Citation: Fei Cao, Sebastien Motsch, Alexander Reamy, Ryan Theisen. Asymptotic flocking for the three-zone model[J]. Mathematical Biosciences and Engineering, 2020, 17(6): 7692-7707. doi: 10.3934/mbe.2020391
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The classical beta function
B(δ1,δ2)=∞∫0tδ1−1(1−t)δ2−1dt,(ℜ(δ1)>0,ℜ(δ2)>0) | (1.1) |
and its relation with well known gamma function is given by
B(δ1,δ2)=Γ(δ1)Γ(δ2)Γ(δ1+δ2),ℜ(δ1)>0,ℜ(δ2)>0. |
The Gauss hypergeometric, confluent hypergeometric and Appell's functions which are respectively defined by(see [27])
2F1(δ1,δ2;δ3;z)=∞∑n=0(δ1)n(δ2)n(δ3)nznn!,(|z|<1), (δ1,δ2,δ3∈C and δ3≠0,−1,−2,−3,⋯), | (1.2) |
and
1Φ1(δ2;δ3;z)=∞∑n=0(δ2)n(δ3)nznn!,(|z|<1), (δ2,δ3∈C and δ3≠0,−1,−2,−3,⋯). | (1.3) |
The Appell's series or bivariate hypergeometric series is defined by
F1(δ1,δ2,δ3;δ4;x,y)=∞∑m,n=0(δ1)m+n(δ2)m(δ3)nxmyn(δ4)m+nm!n!; | (1.4) |
for all δ1,δ2,δ3,δ4∈C,δ4≠0,−1,−2,−3,⋯,|x|,|y|<1<1.
The integral representation of hypergeometric, confluent hypergeometric and Appell's functions are respectively defined by
2F1(δ1,δ2;δ3;z)=Γ(δ3)Γ(δ2)Γ(δ3−δ2)∫10tδ2−1(1−t)δ3−δ2−1(1−zt)−δ1dt, | (1.5) |
(ℜ(δ3)>ℜ(δ2)>0,|arg(1−z)|<π), |
and
1Φ1(δ2;δ3;z)=Γ(δ3)Γ(δ2)Γ(δ3−δ2)∫10tδ2−1(1−t)δ3−δ2−1eztdt, | (1.6) |
(ℜ(δ3)>ℜ(δ2)>0). |
F1(δ1,δ2,δ3;δ4;x,y)=Γ(δ4)Γ(δ1)Γ(δ4−δ1)1∫0tδ1−1(1−t)δ4−δ1−1(1−xt)−δ2(1−yt)−δ3dt. | (1.7) |
The k-gamma function, k-beta function and the k-Pochhammer symbol introduced and studied by Diaz and Pariguan [5]. The integral representation of k-gamma function and k-beta function respectively given by
Γk(z)=kzk−1Γ(zk)=∞∫0tz−1e−zkkdt,ℜ(z)>0,k>0 | (1.8) |
Bk(x,y)=1k1∫0txk−1(1−t)yk−1dt,ℜ(x)>0,ℜ(y)>0. | (1.9) |
Here, we recall the following relations (see [5]).
