rotational (a02(0)>0w4>154a_{02}^{(0)}>0\Rightarrow\langle w^{4}\rangle>\frac{15}{4}) velocity distributions; (ii) particles with larger (smaller) translational velocities tend to have larger (smaller) rotational velocities (a11(0)>0c2w2>c2w2=94a_{11}^{(0)}>0\Rightarrow\langle c^{2}w^{2}\rangle>\langle c^{2}\rangle\langle w^{2}\rangle=\frac{9}{4}); and (iii) quasinormal orientations between the vectors 𝐜\mathbf{c} and 𝐰\mathbf{w} tend to be favored against quasiparallel orientations (a00(1)<0cos2ϑ<13a_{00}^{(1)}<0\Rightarrow\langle\cos^{2}\vartheta\rangle<\frac{1}{3}). Exceptions to these general features in the cases of a02(0)a_{02}^{(0)}, a11(0)a_{11}^{(0)}, and a00(1)a_{00}^{(1)} are limited to small regions with α1\alpha\lesssim 1 and β1\beta\lesssim 1 (top-right corners). For the kurtosis a20(0)a_{20}^{(0)}, the size of the top-right exception region is significantly larger and, moreover, another even larger bottom-right corner appears.

It is worth remarking that, while there still exists a prevalence of cos2ϑ<13\langle\cos^{2}\vartheta\rangle<\frac{1}{3} (lifted-tennis-ball effect) for the unforced granular gas in the HCS,Brilliantov et al. (2007); Kranz et al. (2009); Rongali and Alam (2014); Vega Reyes, Santos, and Kremer (2014) a significantly larger region with cos2ϑ>13\langle\cos^{2}\vartheta\rangle>\frac{1}{3} (“cannon-ball” effect) appears close to α,β1\alpha,\beta\lesssim 1 and a second region with the same behavior appears in the opposite perfectly smooth limit (α1\alpha\lesssim 1, β1\beta\gtrsim-1). The counterpart of this second region is completely absent in the case of a heated granular gas considered here. This is closely related to the fact that, while the quasismooth limit β1\beta\to-1 is singular in the HCS,Brilliantov et al. (2007); Vega Reyes, Santos, and Kremer (2014) it becomes regular in the heated case. Taking carefully the limit β1\beta\to-1 in the analytical expressions for θ\theta, γ\gamma, and ajk()a_{jk}^{(\ell)}, one getsSantos, Kremer, and dos Santos (2011)

θ6145α+6α2(1α)1511α+2α2(1α)1+β8κκ+10,γ4(1α2)6145α+6α2(1α)241177α+30α2(1α),{\theta\to\frac{61-45\alpha+6\alpha^{2}(1-\alpha)}{15-11\alpha+2\alpha^{2}(1-\alpha)}\frac{1+\beta}{8}{\frac{\kappa}{\kappa+1}}\to 0,\quad\gamma\to 4(1-\alpha^{2})\frac{61-45\alpha+6\alpha^{2}(1-\alpha)}{241-177\alpha+30\alpha^{2}(1-\alpha)}}, (41a)
a20(0)16(1α)12α2241177α+30α2(1α),a02(0)0,a11(0)0,a00(1)0.{a_{20}^{(0)}\to 16(1-\alpha)\frac{1-2\alpha^{2}}{241-177\alpha+30\alpha^{2}(1-\alpha)},\quad a_{02}^{(0)}\to 0,\quad a_{11}^{(0)}\to 0,\quad a_{00}^{(1)}\to 0}. (41b)

The expression of a20(0)a_{20}^{(0)} in Eq. (41b) coincides with the one derived directly for strict smooth spheres (β=1\beta=-1).van Noije and Ernst (1998) Interestingly, in the latter case the rotational distribution function (and hence the temperature TrT_{r}) is not uniquely defined since it preserves with time its initial arbitrary form. On the other hand, the limit β1\beta\to-1 shows that the the rotational degrees of freedom become decoupled from the translational ones (a11(0)0a_{11}^{(0)}\to 0, a00(1)0a_{00}^{(1)}\to 0) but the rotational distribution function tends to a Maxwellian a02(0)0a_{02}^{(0)}\to 0 with a temperature much smaller than the translational one (Tr/Tt0T_{r}/T_{t}\to 0).

Of course the theoretical results presented in this section are valid only if they agree with a direct comparison with a solution of the Boltzmann equation (7) free from any additional hypotheses. This comparison will be done in Sec. IV.

