Coarse-graining schemes and a posteriori error estimates for stochastic lattice systems
Markos A. Katsoulakis; Petr Plecháč; Luc Rey-Bellet; Dimitrios K. Tsagkarogiannis
ESAIM: Mathematical Modelling and Numerical Analysis (2007)
- Volume: 41, Issue: 3, page 627-660
- ISSN: 0764-583X
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topKatsoulakis, Markos A., et al. "Coarse-graining schemes and a posteriori error estimates for stochastic lattice systems." ESAIM: Mathematical Modelling and Numerical Analysis 41.3 (2007): 627-660. <http://eudml.org/doc/250071>.
@article{Katsoulakis2007,
abstract = {
The primary objective of this work is to develop coarse-graining
schemes for stochastic many-body microscopic models and quantify their
effectiveness in terms of a priori and a posteriori error analysis. In
this paper we focus on stochastic lattice systems of
interacting particles at equilibrium.
The proposed algorithms are derived from an initial coarse-grained
approximation that is directly computable by Monte Carlo simulations,
and the corresponding numerical error is calculated using the specific relative entropy between the exact and approximate coarse-grained equilibrium measures. Subsequently we carry out a cluster expansion around this first – and often inadequate – approximation and obtain more accurate coarse-graining schemes.
The cluster expansions yield also sharp a posteriori error estimates for
the coarse-grained approximations that can be used for the construction of
adaptive coarse-graining methods.
We present a number of numerical examples that demonstrate that the
coarse-graining schemes developed here allow for accurate predictions of critical behavior and hysteresis in systems with intermediate and long-range interactions. We also present examples where they substantially improve
predictions of earlier coarse-graining schemes for short-range interactions.
},
author = {Katsoulakis, Markos A., Plecháč, Petr, Rey-Bellet, Luc, Tsagkarogiannis, Dimitrios K.},
journal = {ESAIM: Mathematical Modelling and Numerical Analysis},
keywords = {Coarse-graining; a posteriori error estimate; relative entropy;
lattice spin systems; Monte Carlo method; Gibbs measure; cluster expansion;
renormalization group map.; coarse-graining; a posteriori error estimate; lattice spin systems; renormalization group map},
language = {eng},
month = {8},
number = {3},
pages = {627-660},
publisher = {EDP Sciences},
title = {Coarse-graining schemes and a posteriori error estimates for stochastic lattice systems},
url = {http://eudml.org/doc/250071},
volume = {41},
year = {2007},
}
TY - JOUR
AU - Katsoulakis, Markos A.
AU - Plecháč, Petr
AU - Rey-Bellet, Luc
AU - Tsagkarogiannis, Dimitrios K.
TI - Coarse-graining schemes and a posteriori error estimates for stochastic lattice systems
JO - ESAIM: Mathematical Modelling and Numerical Analysis
DA - 2007/8//
PB - EDP Sciences
VL - 41
IS - 3
SP - 627
EP - 660
AB -
The primary objective of this work is to develop coarse-graining
schemes for stochastic many-body microscopic models and quantify their
effectiveness in terms of a priori and a posteriori error analysis. In
this paper we focus on stochastic lattice systems of
interacting particles at equilibrium.
The proposed algorithms are derived from an initial coarse-grained
approximation that is directly computable by Monte Carlo simulations,
and the corresponding numerical error is calculated using the specific relative entropy between the exact and approximate coarse-grained equilibrium measures. Subsequently we carry out a cluster expansion around this first – and often inadequate – approximation and obtain more accurate coarse-graining schemes.
The cluster expansions yield also sharp a posteriori error estimates for
the coarse-grained approximations that can be used for the construction of
adaptive coarse-graining methods.
We present a number of numerical examples that demonstrate that the
coarse-graining schemes developed here allow for accurate predictions of critical behavior and hysteresis in systems with intermediate and long-range interactions. We also present examples where they substantially improve
predictions of earlier coarse-graining schemes for short-range interactions.
LA - eng
KW - Coarse-graining; a posteriori error estimate; relative entropy;
lattice spin systems; Monte Carlo method; Gibbs measure; cluster expansion;
renormalization group map.; coarse-graining; a posteriori error estimate; lattice spin systems; renormalization group map
UR - http://eudml.org/doc/250071
ER -
References
top- J. Bricmont, A. Kupiainen and R. Lefevere, Renormalization group pathologies and the definition of Gibbs states. Comm. Math. Phys.194 (1998) 359–388.
