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Books on the topic 'Statistical mechanics ; complex systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

1975-, Reguera D., Bonilla L. L. 1956-, and Rubí J. M, eds. Coherent structures in complex systems: Selected papers of the XVII Sitges Conference on Statistical Mechanics, held at Sitges, Barcelona, Spain, 5-9 June 2000 : preliminary version. Springer, 2001.

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2

Pastor-Satorras, Romualdo, Miguel Rubi, and Albert Diaz-Guilera, eds. Statistical Mechanics of Complex Networks. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b12331.

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3

Bertin, Eric. Statistical Physics of Complex Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42340-1.

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4

Bertin, Eric. Statistical Physics of Complex Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79949-6.

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5

Lavis, D. A. Statistical mechanics of lattice systems. Springer, 1999.

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6

1925-, Bell G. M., and Bell G. M. 1925-, eds. Statistical mechanics of lattice systems. 2nd ed. Springer, 1999.

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7

Lavis, D. A. Statistical mechanics of lattice systems. 2nd ed. Springer, 2010.

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8

Lavis, David A., and George M. Bell. Statistical Mechanics of Lattice Systems. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-10020-2.

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9

Lavis, David A., and George M. Bell. Statistical Mechanics of Lattice Systems. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03843-7.

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10

Sinaĭ, Ya, ed. Dynamical Systems and Statistical Mechanics. American Mathematical Society, 1991. http://dx.doi.org/10.1090/advsov/003.

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11

Introduction to nonextensive statistical mechanics: Approaching a complex world. Springer, 2009.

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12

N, Skri͡abin I͡U, ed. Statistical mechanics of magnetically ordered systems. Consultants Bureau, 1988.

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13

Izyumov, Yu A. Statistical mechanics of magnetically ordered systems. Consultants Bureau, 1988.

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14

Schmittmann, B. Statistical mechanics of driven diffusive systems. Academic Press, 1995.

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15

Nonequilibrium statistical mechanics of heterogeneous fluid systems. CRC Press, 1995.

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16

Zaman, Muhammad H. Statistical Mechanics of Cellular Systems and Processes. Cambridge University Press, 2009.

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17

Liebmann, R. Statistical mechanics of periodic frustrated Ising systems. Springer-Verlag, 1986.

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18

Gayrard, Véronique, Louis-Pierre Arguin, Nicola Kistler, and Irina Kourkova, eds. Statistical Mechanics of Classical and Disordered Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29077-1.

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19

Zaman, Muhammad H., ed. Statistical Mechanics of Cellular Systems and Processes. Cambridge University Press, 2009. http://dx.doi.org/10.1017/cbo9780511576768.

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20

Walschaers, Mattia. Statistical Benchmarks for Quantum Transport in Complex Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93151-7.

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21

Schmelzer, J. Aggregation phenomena in complex systems. Wiley-VCH, 1999.

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22

Ngai, K. L. Relaxation and diffusion in complex systems. Springer, 2011.

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23

Relaxation and diffusion in complex systems. Springer, 2011.

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24

Chaos, scattering, and statistical mechanics. Cambridge University Press, 1998.

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25

Petrina, D. I͡A. Mathematical foundations of classical statistical mechanics: Continuous systems. Gordon and Breach Science Publishers, 1989.

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26

Petrina, D. I͡A. Mathematical foundations of quantum statistical mechanics: Continous systems. Kluwer Academic Publishers, 1995.

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27

I, Gerasimenko V., and Malyshev P. V, eds. Mathematical foundations of classical statistical mechanics: Continuous systems. 2nd ed. Taylor & Francis, 2002.

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28

I, Sadovnikov B., and Shumovskiĭ A. S, eds. Mathematical methods of statistical mechanics of model systems. CRC Press, 1994.

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29

1939-, Beiglböck W., Eckmann Jean Pierre, Grosse Harald 1944-, et al., eds. Scaling Limits in Statistical Mechanics and Microstructures in Continuum Mechanics. Springer Berlin Heidelberg, 2009.

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30

Minai, Ali A. Unifying Themes in Complex Systems: Proceedings of the Fifth International Conference on Complex Systems. Springer Berlin Heidelberg, 2011.

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31

J, West Bruce, ed. The nonequilibrium statistical mechanics of open and closed systems. VCH Publishers, 1990.

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32

Baldovin, Marco. Statistical Mechanics of Hamiltonian Systems with Bounded Kinetic Terms. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51170-8.

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33

Bertin, Eric. A Concise Introduction to the Statistical Physics of Complex Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-23923-6.

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34

Minai, Ali A. Unifying Themes in Complex Systems VII: Proceedings of the Seventh International Conference on Complex Systems. Springer Berlin Heidelberg, 2012.

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35

Francesco, Fucito, Sbragaglia Mauro, and SpringerLink (Online service), eds. Solved Problems in Quantum and Statistical Mechanics. Springer Milan, 2012.

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36

An introduction to chaos in nonequilibrium statistical mechanics. Cambridge University Press, 1999.

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37

Viswanathan, Gandhimohan M., Ernesto P. Raposo, and Marcos Gomes Eleutério da Luz. Perspectives and challenges in statistical physics and complex systems for the next decade. World Scientific, 2014.

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38

Nicolis, G. Foundations of complex systems: Nonlinear dynamics, statistical physics, information and prediction. World Scientific, 2007.

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39

Doursat, René. Morphogenetic Engineering: Toward Programmable Complex Systems. Springer Berlin Heidelberg, 2012.

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40

Michel, Olivier, Hiroki Sayama, and René Doursat. Morphogenetic engineering: Toward programmable complex systems. Springer, 2013.