IV Comparison of theoretical results with DSMC data

We display in this section detailed comparisons of the theoretical results with accurate DSMC data, as obtained from a code we wrote specifically for the Boltzmann equation (7) for this system. For data noise reduction, we have used 2×1062\times 10^{6} simulation particles for all cases in this work. More details on the implementation of DSMC in a heated granular gas can be found in Ref. Montanero and Santos, 2000. We fixed the value κ=25\kappa=\frac{2}{5} (uniform spheres) for the reduced moment of inertia and varied either the coefficient of normal restitution α\alpha (at fixed β\beta) or the coefficient of tangential restitution β\beta (at fixed α\alpha). The noise intensity parameter was typically chosen as χ02=245nπσ2[Tt(0)/m]3/2\chi_{0}^{2}=\frac{24}{5}n\pi\sigma^{2}[T_{t}(0)/m]^{3/2}, which corresponds to γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381, but other values were also considered to check the independence of the steady state on the precise value of χ02\chi_{0}^{2}. In all cases, the particle velocities were initially sampled from a Maxwellian distribution [i.e., ajk()(0)=0a_{jk}^{(\ell)}(0)=0] with a common temperature Tr(0)=Tt(0)T_{r}(0)=T_{t}(0) [i.e., θ(0)=1\theta(0)=1]. For each different system, the corresponding data for both transient and steady states were recorded.

IV.1 Transient behavior

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Figure 2: Evolution, for α=0.9\alpha=0.9, β=0\beta=0, and γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381 of (a) temperature ratio θ(τ)\theta(\tau) and reduced noise intensity (normalized to its initial value) γ(τ)/γ(0)\gamma(\tau)/\gamma(0), and (b) cumulants ajk()(τ)a_{jk}^{(\ell)}(\tau). Time is measured in units of number of collisions per particle, τ\tau. Solid lines stand for DSMC results, dashed lines for the Sonine approximation, and dotted lines [only in panel (a)] for the Maxwellian approximation.

As an illustration of the relaxation towards the steady state, and for the case α=0.9\alpha=0.9, β=0\beta=0, and γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381, we show in Fig. 2 the evolution of the temperature ratio θ(τ)\theta(\tau) and the dimensionless noise intensity γ(τ)\gamma(\tau) in panel (a), and of the four cumulants a20(0)(τ)a_{20}^{(0)}(\tau), a02(0)(τ)a_{02}^{(0)}(\tau), a11(0)(τ)a_{11}^{(0)}(\tau), and a00(1)(τ)a_{00}^{(1)}(\tau) in panel (b). A very good agreement between theory and simulation is observed. In the case of γ(τ)\gamma(\tau), the Maxwellian and Sonine approximations give results practically indistinguishable from the DSMC ones. For θ(τ)\theta(\tau), the Sonine approximation is still virtually perfect, while the Maxwellian one tends to slightly overestimate this quantity. The initial reduced white noise intensity γ(0)=185π\gamma(0)=\frac{18}{5}\sqrt{\pi} is larger than the initial cooling rate μ20(0)(0)\mu_{20}^{(0)}(0), and therefore the external-force heating effect dominates over the inelastic cooling. As a consequence, γ(τ)\gamma(\tau) monotonically decays in time [see Eq. (19)] until the steady state is reached (after about 1010 collisions per particle). In this respect, note that, according to Eq. (16), the normalized quantity γ(τ)/γ(0)\gamma(\tau)/\gamma(0) plotted in Fig. 2(a) is equivalent to [Tt(τ)/Tt(0)]3/2[T_{t}(\tau)/T_{t}(0)]^{-3/2}. Thus, the steady-state value γ(τ)/γ(0)0.099\gamma(\tau)/\gamma(0)\to 0.099 implies Tt(τ)/Tt(0)4.66T_{t}(\tau)/T_{t}(0)\to 4.66. The heating is much less efficient in the case of TrT_{r} since the stochastic force acts directly on the translational velocity only. Therefore, the rotational-to-translational temperature ratio decays (but non-monotonically) to Tr(τ)/Tt(τ)0.217T_{r}(\tau)/T_{t}(\tau)\to 0.217 and the rotational temperature has hardly increased to Tr(τ)/Tr(0)1.010T_{r}(\tau)/T_{r}(0)\to 1.010.

The evolution of the cumulants is much less intuitive. As can be observed in Fig. 2(b), for the case under consideration (α=0.9\alpha=0.9, β=0\beta=0) the translational kurtosis a20(0)a_{20}^{(0)} hardly increases, the rotational kurtosis a02(0)a_{02}^{(0)} grows non-monotonically, and the more relevant non-Maxwellian properties are associated with the correlation quantities a11(0)a_{11}^{(0)} and a00(1)a_{00}^{(1)}. All these features are well captured by our Sonine approximation, although it tends to slightly overestimate a02(0)a_{02}^{(0)} and underestimate a11(0)a_{11}^{(0)} and |a00(1)||a_{00}^{(1)}|.

IV.2 Steady state

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Figure 3: Steady-state values of (a) the temperature ratio θ\theta, (b) the reduced noise intensity γ\gamma, and (c) the cumulants ajk()a_{jk}^{(\ell)} as functions of β\beta for α=0.9\alpha=0.9. Circles stand for DSMC data [with γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381], solid lines for the Sonine approximation, and dashed lines [only in panels (a) and (b)] for the Maxwellian approximation. The DSMC data for the quantities bb (×\times) and hh (++) [see Eq. (28)] are also included in panel (c).