Bk(x,y)=Γk(x)Γk(y)Γk(x+y), | (1.10) |
(z)n,k=Γk(z+nk)Γk(z), | (1.11) |
where (z)n,k=(z)(z+k)(z+2k)⋯(z+(n−1)k);(z)0,k=1 and k>0
and
∞∑n=0(α)n,kznn!=(1−kz)−αk. | (1.12) |
These studies were followed by Mansour [16], Kokologiannaki [13], Krasniqi [14] and Merovci [17]. In 2012, Mubeen and Habibullah [18] defined the k-hypergeometric function as
2F1,k(δ1,δ2;δ3;z)=∞∑n=0(δ1)n,k(δ2)n,k(δ3)n,kznn!, | (1.13) |
where δ1,δ2,δ3∈C and δ3≠0,−1,−2,⋯ and its integral representation is given by
2F1,k(δ1,δ2;δ3;z)=1kBk(δ2,δ3−δ2)×∫10tδ2k−1(1−t)δ3−δ2k−1(1−ktz)−δ1kdt. | (1.14) |
The k-Riemann-Liouville (R-L) fractional integral using k-gamma function introduced in [19]:
(Iαkf(t))(x)=1kΓk(α)∫x0f(t)(x−t)αk−1dt,k,α∈R+. | (1.15) |
Later on Mubeen and Iqbal [11] established the improved version of Gruss type inequalities by utilizing k-fractional integrals. In [1], Agarwal et al. presented certain Hermite-Hadamard type inequalities for generalized k-fractional integrals. Set et al. [29] presented an integral identity and generalized Hermite–Hadamard type inequalities for Riemann–Liouville fractional integral. Mubeen et al. [24] established integral inequalities of Ostrowski type for k-fractional Riemann–Liouville integrals. Recently, many researchers have introduced generalized version of k-fractional integrals and investigated a large bulk of various inequalities via the said fractional integrals. The interesting readers are referred to see the work of [9,10,26,30]. Farid et al. [7] introduced Hadamard k-fractional integrals. In [8] introduced Hadamard-type inequalities for k-fractional Riemann-Liouville integrals. In [12,31], the authors established certain inequalities by utilizing Hadamard-type inequalities for k-fractional Riemann-Liouville integrals. In [25], Nisar et al. established certain Gronwall type inequalities associated with Riemann-Liouville k- and Hadamard k-fractional derivatives and their applications. In [25], they presented dependence solutions of certain k-fractional differential equations of arbitrary real order with initial conditions. Recently, Samraiz et al. [28] defined an extension of Hadamard k-fractional derivative and proved its various properties.
The solution of some integral equations involving confluent k-hypergeometric functions and k-analogue of Kummer's first formula are given in [22,23]. While the k-hypergeometric and confluent k-hypergeometric differential equations are introduced in [20]. In 2015, Mubeen et al. [21] introduced k-Appell hypergeometric function as
F1,k(δ1,δ2,δ3;δ4;z1,z2)=∞∑m,n=0(δ1)m+n,k(δ2)m,k(δ3)m,k(δ4)m+n,kzm1zn2m!n! | (1.16) |
for all δ1,δ2,δ3,δ4∈C,δ4≠0,−1,−2,−3,⋯,max{|z1|,|z2|}<1k and k>0. Also, Mubeen et al. defined its integral representation as
F1,k(δ1,δ2,δ3;δ4;z1,z2)=1kBk(δ1,δ4−δ1)1∫0tδ1k−1(1−t)δ4−δ1k−1(1−kz1t)−δ2k(1−kz2t)−δ3kdt, | (1.17) |
(ℜ(δ4)>ℜ(δ1)>0). |
In this section, we recall the following definition of fractional derivatives from and give a new extension called Riemann-Liouville k-fractional derivative.
Definition 2.1. The well-known R-L fractional derivative of order μ is defined by
Dμx{f(x)}=1Γ(−μ)∫x0f(t)(x−t)−μ−1dt,ℜ(μ)<0. | (2.1) |
For the case m−1<ℜ(μ)<m where m=1,2,⋯, it follows
Dμx{f(x)}=dmdxmDμ−mx{f(x)}=dmdxm{1Γ(−μ+m)∫x0f(t)(x−t)−μ+m−1dt}. | (2.2) |
For further study and applications, we refer the readers to the work of [2,3,4,15,32]. In the following, we define Riemann-Liouville k-fractional derivative of order μ as
Definition 2.2.
kDμx{f(x)}=1kΓk(−μ)∫x0f(t)(x−t)−μk−1dt,ℜ(μ)<0,k∈R+. | (2.3) |
For the case m−1<ℜ(μ)<m where m=1,2,⋯, it follows
kDμx{f(x)}=dmdxmkDμ−mkx{f(x)}=dmdxm{1kΓk(−μ+mk)∫x0f(t)(x−t)−μk+m−1dt}. | (2.4) |
Note that for k=1, definition 2.2 reduces to the classical R-L fractional derivative operator given in definition 2.1.
Now, we are ready to prove some theorems by using the new definition 2.2.
Theorem 1. The following formula holds true,
kDμz{zηk}=zη−μkΓk(−μ)Bk(η+k,−μ),ℜ(μ)<0. | (2.5) |
Proof. From (2.3), we have
kDμz{zηk}=1kΓk(−μ)∫z0tηk(z−t)−μk−1dt. | (2.6) |
Substituting t=uz in (2.6), we get
kDμz{zηk}=1kΓk(−μ)∫10(uz)ηk(z−uz)−μk−1zdu=zη−μkkΓk(−μ)∫10uηk(1−u)−μk−1du. |
Applying definition (1.9) to the above equation, we get the desired result.