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41

Albeverio, Sergio. The statistical mechanics of quantum lattice systems: A path integral approach. European Mathematical Society, 2009.

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42

The statistical mechanics of quantum lattice systems: A path integral approach. European Mathematical Society, 2009.

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43

Structure in complex networks. Springer, 2009.

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44

Thurner, Stefan, Rudolf Hanel, and Peter Klimekl. Statistical Mechanics and Information Theory for Complex Systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821939.003.0006.

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Most complex systems are statistical systems. Statsitical mechanics and information theory usually do not apply to complex systems because the latter break the assumptions of ergodicity, independence, and multinomial statistics. We show that it is possible to generalize the frameworks of statistical mechanics and information theory in a meaningful way, such that they become useful for understanding the statistics of complex systems.We clarify that the notion of entropy for complex systems is strongly dependent on the context where it is used, and differs if it is used as an extensive quantity, a measure of information, or as a tool for statistical inference. We show this explicitly for simple path-dependent complex processes such as Polya urn processes, and sample space reducing processes.We also show it is possible to generalize the maximum entropy principle to path-dependent processes and how this can be used to compute timedependent distribution functions of history dependent processes.

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45

Allen, Michael P., and Dominic J. Tildesley. Statistical mechanics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0002.

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This chapter contains the essential statistical mechanics required to understand the inner workings of, and interpretation of results from, computer simulations. The microcanonical, canonical, isothermal–isobaric, semigrand and grand canonical ensembles are defined. Thermodynamic, structural, and dynamical properties of simple and complex liquids are related to appropriate functions of molecular positions and velocities. A number of important thermodynamic properties are defined in terms of fluctuations in these ensembles. The effect of the inclusion of hard constraints in the underlying potential model on the calculated properties is considered, and the addition of long-range and quantum corrections to classical simulations is presented. The extension of statistical mechanics to describe inhomogeneous systems such as the planar gas–liquid interface, fluid membranes, and liquid crystals, and its application in the simulation of these systems, are discussed.

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46

E, Cladis P., Palffy-Muhoray P, and NATO Advanced Research Workshop on Spatio-Temporal Patterns in Nonequilibrium Complex Systems (1993 : Santa Fe, N.M.), eds. Spatio-temporal patterns in nonequilibrium complex systems: NATO advanced research workshop. Addison-Wesley, 1995.

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47

Thurner, Stefan, Rudolf Hanel, and Peter Klimekl. The Future of the Science of Complex Systems? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821939.003.0007.

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The chapter is a mini outlook on the field. The classic achievenments in complexity science are mentioned, and we summarize how the new directions contained in this book might open new doors into a truly twenty-first-century science of complex systems.We do that by clarifying the origin of scaling laws, in particular for driven non-equilibrium systems, deriving the statistics of driven systems on the basis of driving and relaxing processes, categorizing probabilistic complex systems into universality classes, by developing ways for meaningful generalizations of statistical mechanics, and information theory so that they become useful for complex systems, and finally, by unifying the different approaches to evolution and co-evolution into a single mathematical framework that can serve as the basis for understanding co-evolutionary dynamics of states and interactions. We comment on our view of the role of artificial intelligence and our opinion on the future of science of complex systems.

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48

Thurner, Stefan, Peter Klimek, and Rudolf Hanel. Introduction to the Theory of Complex Systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198821939.001.0001.

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This book is a comprehensive introduction to quantitative approaches to complex adaptive systems. Practically all areas of life on this planet are constantly confronted with complex systems, be it ecosystems, societies, traffic, financial markets, opinion formation, epidemic spreading, or the internet and social media. Complex systems are systems composed of many elements that interact with each other, which makes them extremely rich dynamical systems showing a huge range of phenomena. Properties of complex systems that are of particular importance are their efficiency, robustness, resilience, and proneness to collapse. The quantitative tools and concepts needed to understand the co-evolutionary nature of networked systems and their properties are challenging. The intention of the book is to give a self-contained introduction to these concepts so that the reader will be equipped with a conceptual and mathematical toolset that allows her to engage in the science of complex systems. Topics covered include random processes of path-dependent processes, co-evolutionary dynamics, the statistics of driven nonequilibrium systems, dynamics of networks, the theory of scaling, and approaches from statistical mechanics and information theory. The book extends well beyond the early classical literature in the field of complex systems and summarizes the methodological progress over the past twenty years in a clear, structured, and comprehensive way. The book is intended for natural scientists and graduate students.

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49

Ross, John, Igor Schreiber, and Marcel O. Vlad. Determination of Complex Reaction Mechanisms. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195178685.001.0001.

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In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathway, and on the reaction mechanism. Basic pulse theory is demonstrated and tested in an experiment on glycolysis. In a second approach, measurements on time series of concentrations are used to construct correlation functions and a theory is developed which shows that from these functions information may be inferred on the reaction pathway, the reaction mechanism, and the centers of control in that mechanism. A third approach is based on application of genetic algorithm methods to the study of the evolutionary development of a reaction mechanism, to the attainment given goals in a mechanism, and to the determination of a reaction mechanism and rate coefficients by comparison with experiment. Responses of non-linear systems to pulses or other perturbations are analyzed, and mechanisms of oscillatory reactions are presented in detail. The concluding chapters give an introduction to bioinformatics and statistical methods for determining reaction mechanisms.

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50

Cladis, P. E., and P. Palffy-Muhoray. Spatio-Temporal Patterns in Nonequilibrium Complex Systems: NATO Advanced Research Workshop (Santa Fe Institute Studies in the Sciences of Complexity Proceedings). Addison Wesley Longman, 1994.

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