Now we focus on the steady state. The influence of the coefficient of tangential restitution β\beta on θ\theta, γ\gamma, and ajk()a_{jk}^{(\ell)} at a fixed coefficient of normal restitution α=0.9\alpha=0.9 is shown in Fig. 3. The DSMC data for the correlation quantities bb and hh [see Eq. (28)] are also plotted in panel (c). Panels (a) and (b) confirm the excellent performance of the simple Maxwellian approximation (36) and of the more elaborate Sonine approximation in what concerns θ\theta and γ\gamma. The temperature ratio θ\theta monotonically increases from θ0\theta\to 0 in the smooth limit β1\beta\to-1 [see (41a)] to θ1\theta\simeq 1 at the perfectly rough case β=1\beta=1. Although not visible on the scale of Fig. 3(a), the DSMC value at β=1\beta=1 is actually θ=0.998\theta=0.998. The quantity γ\gamma exhibits a non-monotonic dependence on β\beta, as already discussed in connection with Fig. 1(b), with a maximum γmax0.675\gamma_{\max}\simeq 0.675 at β0.3\beta\simeq 0.3.

Regarding the cumulants, the behaviors observed in Fig. 3(c) agree with what might have been anticipated by imagining a vertical slice α=0.9\alpha=0.9 in Figs. 1(c)–(f). While a02(0)a_{02}^{(0)}, a11(0)a_{11}^{(0)}, and |a00(1)||a_{00}^{(1)}| vanish at β1\beta\to-1, are very small at β=1\beta=1, and present maxima in the medium-roughness region β0\beta\sim 0, the translational kurtosis a20(0)a_{20}^{(0)} has a more complex behavior with a (positive) maximum at β0.34\beta\simeq 0.34 and two (negative) local minima at β0.79\beta\simeq-0.79 and β0.93\beta\simeq 0.93. We can also observe that the expectations (40) are indeed satisfied. Actually, the only visible differences between a00(1)a_{00}^{(1)}, bb, and hh occur in the region β0\beta\sim 0, where one has |h||a00(1)||b||h|\lesssim|a_{00}^{(1)}|\lesssim|b|. As is apparent from Fig. 3(c), the performance of the Sonine approximation is very good, although small discrepancies, especially in the case of the rotational kurtosis a02(0)a_{02}^{(0)}, appear in the region of medium roughness (β0\beta\sim 0), where the magnitudes of the cumulants are higher. Although hardly visible in Fig. 3(c), the theory succeeds in predicting that a02(1)<0a_{02}^{(1)}<0 (leptokurtic rotational velocity distribution), a11(0)<0a_{11}^{(0)}<0 (high cc correlated with low ww, and viceversa), and a00(1)>0a_{00}^{(1)}>0 (cannon-ball effect) in the regions 0.89β10.89\lesssim\beta\leq 1, 0.92β10.92\lesssim\beta\leq 1, and 0.94β10.94\lesssim\beta\leq 1, respectively. Partially due to the fact that the translational kurtosis a20(0)a_{20}^{(0)} is the cumulant of smaller magnitude in the central region, its Sonine prediction is excellent for all β\beta.

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Figure 4: Steady-state values of (a) the temperature ratio θ\theta, (b) the reduced noise intensity γ\gamma, and (c) the cumulants ajk()a_{jk}^{(\ell)} as functions of α\alpha for β=0.9\beta=-0.9. Circles stand for DSMC data [with γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381], solid lines for the Sonine approximation, and dashed lines [only in panels (a) and (b)] for the Maxwellian approximation. The DSMC data for the quantities bb (×\times) and hh (++) [see Eq. (28)] are also included in panel (c).
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Figure 5: Steady-state values of (a) the temperature ratio θ\theta, (b) the reduced noise intensity γ\gamma, and (c) the cumulants ajk()a_{jk}^{(\ell)} as functions of α\alpha for β=0\beta=0. Circles stand for DSMC data [with γ(0)=310π,35π,65π,95π,3π,185π\gamma(0)=\frac{3}{10}\sqrt{\pi},\frac{3}{5}\sqrt{\pi},\frac{6}{5}\sqrt{\pi},\frac{9}{5}\sqrt{\pi},3\sqrt{\pi},\frac{18}{5}\sqrt{\pi}], solid lines for the Sonine approximation, and dashed lines [only in panels (a) and (b)] for the Maxwellian approximation. The DSMC data for the quantities bb (×\times) and hh (++) [see Eq. (28)] are also included in panel (c).
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Figure 6: Steady-state values of (a) the temperature ratio θ\theta, (b) the reduced noise intensity γ\gamma, and (c) the cumulants ajk()a_{jk}^{(\ell)} as functions of α\alpha for β=0.9\beta=0.9. Circles stand for DSMC data [with γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381], solid lines for the Sonine approximation, and dashed lines [only in panels (a) and (b)] for the Maxwellian approximation. The DSMC data for the quantities bb (×\times) and hh (++) [see Eq. (28)] are also included in panel (c).