Theorem 2. Let ℜ(μ)>0 and suppose that the function f(z) is analytic at the origin with its Maclaurin expansion given by f(z)=∑∞n=0anzn where |z|<ρ for some ρ∈R+. Then
kDμz{f(z)}=∞∑n=0ankDμz{zn}. | (2.7) |
Proof. Using the series expansion of the function f(z) in (2.3) gives
kDμz{f(z)}=1kΓk(−μ)∫z0∞∑n=0antn(z−t)−μk−1dt. |
As the series is uniformly convergent on any closed disk centered at the origin with its radius smaller then ρ, therefore the series so does on the line segment from 0 to a fixed z for |z|<ρ. Thus it guarantee terms by terms integration as follows
kDμz{f(z)}=∞∑n=0an{1kΓk(−μ)∫z0tn(z−t)−μk−1dt=∞∑n=0ankDμz{zn}, |
which is the required proof.
Theorem 3. The following result holds true:
kDη−μz{zηk−1(1−kz)−βk}=Γk(η)Γk(μ)zμk−12F1,k(β,η;μ;z), | (2.8) |
where ℜ(μ)>ℜ(η)>0 and |z|<1.
Proof. By direct calculation, we have
kDη−μz{zηk−1(1−kz)−βk}=1kΓk(μ−η)∫z0tηk−1(1−kt)−βk(z−t)μ−ηk−1dt=zμ−ηk−1kΓk(μ−η)∫z0tηk−1(1−kt)−βk(1−tz)μ−ηk−1dt. |
Substituting t=zu in the above equation, we get
kDη−μz{zηk−1(1−kz)−βk}=zμk−1kΓk(μ−η)∫10uηk−1(1−kuz)−βk(1−u)μ−ηk−1zdu. |
Applying (1.14) and after simplification we get the required proof.
Theorem 4. The following result holds true:
kDη−μz{zηk−1(1−kaz)−αk(1−kbz)−βk}=Γk(η)Γk(μ)zμk−1F1,k(η,α,β;μ;az,bz), | (2.9) |
where ℜ(μ)>ℜ(η)>0, ℜ(α)>0, ℜ(β)>0, max{|az|,|bz|}<1k.
Proof. To prove (2.9), we use the power series expansion
(1−kaz)−αk(1−kbz)−βk=∞∑m=0∞∑n=0(α)m,k(β)n,k(az)mm!(bz)nn!. |
Now, applying Theorem 1, we obtain
kDη−μz{zηk−1(1−kaz)−αk(1−kbz)−βk}=∞∑m=0∞∑n=0(α)m,k(β)n,k(a)mm!(b)nn!kDη−μz{zηk+m+n−1}=∞∑m=0∞∑n=0(α)m,k(β)n,k(a)mm!(b)nn!βk(η+mk+nk,μ−η)Γk(μ−η)zμk+m+n−1=∞∑m=0∞∑n=0(α)m,k(β)n,k(a)mm!(b)nn!Γk(η+mk+nk)Γk(μ+mk+nk)zμk+m+n−1. |
In view of (1.16), we get
kDη−μz{zηk−1(1−kaz)−αk(1−kbz)−βk}=Γk(η)Γk(μ)zμk−1F1,k(η,α,β;μ;az,bz). |
Theorem 5. The following Mellin transform formula holds true:
M{e−xkDμz(zηk);s}=Γ(s)Γk(−μ)Bk(η+k,−μ)zη−μk, | (2.10) |
where ℜ(η)>−1, ℜ(μ)<0, ℜ(s)>0.
Proof. Applying the Mellin transform on definition (2.3), we have
M{e−xkDμz(zηk);s}=∫∞0xs−1e−xkDμz(zη);s}dx=1kΓk(−μ)∫∞0xs−1e−x{∫z0tηk(z−t)−μk−1dt}dx=z−μk−1kΓk(−μ)∫∞0xs−1e−x{∫z0tηk(1−tz)−μk−1dt}dx=zη−μkkΓk(−μ)∫∞0xs−1e−x{∫10uηk(1−u)−μk−1du}dx |
Interchanging the order of integrations in above equation, we get
M{e−xkDμz(zηk);s}=zη−μkkΓk(−μ)∫10uηk(1−u)−μk−1(∫∞0xs−1e−xdx)du.=zη−μkkΓk(−μ)Γ(s)∫10uηk(1−u)−μk−1du=Γ(s)Γk(−μ)Bk(η+k,−μ)zη−μk, |
which completes the proof.