- C. Cammarota, Decay of correlations for infinite range interactions in unbounded spin systems. Comm. Math. Phys.85 (1982) 517–528.
- A. Chatterjee, M. Katsoulakis and D. Vlachos, Spatially adaptive lattice coarse-grained Monte Carlo simulations for diffusion of interacting molecules. J. Chem. Phys.121 (2004) 11420–11431.
- A. Chatterjee, M. Katsoulakis and D. Vlachos, Spatially adaptive grand canonical ensemble Monte Carlo simulations. Phys. Rev. E71 (2005) 026702.
- T.M. Cover and J.A. Thomas, Elements of Information Theory. John Wiley and Sons, Inc. (1991).
- G.A. Gallavotti and S. Miracle-Sole, Correlation functions of a lattice system. Comm. Math. Phys.7 (1968) 274–288.
- N. Goldenfeld, Lectures on Phase Transitions and the Renormalization Group, Volume 85. Addison-Wesley, New York (1992).
- C. Gruber and H. Kunz, General properties of polymer systems. Comm. Math. Phys.22 (1971) 133–161.
- M. Hildebrand and A.S. Mikhailov, Mesoscopic modeling in the kinetic theory of adsorbates. J. Chem. Phys.100 (1996) 19089.
- A.E. Ismail, G.C. Rutledge and G. Stephanopoulos, Multiresolution analysis in statistical mechanics. I. Using wavelets to calculate thermodynamics properties. J. Chem. Phys.118 (2003) 4414–4424.
- A.E. Ismail, G.C. Rutledge and G. Stephanopoulos, Multiresolution analysis in statistical mechanics. II. Wavelet transform as a basis for Monte Carlo simulations on lattices. J. Chem. Phys.118 (2003) 4424.
- L. Kadanoff, Scaling laws for Ising models near tc. Physics2 (1966) 263.
- M. Katsoulakis and J. Trashorras, Information loss in coarse-graining of stochastic particle dynamics. J. Statist. Phys.122 (2006) 115–135.
- M. Katsoulakis, A. Majda and D. Vlachos, Coarse-grained stochastic processes for microscopic lattice systems. Proc. Natl. Acad. Sci.100 (2003) 782–782.
- M.A. Katsoulakis, A.J. Majda and D.G. Vlachos, Coarse-grained stochastic processes and Monte Carlo simulations in lattice systems. J. Comp. Phys.186 (2003) 250–278.
- M.A. Katsoulakis, P. Plecháč, L. Rey-Bellet and D.K. Tsagkarogiannis, Coarse-graining schemes for lattice systems with short and long range interactions. (In preparation).
- M.A. Katsoulakis, P. Plecháč and A. Sopasakis, Error analysis of coarse-graining for stochastic lattice dynamics. SIAM J. Numer. Anal.44 (2006) 2270.
- D.A. Lavis and G.M. Bell, Statistical Mechanics of Lattice Systems, Volume I. Springer Verlag (1999).
- J.E. Mayer, Integral equations between distribution functions of molecules. J. Chem. Phys.15 (1947) 187–201.
- R. Peierls, On Ising's model of ferromagnetism. Proc. Camb. Philos. Soc.32 (1936) 477–481.
- I.V. Pivkin and G.E. Karniadakis, Coarse-graining limits in open and wall-bounded dissipative particle dynamics systems. J. Chem. Phys.124 (2006) 184101.
- A. Procacci, B.N.B. De Lima and B. Scoppola, A remark on high temperature polymer expansion for lattice systems with infinite range pair interactions. Lett. Math. Phys.45 (1998) 303–322.
- B. Simon, The Statistical Mechanics of Lattice Gases, Vol. I. Princeton series in Physics (1993).
- A. Szepessy, R. Tempone and G.E. Zouraris, Adaptive weak approximation of stochastic differential equations. Comm. Pure Appl. Math.54 (2001) 1169–1214.
- A.C.D. van Enter, R. Fernández and A.D. Sokal, Regularity properties and pathologies of position-space renormalization-group transformations: scope and limitations of Gibbsian theory. J. Statist. Phys.72 (1993) 879–1167.
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