Now we turn to the analysis of the influence of α\alpha at fixed β\beta. To that end, we have chosen the characteristic values β=0.9\beta=-0.9 (weak roughness), β=0\beta=0 (medium roughness), and β=0.9\beta=0.9 (strong roughness). The results are displayed in Figs. 4, 5, and 6, respectively. Note that in Fig. 5 the plotted DSMC data correspond to six different values of the initial reduced noise intensity ranging from γ(0)=310π0.532\gamma(0)=\frac{3}{10}\sqrt{\pi}\simeq 0.532 to γ(0)=185π6.381\gamma(0)=\frac{18}{5}\sqrt{\pi}\simeq 6.381. The almost perfect collapse of the points confirms the independence of the steady state on the values of χ02\chi_{0}^{2} and, equivalently, γ(0)\gamma(0).

From Figs. 4(a), 5(a), and 6(a) we observe that, even though the Maxwellian approximation states that the temperature ratio θ\theta is independent of α\alpha, this quantity tends to increase with increasing inelasticity, except near the elastic limit (α1\alpha\lesssim 1) for β=0.9\beta=-0.9 and 0.90.9, were a minimum value is reached. These fine-grained phenomena are very well accounted for by our Sonine approximation, although the latter tends to slightly overestimate θ\theta (note the magnified vertical scales). At fixed β\beta a decrease of α\alpha produces an increase of dissipation and, consequently, an increase of γ\gamma. According to Figs. 4(b), 5(b), and 6(b), the parabolic dependence of γ\gamma on α\alpha predicted by the Maxwellian approximation [see Eq. (36)] tends to lie slightly below the DSMC points for small α\alpha. This deviation is satisfactorily corrected by the Sonine approximation. In what concerns the cumulants, Figs. 4(c), 5(c), and 6(c) show again a very good predictive power of the Sonine approximation. As in Fig. 3(c), the larger discrepancies are found for a02(0)a_{02}^{(0)} for medium roughness (β=0\beta=0). Interestingly, the translational kurtosis becomes larger than the rotational one, i.e., a20(0)>a20(0)a_{20}^{(0)}>a_{20}^{(0)} if α\alpha is small enough. Also, the practical equivalence between the correlation quantities a00(1)a_{00}^{(1)}, bb, and hh is maintained for all α\alpha, although small deviations can be observed at β=0.9\beta=-0.9 and β=0\beta=0.

IV.3 Marginal velocity distribution functions

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Figure 7: Ratios of marginal distribution functions (a) Rc(c)=ϕc(c)/ϕc,M(c)R_{c}(c)=\phi_{c}(c)/\phi_{c,M}(c), (b) Rw(w)=ϕw(w)/ϕw,M(w)R_{w}(w)=\phi_{w}(w)/\phi_{w,M}(w), (c) Rcw(c2w2)=ϕcw(c2w2)/ϕcw,M(c2w2)R_{cw}(c^{2}w^{2})=\phi_{cw}(c^{2}w^{2})/\phi_{cw,M}(c^{2}w^{2}), (d) R𝐜𝐰((𝐜𝐰)2)=ϕ𝐜𝐰((𝐜𝐰)2)/ϕ𝐜𝐰,M((𝐜𝐰)2)R_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})=\phi_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})/\phi_{\mathbf{c}\cdot\mathbf{w},M}((\mathbf{c}\cdot\mathbf{w})^{2}), and (e) Rϑ(cos2ϑ)=ϕϑ(cos2ϑ)/ϕϑ,M(cos2ϑ)R_{\vartheta}(\cos^{2}\vartheta)=\phi_{\vartheta}(\cos^{2}\vartheta)/\phi_{\vartheta,M}(\cos^{2}\vartheta) for α=0.9\alpha=0.9 and β=0\beta=0. Symbols stand for DSMC results and lines for the Sonine approximation theory [see Eqs. (39)].

The four fourth-degree cumulants a20(0)a_{20}^{(0)}, a02(0)a_{02}^{(0)}, a11(0)a_{11}^{(0)}, and a00(1)a_{00}^{(1)} encapsulate the basic piece of information about the deviations of the true velocity distribution function ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) from the (two-temperature) Maxwellian ϕM(c,w)=π3exp(c2w2)\phi_{M}(c,w)=\pi^{-3}\exp(-c^{2}-w^{2}). On the other hand, it seems interesting to perform a more direct comparison between ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) and ϕM(c,w)\phi_{M}(c,w) and assess to what extent ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) can be represented by the truncated Sonine expansion (38). Given that ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) depends on the three quantities c2c^{2}, w2w^{2}, and (𝐜𝐰)2(\mathbf{c}\cdot\mathbf{w})^{2} (or, analogously, cos2ϑ\cos^{2}\vartheta), a plot of ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}), or of the ratio ϕ(𝐜,𝐰)/ϕM(c,w)\phi(\mathbf{c},\mathbf{w})/\phi_{M}(c,w), would require a four-dimensional space. Therefore, it is convenient to analyze instead the projections of ϕ(𝐜,𝐰)\phi(\mathbf{c},\mathbf{w}) represented by the five marginal distributions (33).