Theorem 6. The following Mellin transform formula holds true:
M{e−xkDμz((1−kz)−αk);s}=z−μkΓ(s)Γk(−μ)Bk(k,−μ)2F1,k(α,k;−μ+k;z), | (2.11) |
where ℜ(α)>0, ℜ(μ)<0, ℜ(s)>0, and |z|<1.
Proof. Using the power series for (1−kz)−αk and applying Theorem 5 with η=nk, we can write
M{e−xkDμz((1−kz)−αk);s}=∞∑n=0(α)n,kn!M{e−xkDμz(zn);s}=Γ(s)kΓk(−μ)∞∑n=0(α)n,kn!Bk(nk+k,−μ)zn−μk=Γ(s)z−μkΓk(−μ)∞∑n=0Bk(nk+k,−μ)(α)n,kznn!=Γ(s)z−μk∞∑n=0Γk(k+nk)Γk(−μ+k+nk)(α)n,kznn!=Γ(s)Γk(−μ+k)z−μk∞∑n=0(k)n,k(−μ+k)n,k(α)n,kznn!=Γ(s)z−μkΓk(−μ)Bk(k,−μ)2F1,k(α,k;−μ+k;z), |
which is the required proof.
Theorem 7. The following result holds true:
kDη−μz[zηk−1Eμk,γ,δ(z)]=zμk−1kΓk(μ−η)∞∑n=0(μ)n,kΓk(γn+δ)Bk(η+nk,μ−η)znn!, | (2.12) |
where γ,δ,μ∈C, ℜ(p)>0, ℜ(q)>0, ℜ(μ)>ℜ(η)>0 and Eμk,γ,δ(z) is k-Mittag-Leffler function (see [6]) defined as:
Eμk,γ,δ(z)=∞∑n=0(μ)n,kΓk(γn+δ)znn!. | (2.13) |
Proof. Using (2.13), the left-hand side of (2.12) can be written as
kDη−μz[zηk−1Eμk,γ,δ(z)]=kDη−μz[zηk−1{∞∑n=0(μ)n,kΓk(γn+δ)znn!}]. |
By Theorem 2, we have
kDη−μz[zηk−1Eμk,γ,δ(z)]=∞∑n=0(μ)n,kΓk(γn+δ){kDμz[zηk+n−1]}. |
In view of Theorem 1, we get the required proof.
Theorem 8. The following result holds true:
kDη−μz{zηk−1mΨn[(αi,Ai)1,m;|z(βj,Bj)1,n;]}=zμk−1kΓk(μ−η)×∞∑n=0∏mi=1Γ(αi+Ain)∏nj=1Γ(βj+BjnBk(η+nk,μ−η)znn!, | (2.14) |
where ℜ(p)>0, ℜ(q)>0, ℜ(μ)>ℜ(η)>0 and mΨn(z) is the Fox-Wright function defined by (see [15], pages 56–58)
mΨn(z)=mΨn[(αi,Ai)1,m;|z(βj,Bj)1,n;]=∞∑n=0∏mi=1Γ(αi+Ain)∏nj=1Γ(βj+Bjnznn!. | (2.15) |
Proof. Applying Theorem 1 and followed the same procedure used in Theorem 7, we get the desired result.
Recently, many researchers have introduced various generalizations of fractional integrals and derivatives. In this line, we have established a k-fractional derivative and its various properties. If we letting k→1 then all the results established in this paper will reduce to the results related to the classical Reimann-Liouville fractional derivative operator.
The author K.S. Nisar thanks to Deanship of Scientific Research (DSR), Prince Sattam bin Abdulaziz University for providing facilities and support.
The authors declare no conflict of interest.
