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Rate of relaxation for a mean-field zero-range process
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Graham, Benjamin T.. (2009) Rate of relaxation for a mean-field zero-range process. The Annals of Applied Probability, Vol.19 (No.2). pp. 497-520. ISSN 1050-5164
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Official URL: http://dx.doi.org/10.1214/08-AAP549
Abstract
We study the zero-range process on the complete graph. It is a Markov chain model for a microcanonical ensemble. We prove that the process converges to a fluid limit. The fluid limit rapidly relaxes to the appropriate Gibbs distribution.
| Item Type: | Journal Article |
|---|---|
| Subjects: | Q Science > QA Mathematics Q Science > QC Physics |
| Divisions: | Faculty of Science > Statistics |
| Library of Congress Subject Headings (LCSH): | Mean field theory, Markov processes, Relaxation methods (Mathematics), Logarithmic functions |
| Journal or Publication Title: | The Annals of Applied Probability |
| Publisher: | Institute of Mathematical Statistics |
| ISSN: | 1050-5164 |
| Date: | 2009 |
| Volume: | Vol.19 |
| Number: | No.2 |
| Page Range: | pp. 497-520 |
| Identification Number: | 10.1214/08-AAP549 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| References: | [1] CSISZÁR, I. (1967). Information-type measures of difference of probability distributions and indirect observations. Studia Sci. Math. Hungar. 2 299–318. MR0219345 [2] DARLING, R. W. R. and NORRIS, J. R. (2005). Structure of large random hypergraphs. Ann. Appl. Probab. 15 125–152. MR2115039 [3] DIACONIS, P. and SALOFF-COSTE, L. (1996). Logarithmic Sobolev inequalities for finite Markov chains. Ann. Appl. Probab. 6 695–750. MR1410112 [4] EHRENFEST, P. and EHRENFEST, T. (1907). Über zwei bekannte Einwände gegen das Boltzmannsche H-theorem. Phys. Zeit. 8 311–314. [5] EHRENFEST, P. and EHRENFEST, T. (1959). The Conceptual Foundations of the Statistical Approach in Mechanics. Cornell Univ. Press, Ithaca, NY. Translated by M. J. Moravcsik. MR0106571 [6] FELLER, W. (1968). An Introduction to Probability Theory and Its Applications. Vol. I. 3rd ed. Wiley, New York. MR0228020 [7] GOLDSCHMIDT, C. A. (2003). Large random hypergraphs. Ph.D. thesis, Univ. Cambridge. Available at http://www.stats.ox.ac.uk/~goldschm/. [8] GRAHAM, B. T. (2007). Interacting stochastic systems. Ph.D. thesis, Univ. Cambridge. Available at http://www.math.ubc.ca/~ben/. [9] JOHNSON, N. L. and KOTZ, S. (1977). Urn Models and Their Application. Wiley, New York. MR0488211 [10] KAHN, J., KALAI, G. and LINIAL, N. (1988). The influence of variables on Boolean functions. In Proceedings of 29th Symposium on the Foundations of Computer Science 68–80. Computer Science Press. [11] LINDVALL, T. (2002). Lectures on the Coupling Method. Dover, Mineola, NY. Corrected reprint of the 1992 original. MR1924231 [12] MCCOY, B. M. and WU, T. T. (1973). The Two-Dimensional Ising Model. Harvard Univ. Press, Cambridge. [13] MCDIARMID, C. (1998). Concentration. In Probabilistic Methods for Algorithmic Discrete Mathematics. Algorithms Combin. 16 195–248. Springer, Berlin. MR1678578 [14] MICLO, L. (1999). An example of application of discrete Hardy’s inequalities. Markov Process. Related Fields 5 319–330. MR1710983 [15] MITZENMACHER, M. (1999). On the analysis of randomized load balancing schemes. Theory Comput. Syst. 32 361–386. ACM Symposium on Parallel Algorithms and Architectures (Padua, 1996). MR1678304 |
| URI: | http://wrap.warwick.ac.uk/id/eprint/41071 |
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