Figure 7 displays the ratios Rc(c)=ϕc(c)/ϕc,M(c)R_{c}(c)=\phi_{c}(c)/\phi_{c,M}(c), Rw(w)=ϕw(w)/ϕw,M(w)R_{w}(w)=\phi_{w}(w)/\phi_{w,M}(w), Rcw(c2w2)=ϕcw(c2w2)/ϕcw,M(c2w2)R_{cw}(c^{2}w^{2})=\phi_{cw}(c^{2}w^{2})/\phi_{cw,M}(c^{2}w^{2}), R𝐜𝐰((𝐜𝐰)2)=ϕ𝐜𝐰((𝐜𝐰)2)/ϕ𝐜𝐰,M((𝐜𝐰)2)R_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})=\phi_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2})/\phi_{\mathbf{c}\cdot\mathbf{w},M}((\mathbf{c}\cdot\mathbf{w})^{2}), and Rϑ(cos2ϑ)=ϕϑ(cos2ϑ)/ϕϑ,M(cos2ϑ)R_{\vartheta}(\cos^{2}\vartheta)=\phi_{\vartheta}(\cos^{2}\vartheta)/\phi_{\vartheta,M}(\cos^{2}\vartheta) for the representative system α=0.9\alpha=0.9, β=0\beta=0. As we saw from Fig. 3(c), at this value of the coefficient of normal restitution β\beta the magnitudes of all the cumulants, except the translational kurtosis a20(0)a_{20}^{(0)} are close to their maxima for α=0.9\alpha=0.9. As can be observed from Fig. 7(a), although the Sonine approximation predicts very accurately the small value of a20(0)a_{20}^{(0)} (a20(0)=0.00144a_{20}^{(0)}=0.00144 versus the DSMC value 0.001370.00137), the function Rc(c)R_{c}(c) is only qualitatively captured by Eq. (39a). In particular, the high-velocity tail of Rc(c)R_{c}(c) (for c2.5c\gtrsim 2.5) is higher than predicted by the Sonine approximation. In contrast, even though the Sonine approximation overestimates the rotational kurtosis by about 12% (a02(0)=0.0343a_{02}^{(0)}=0.0343 versus the DSMC value 0.03050.0305), Fig. 7(b) shows that the predicted function Rw(w)R_{w}(w) is rather accurate up to w3.4w\simeq 3.4, where Rw(w)R_{w}(w) reaches values as high as 2.52.5. Again, however, the high-velocity tail of Rw(w)R_{w}(w) is more overpopulated than the Sonine prediction. In fact, the high-velocity tails of the velocity distribution, which typically do not influence the first few cumulants, are not expected to be accounted for by any truncated Sonine expansion.

Now, we turn to the three marginal distribution functions related to the translational-rotational correlations. Figure 7(c) shows that small (c2w20.56c^{2}w^{2}\lesssim 0.56) and large (c2w26.15c^{2}w^{2}\gtrsim 6.15) values of c2w2c^{2}w^{2} are more probable than it might be expected from the Maxwellian distribution. This phenomenon is well described by the Sonine approximation (39b), although some differences are observed around the minimum of Rcw(c2w2)R_{cw}(c^{2}w^{2}). Anyway, the error in c2w294\langle c^{2}w^{2}\rangle-\frac{9}{4} is less than 3% (94a11(0)=0.162\frac{9}{4}a_{11}^{(0)}=0.162 versus the DSMC value 0.1670.167). According to Fig.  7(d), most of the values of (𝐜𝐰)2(\mathbf{c}\cdot\mathbf{w})^{2} within the “thermal” range are less probable than the Maxwellian expectations. This agrees with a negative value of (𝐜𝐰)234\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle-\frac{3}{4}, which is very well described by the Sonine approximation (34a11(0)+158a00(11)=0.0518\frac{3}{4}a_{11}^{(0)}+\frac{15}{8}a_{00}^{(11)}=-0.0518 versus the DSMC value 0.0520-0.0520). Note that the positive value of a11(0)a_{11}^{(0)} (i.e., c2w2>c2w2\langle c^{2}w^{2}\rangle>\langle c^{2}\rangle\langle w^{2}\rangle) is dominated by a negative value of 52a00(1)\frac{5}{2}a_{00}^{(1)} (i.e., 3(𝐜𝐰)2<c2w23\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle<\langle c^{2}w^{2}\rangle), resulting in 3(𝐜𝐰)2<c2w2<c2w23\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle<\langle c^{2}\rangle\langle w^{2}\rangle<\langle c^{2}w^{2}\rangle. Obviously, in order to preserve normalization, R𝐜𝐰((𝐜𝐰)2)R_{\mathbf{c}\cdot\mathbf{w}}((\mathbf{c}\cdot\mathbf{w})^{2}) must be larger than unity for values of (𝐜𝐰)2(\mathbf{c}\cdot\mathbf{w})^{2} higher than those considered in our DSMC simulations (according to the Sonine approximation, this would happen for (𝐜𝐰)2>19.26(\mathbf{c}\cdot\mathbf{w})^{2}>19.26), but they do not affect the sign of (𝐜𝐰)234\langle(\mathbf{c}\cdot\mathbf{w})^{2}\rangle-\frac{3}{4}. Finally, Fig. 7(e) confirms the lifted-tennis-ball effect, i.e., the values of cos2ϑ\cos^{2}\vartheta smaller than about 13\frac{1}{3} are more probable than one could expect from a Maxwellian distribution, so that cos2ϑ13=310b<0\langle\cos^{2}\vartheta\rangle-\frac{1}{3}=\frac{3}{10}b<0. The Sonine approximation predicts the former difference within an error smaller than 5% (310b=0.0169\frac{3}{10}b=-0.0169 versus the DSMC value 0.0177-0.0177). Apart from the average value cos2ϑ\langle\cos^{2}\vartheta\rangle, the Sonine approximation (39d) describes rather accurately the whole distribution Rϑ(cos2ϑ)R_{\vartheta}(\cos^{2}\vartheta), as Fig. 7(e) shows.