[1] | I. Aoki, A Simulation Study on the Schooling Mechanism in Fish, Bulletin of the Japanese Society of Scientific Fisheries (Japan), 1982. |
[2] |
I. D. Couzin, J. Krause, R. James, G. D Ruxton, N. R. Franks, Collective memory and spatial sorting in animal groups, J. Theor. Biol., 218 (2002), 1-11. doi: 10.1006/jtbi.2002.3065
![]() |
[3] |
A. Huth, C. Wissel, The simulation of the movement of fish schools, J. Theor. Biol., 156 (1992), 365-385. doi: 10.1016/S0022-5193(05)80681-2
![]() |
[4] | Y. X. Li, R. Lukeman, L. Edelstein-Keshet, Minimal mechanisms for school formation in self-propelled particles, Phys. D: Nonlinear Phenomena, 237 (2008), 699-720. |
[5] | C. W. Reynolds, Flocks, herds and schools: A distributed behavioral model, in ACM SIGGRAPH Computer Graphics, (1987), 25-34. |
[6] | F. Cucker, S. Smale, Emergent behavior in flocks, IEEE Trans. Automatic Control, 52 (2007), 852. |
[7] |
F. Cucker, S. Smale, On the mathematics of emergence, Jpn. J. Math., 2 (2007), 197-227. doi: 10.1007/s11537-007-0647-x
![]() |
[8] |
T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, O. Shochet, Novel type of phase transition in a system of self-driven particles, Phys. Rev. Lett., 75 (1995), 1226-1229. doi: 10.1103/PhysRevLett.75.1226
![]() |
[9] |
M. Agueh, R. Illner, A. Richardson, Analysis and simulations of a refined flocking and swarming model of Cucker-Smale type, Kinetic Related Models, 4 (2011), 1-16. doi: 10.3934/krm.2011.4.1
![]() |
[10] |
S. Motsch, E. Tadmor, A new model for self-organized dynamics and its flocking behavior, J. Stat. Phys., 144 (2011), 923-947. doi: 10.1007/s10955-011-0285-9
![]() |
[11] |
S. Motsch, E. Tadmor, Heterophilious dynamics enhances consensus, SIAM Rev., 56 (2014), 577-621. doi: 10.1137/120901866
![]() |
[12] |
J. A. Carrillo, M. Fornasier, J. Rosado, G. Toscani, Asymptotic flocking dynamics for the kinetic Cucker-Smale model, SIAM J. Math. Anal., 42 (2010), 218-236. doi: 10.1137/090757290
![]() |
[13] |
S. Y. Ha, J. G. Liu, A simple proof of the Cucker-Smale flocking dynamics and mean-field limit, Commun. Math. Sci., 7 (2009), 297-325. doi: 10.4310/CMS.2009.v7.n2.a2
![]() |
[14] |
S. Y. Ha, E. Tadmor, From particle to kinetic and hydrodynamic descriptions of flocking, Kinetic Related Models, 1 (2008), 415-435. doi: 10.3934/krm.2008.1.415
![]() |
[15] | J. A. Carrillo, Y. P. Choi, S. Pérez, A review on attractive-repulsive hydrodynamics for consensus in collective behavior, preprint, arXiv: 1605.00232. |
[16] | J. A. Carrillo, Y. Huang, S. Martin, Explicit flock solutions for Quasi-Morse potentials, Eur. J. Appl. Math., (2014), 1-26. |
[17] | J. Von Brecht, D. Uminsky, T. Kolokolnikov, A. Bertozzi, Predicting pattern formation in particle interactions, Math. Models Methods Appl. Sci., 22 (2012). |
[18] |
D. Bakry, P. Cattiaux, A. Guillin, Rate of convergence for ergodic continuous Markov processes: Lyapunov versus Poincaré, J. Funct. Anal., 254 (2008), 727-759. doi: 10.1016/j.jfa.2007.11.002
![]() |
[19] | C. Villani, Hypocoercivity, Memoirs of the American Mathematical Society, 2009. |
[20] |
P. E. Jabin, S. Motsch, Clustering and asymptotic behavior in opinion formation, J. Differ. Equations, 257 (2014), 4165-4187. doi: 10.1016/j.jde.2014.08.005
![]() |
[21] | T. Karper, A. Mellet, K. Trivisa, On strong local alignment in the kinetic Cucker-Smale model, in Hyperbolic Conservation Laws and Related Analysis with Applications, Springer, (2014), 227-242. |
[22] |
