Chaos and statistical mechanics in the Hamiltonian mean field model

被引:68
|
作者
Latora, V
Rapisarda, A
Ruffo, S
机构
[1] Univ Florence, Dipartimento Energet S Stecco, I-50139 Florence, Italy
[2] Ist Nazl Fis Nucl, I-50139 Florence, Italy
[3] MIT, Ctr Theoret Phys, Nucl Sci Lab, Cambridge, MA 02139 USA
[4] MIT, Dept Phys, Cambridge, MA 02139 USA
[5] Ist Nazl Fis Nucl, Sez Catania, I-95129 Catania, Italy
[6] Univ Catania, Dipartmento Fis, I-95129 Catania, Italy
来源
PHYSICA D | 1999年 / 131卷 / 1-4期
关键词
Hamiltonian dynamics; equilibrium statistical mechanics; Lyapunov exponents; relaxation to equilibrium;
D O I
10.1016/S0167-2789(98)00217-6
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We study the dynamical and statistical behavior of the Hamiltonian mean field (HMF) model in order to investigate the relation between microscopic chaos and phase transitions. HMF is a simple toy model of N fully coupled rotators which shows a second-order phase transition. The solution in the canonical ensemble is briefly recalled and its predictions are tested numerically at finite N. The Vlasov stationary solution is shown to give the same consistency equation of the canonical solution and its predictions for rotator angle and momenta distribution functions agree very well with numerical simulations, A link is established between the behavior of the maximal Lyapunov exponent and that of thermodynamical fluctuations, expressed by kinetic energy fluctuations or specific heat. The extensivity of chaos in the N-->infinity limit is tested through the scaling properties of Lyapunov spectra and of the Kolmogorov-Sinai entropy, Chaotic dynamics provides the mixing property in phase space necessary for obtaining equilibration; however, the relaxation time to equilibrium grows with N, at least near the critical point. Our results constitute an interesting bridge between Hamiltonian chaos in many degrees of freedom systems and equilibrium thermodynamics. (C) 1999 Elsevier Science B.V All rights reserved.
引用
收藏
页码:38 / 54
页数:17
相关论文
共 50 条
  • [41] Geometry and molecular dynamics of the Hamiltonian mean-field model in a magnetic field
    Araujo, Rubia
    Miranda Filho, L. H.
    Santos, Fernando A. N.
    Coutinho-Filho, M. D.
    PHYSICAL REVIEW E, 2021, 103 (01)
  • [42] Mean Field Limit and Propagation of Chaos for a Pedestrian Flow Model
    Li Chen
    Simone Göttlich
    Qitao Yin
    Journal of Statistical Physics, 2017, 166 : 211 - 229
  • [43] Mean Field Limit and Propagation of Chaos for a Pedestrian Flow Model
    Chen, Li
    Goettlich, Simone
    Yin, Qitao
    JOURNAL OF STATISTICAL PHYSICS, 2017, 166 (02) : 211 - 229
  • [44] Hamiltonian dynamics, nanosystems, and nonequilibrium statistical mechanics
    Gaspard, Pierre
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2006, 369 (01) : 201 - 246
  • [45] Statistical mechanics of Hamiltonian adaptive resolution simulations
    Espanol, P.
    Delgado-Buscalioni, R.
    Everaers, R.
    Potestio, R.
    Donadio, D.
    Kremer, K.
    JOURNAL OF CHEMICAL PHYSICS, 2015, 142 (06):
  • [46] Remarks on non-Hamiltonian statistical mechanics
    Ramshaw, JD
    EUROPHYSICS LETTERS, 2002, 59 (03): : 319 - 323
  • [47] Geometric approach to Hamiltonian dynamics and statistical mechanics
    Casetti, L
    Pettini, M
    Cohen, EGD
    PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2000, 337 (03): : 237 - 341
  • [48] Non-Hamiltonian equilibrium statistical mechanics
    Sergi, A
    PHYSICAL REVIEW E, 2003, 67 (02):
  • [49] Statistical mechanics of continual learning: Variational principle and mean-field potential
    Li, Chan
    Huang, Zhenye
    Zou, Wenxuan
    Huang, Haiping
    PHYSICAL REVIEW E, 2023, 108 (01)
  • [50] Hierarchical mean-field theory in quantum statistical mechanics: A bosonic example
    Ortiz, G
    Batista, CD
    PHYSICAL REVIEW B, 2003, 67 (13):