V Conclusion

We have developed in this work a kinetic theory for a dilute granular gas of rough hard spheres that is heated by a uniform stochastic volume force. Our theory is based on a Sonine polynomial expansion of the granular gas distribution function around the Maxwellian. Thus, we obtain a numerical solution of the velocity distribution function at all times and an analytical solution for the uniform steady state that is reached after a relatively short relaxation time. We have tested our theoretical approach against DSMC data, obtaining a very good agreement between simulation and theory.

Contrary to the results for a freely cooling granular gas of rough spheres in a recent work,Vega Reyes, Santos, and Kremer (2014) the cumulants of the distribution function reach low values (always below 0.10.1, as measured from simulations and theory) and thus our theoretical approach works in the whole range of inelasticity and roughness values. In other words, it would not be necessary for the heated granular gas to add higher order terms in the truncated Sonine expansion that we have considered, as done in recent works on the HCS for inelastic rough spheres.Rongali and Alam (2014) Also, thanks to the existence of a true steady state (where inelastic cooling and external heating balance each other), the quasismooth limit β1\beta\to-1 is regular and thus the results for purely smooth spheres (β=1\beta=-1) are recovered in that limit. Again, this differs from the situation in the HCS.Brilliantov et al. (2007); Kranz et al. (2009); Vega Reyes, Santos, and Kremer (2014)

Another relevant result for the heated granular gas is that the translations and rotations in particles, although still correlated as in the HCS,Brilliantov et al. (2007) show a very mince cannon-ball effect region and this effect completely disappears from the nearly-smooth region, appearing only near the completely elastic and rough limit. This is in contrast with the behavior in the HCS, where two neat cannon-ball regions may be found.Brilliantov et al. (2007); Kranz et al. (2009); Rongali and Alam (2014)

Summarizing, the white noise force has an effect of making the distribution function more similar to the Maxwellian for the whole range of coefficients of normal and tangential restitution. Since our Sonine expansion is done around the Maxwellian we expect the theoretical solution that we provide in this work to be an accurate description and a reference for researchers interested in the description of the transport properties of a heated granular gas of rough spheres.

Acknowledgements.
The authors acknowledge support from the Spanish Government through Grant No. FIS2013-42840-P and from the Regional Government of Extremadura (Spain) through Grant No. GR15104 (partially financed by the European Regional Development Fund, ERDF). Computing facilities from Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the ERDF, are gratefully acknowledged.

*

Appendix A Collisional moments

We write in this Appendix the Sonine-approximation expressions of the collisional moments μpq(2r)\mu_{pq}^{(2r)} (with p+q+2r=2p+q+2r=2 and 44) as linear functions of the cumulants ajk()a_{jk}^{(\ell)} (with j+k+2=2j+k+2\ell=2) and nonlinear functions of the temperature ratio θ\theta. Those expressions, where we we make use of the parameters (5), are