J. Haskovec, Flocking dynamics and mean-field limit in the Cucker-Smale-type model with topological interactions, Phys. D: Nonlinear Phenomena, 261 (2013), 42-51. doi: 10.1016/j.physd.2013.06.006
![]() |
[23] | M. Ballerini, N. Cabibbo, R. Candelier, A. Cavagna, E. Cisbani, I. Giardina, et al., Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study, Proceed. Natl. Acad. Sci., 105 (2008), 1232. |
[24] |
A. Blanchet, P. Degond, Topological interactions in a Boltzmann-type framework, J. Stat. Phys., 163 (2016), 41-60. doi: 10.1007/s10955-016-1471-6
![]() |
[25] | J. A. Carrillo, Y. Huang, Explicit Equilibrium solutions for the aggregation equation with power-law potentials, preprint, arXiv: 1602.06615. |
[26] |
R. Fetecau, Y. Huang, T. Kolokolnikov, Swarm dynamics and equilibria for a nonlocal aggregation model, Nonlinearity, 24 (2011), 2681. doi: 10.1088/0951-7715/24/10/002
![]() |
[27] |
T. Kolokolnikov, H. Sun, D. Uminsky, A. Bertozzi, Stability of ring patterns arising from two-dimensional particle interactions, Phys. Rev. E, 84 (2011), 015203. doi: 10.1103/PhysRevE.84.015203
![]() |
[28] | Y. Chuang, M. R. D'Orsogna, D. Marthaler, A. L. Bertozzi, L. S. Chayes, State transitions and the continuum limit for a 2d interacting, self-propelled particle system, Phys. D: Nonlinear Phenomena, 232 (2007), 33-47. |
[29] | M. R. D'Orsogna, Y. L. Chuang, A. L. Bertozzi, L. S. Chayes, Self-propelled particles with soft-core interactions: Patterns, stability, and collapse, Phys. Rev. Lett., 96 (2006), 104302. |
[30] | D. Ruelle, Statistical Mechanics: Rigorous Results. World Scientific, 1969. |
[31] |
D. Balagué, J. A. Carrillo, T. Laurent, G. Raoul, Dimensionality of local minimizers of the Interaction energy, Arch. Rational Mech. Anal., 209 (2013), 1055-1088. doi: 10.1007/s00205-013-0644-6
![]() |
[32] |
L. Desvillettes, C. Villani, On the trend to global equilibrium for spatially inhomogeneous kinetic systems: The Boltzmann equation, Inventiones Math., 159 (2005), 245-316. doi: 10.1007/s00222-004-0389-9
![]() |
[33] |
F. Filbet, On deterministic approximation of the Boltzmann equation in a bounded domain, Multiscale Modell. Simul., 10 (2012), 792-817. doi: 10.1137/11082419X
![]() |
[34] |
F. Bolley, J. A. Canizo, J. A. Carrillo, Stochastic mean-field limit: non-Lipschitz forces and swarming, Math. Models Methods. Appl. Sci., 21 (2011), 2179-2210. doi: 10.1142/S0218202511005702
![]() |
[35] | J. Carrillo, Y. P. Choi, M. Hauray, The derivation of swarming models: mean-field limit and Wasserstein distances, in Collective Dynamics from Bacteria to Crowds, Springer, (2014), 1-46. |
[36] |
P. Degond, G. Dimarco, T. B. N. Mac, N. Wang, Macroscopic models of collective motion with repulsion, Commun. Math. Sci., 13 (2015), 1615-1638. doi: 10.4310/CMS.2015.v13.n6.a12
![]() |
[37] | P. Degond, J. G. Liu, S. Motsch, V. Panferov, Hydrodynamic models of self-organized dynamics: derivation and existence theory, Methods Appl. Anal., 20 (2013), 89-114. |
[38] |
P. Degond, S. Motsch, Continuum limit of self-driven particles with orientation interaction, Math. Models Methods Appl. Sci., 18 (2008), 1193-1215. doi: 10.1142/S0218202508003005
![]() |
[39] |
P. E. Jabin, A review of the mean field limits for Vlasov equations, Kinetic Related Models, 7 (2014), 661-711. doi: 10.3934/krm.2014.7.661
![]() |
[40] | H. Spohn, Large Scale Dynamics of Interacting Particles, Springer, 1991. |
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