μ20(0)=4[α~(1α~)+β~(1β~)](1+3a20(0)16)4β~2θκ(1a20(0)16+2a11(0)a00(1)8),{\mu_{20}^{(0)}}={4\left[\widetilde{\alpha}\left(1-\widetilde{\alpha}\right)+\widetilde{\beta}\left(1-\widetilde{\beta}\right)\right]\left(1+\frac{3a_{20}^{(0)}}{16}\right)}{-\frac{4\widetilde{\beta}^{2}\theta}{\kappa}\left(1-\frac{a_{20}^{(0)}}{16}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)}, (42)
μ02(0)=4β~κ[(1β~κ)(1a20(0)16+2a11(0)a00(1)8)β~θ(1+3a20(0)16)],\mu_{02}^{(0)}=\frac{4\widetilde{\beta}}{\kappa}\left[\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\left(1-\frac{a_{20}^{(0)}}{16}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)-\frac{\widetilde{\beta}}{\theta}\left(1+\frac{3a_{20}^{(0)}}{16}\right)\right], (43)
μ40(0)\displaystyle\mu_{40}^{(0)} =\displaystyle= 16[α~3(2α~)+β~3(2β~)α~β~(1α~β~+α~β~)]+22(α~+β~)\displaystyle 16\left[\widetilde{\alpha}^{3}\left(2-\widetilde{\alpha}\right)+\widetilde{\beta}^{3}\left(2-\widetilde{\beta}\right)-\widetilde{\alpha}\widetilde{\beta}\left(1-\widetilde{\alpha}-\widetilde{\beta}+\widetilde{\alpha}\widetilde{\beta}\right)\right]+22\left(\widetilde{\alpha}+\widetilde{\beta}\right) (44)
38(α~2+β~2)15[α~β~(2315α~β~+α~β~)269120(α~+β~)+357120(α~2+β~2)\displaystyle-38\left(\widetilde{\alpha}^{2}+\widetilde{\beta}^{2}\right)-15\Bigg{[}\widetilde{\alpha}\widetilde{\beta}\left(\frac{23}{15}-\widetilde{\alpha}-\widetilde{\beta}+\widetilde{\alpha}\widetilde{\beta}\right)-\frac{269}{120}\left(\widetilde{\alpha}+\widetilde{\beta}\right)+\frac{357}{120}\left(\widetilde{\alpha}^{2}+\widetilde{\beta}^{2}\right)
α~3(2α~)β~3(2β~)]a20(0)22β~2θκ(1+41a20(0)176+32a11(0)a00(1)8)\displaystyle-\widetilde{\alpha}^{3}\left(2-\widetilde{\alpha}\right)-\widetilde{\beta}^{3}\left(2-\widetilde{\beta}\right)\Bigg{]}a_{20}^{(0)}-\frac{22\widetilde{\beta}^{2}\theta}{\kappa}\left(1+\frac{41a_{20}^{(0)}}{176}+3\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)
+16β~2θκ[α~(1α~)+2β~(1β~)](1+3a20(0)16+32a11(0)a00(1)8)\displaystyle+\frac{16\widetilde{\beta}^{2}\theta}{\kappa}\left[\widetilde{\alpha}\left(1-\widetilde{\alpha}\right)+2\widetilde{\beta}\left(1-\widetilde{\beta}\right)\right]\left(1+\frac{3a_{20}^{(0)}}{16}+3\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)
16β~4θ2κ2(1a20(0)16+a02(0)2+2a11(0)a00(1)4),\displaystyle-\frac{16\widetilde{\beta}^{4}\theta^{2}}{\kappa^{2}}\left(1-\frac{a_{20}^{(0)}}{16}+\frac{a_{02}^{(0)}}{2}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{4}\right),
μ22(0)\displaystyle\mu_{22}^{(0)} =\displaystyle= 6[α~(1α~)+β~(1β~)4α~β~3κ(1α~)(1β~κ)8β~23κ(34β~β~κ+2β~2κ)]\displaystyle 6\left[\widetilde{\alpha}\left(1-\widetilde{\alpha}\right)+\widetilde{\beta}\left(1-\widetilde{\beta}\right)-\frac{4\widetilde{\alpha}\widetilde{\beta}}{3\kappa}\left(1-\widetilde{\alpha}\right)\left(1-\frac{\widetilde{\beta}}{\kappa}\right)-\frac{8\widetilde{\beta}^{2}}{3\kappa}\left(\frac{3}{4}-\widetilde{\beta}-\frac{\widetilde{\beta}}{\kappa}+2\frac{\widetilde{\beta}^{2}}{\kappa}\right)\right] (45)
×(1+3a20(0)16+32a11(0)a00(1)8)+7β~κ(1β~κ)(1+29a20(0)112)3β~22κθa20(0)\displaystyle\times\left(1+\frac{3a_{20}^{(0)}}{16}+3\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)+\frac{7\widetilde{\beta}}{\kappa}\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\left(1+\frac{29a_{20}^{(0)}}{112}\right)-\frac{3\widetilde{\beta}^{2}}{2\kappa\theta}a_{20}^{(0)}
8β~2κθ[98α~(1α~)2β~(1β~)](1+15a20(0)16)β~2θκ[58β~κ(1β~κ)]a02(0)\displaystyle-\frac{8\widetilde{\beta}^{2}}{\kappa\theta}\left[\frac{9}{8}-\widetilde{\alpha}\left(1-\widetilde{\alpha}\right)-2\widetilde{\beta}\left(1-\widetilde{\beta}\right)\right]\left(1+\frac{15a_{20}^{(0)}}{16}\right)-\frac{\widetilde{\beta}^{2}\theta}{\kappa}\left[5-8\frac{\widetilde{\beta}}{\kappa}\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\right]a_{02}^{(0)}
8β~2θκ[12β~κ(1β~κ)](1a20(0)16+2a11(0)a00(1)4)+3[β~κ(37122β~7β~4κ)\displaystyle-\frac{8\widetilde{\beta}^{2}\theta}{\kappa}\left[1-2\frac{\widetilde{\beta}}{\kappa}\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\right]\left(1-\frac{a_{20}^{(0)}}{16}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{4}\right)+3\Bigg{[}\frac{\widetilde{\beta}}{\kappa}\left(\frac{37}{12}-2\widetilde{\beta}-\frac{7\widetilde{\beta}}{4\kappa}\right)
+α~+β~4α~β~3κ]2a11(0)a00(1)2+[5(α~+β~)3(α~2+β~2)+4β~κ(1β~)\displaystyle+\widetilde{\alpha}+\widetilde{\beta}-\frac{4\widetilde{\alpha}\widetilde{\beta}}{3\kappa}\Bigg{]}\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{2}{+\Bigg{[}5\left(\widetilde{\alpha}+\widetilde{\beta}\right)-3\left(\widetilde{\alpha}^{2}+\widetilde{\beta}^{2}\right)}{+\frac{4\widetilde{\beta}}{\kappa}\left(1-\widetilde{\beta}\right)}
β~2κ2(2+κθ)]3a00(1)4,\displaystyle{-\frac{\widetilde{\beta}^{2}}{\kappa^{2}}\left(2+\kappa\theta\right)\Bigg{]}\frac{3a_{00}^{(1)}}{4}},
μ04(0)\displaystyle\mu_{04}^{(0)} =\displaystyle= β~κ{4(1β~κ)[54β~κ(1β~κ)](1a20(0)16)4β~θ[58β~κ(1β~κ)]\displaystyle\frac{\widetilde{\beta}}{\kappa}\left\{4\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\left[5-4\frac{\widetilde{\beta}}{\kappa}\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\right]\left(1-\frac{a_{20}^{(0)}}{16}\right)-\frac{4\widetilde{\beta}}{\theta}\left[5-8\frac{\widetilde{\beta}}{\kappa}\left(1-\frac{\widetilde{\beta}}{\kappa}\right)\right]\right. (46)
×(1+3a20(0)16+32a11(0)a00(1)8)5(14β~5κ)(2a11(0)a00(1))16β~3κθ2(1+15a20(0)16)\displaystyle\times\left(1+\frac{3a_{20}^{(0)}}{16}+3\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{8}\right)-{5}\left(1-\frac{4\widetilde{\beta}}{5\kappa}\right)\left({2a_{11}^{(0)}{-a_{00}^{(1)}}}\right)-\frac{16\widetilde{\beta}^{3}}{\kappa\theta^{2}}\left(1+\frac{15a_{20}^{(0)}}{16}\right)
+4(5132β~κ+4β~2κ22β~3κ3)(a02(0)+2a11(0)a00(1)2)+(1β~κβ~θ)3a00(1)2},\displaystyle\left.+4\left(5-\frac{13}{2}\frac{\widetilde{\beta}}{\kappa}+4\frac{\widetilde{\beta}^{2}}{\kappa^{2}}-2\frac{\widetilde{\beta}^{3}}{\kappa^{3}}\right)\left(a_{02}^{(0)}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{2}\right){+\left(1-\frac{\widetilde{\beta}}{\kappa}-\frac{\widetilde{\beta}}{\theta}\right)\frac{3a_{00}^{(1)}}{2}}\right\},
μ00(2)\displaystyle{\mu_{00}^{(2)}} =\displaystyle= 2[α~(1α~)β~2(1+1κ2)](1+3a20(0)16+3a11(0)4+3a00(1)4)+α~(a11(0)+4a00(1))\displaystyle 2\left[\widetilde{\alpha}\left(1-\widetilde{\alpha}\right)-\widetilde{\beta}^{2}\left(1+\frac{1}{\kappa^{2}}\right)\right]\left(1+\frac{3a_{20}^{(0)}}{16}+\frac{3a_{11}^{(0)}}{4}+\frac{3a_{00}^{(1)}}{4}\right)+{\widetilde{\alpha}}\left(a_{11}^{(0)}+4a_{00}^{(1)}\right) (47)
+2β~(1+1β~κ)(1+3a20(0)16+5a11(0)4+13a00(1)8)+3β~(34α~)(1+1κ)a00(1)\displaystyle+2\widetilde{\beta}\left(1+\frac{1-\widetilde{\beta}}{\kappa}\right)\left(1+\frac{3a_{20}^{(0)}}{16}+\frac{5a_{11}^{(0)}}{4}+\frac{13a_{00}^{(1)}}{8}\right)+3\widetilde{\beta}\left(\frac{3}{4}-\widetilde{\alpha}\right)\left(1+\frac{1}{\kappa}\right){a_{00}^{(1)}}
β~2κθ(1+7a20(0)16)β~2θκ(1a20(0)16+2a11(0)a00(1)4).\displaystyle-\frac{\widetilde{\beta}^{2}}{\kappa\theta}\left(1+\frac{7a_{20}^{(0)}}{16}\right)-\frac{\widetilde{\beta}^{2}\theta}{\kappa}\left(1-\frac{a_{20}^{(0)}}{16}+\frac{2a_{11}^{(0)}{-a_{00}^{(1)}}}{4}\right).

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