Nonextensive Statistical Mechanics

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7.1 Physics 249Fig. 7.36 Data collapse of the same numerical data of Fig. 7.35 in log vs. log representation (from[543]).Fig. 7.37 Data collapse of the same numerical data of Fig. 7.35 in q-log vs. linear representation.The straight line implies that the scaling function is a q-exponential with q ≃ 2.98 (from [543]).
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Introduction to Nonextensive Statis
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Constantino TsallisCentro Brasileir
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PrefaceIn 1902, after three decades
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Prefaceixequation inspired by the p
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Prefacexinearby. 4 Nonextensive sta
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Prefacexiiicircular epicycles. So w
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ContentsPart IBasics or How the The
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Contentsxvii5.2 Low-Dimensional Con
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Part IBasics or How the Theory Work
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4 1 Historical Background and Physi
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10 1 Historical Background and Phys
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Chapter 2Learning with Boltzmann-Gi
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2.1 Boltzmann-Gibbs Entropy 212.1.2
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2.1 Boltzmann-Gibbs Entropy 232.1.2
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2.1 Boltzmann-Gibbs Entropy 25where
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2.1 Boltzmann-Gibbs Entropy 27the s
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2.2 Kullback-Leibler Relative Entro
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2.3 Constraints and Entropy Optimiz
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2.4 Boltzmann-Gibbs Statistical Mec
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2.4 Boltzmann-Gibbs Statistical Mec
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Chapter 3Generalizing What We Learn
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3.1 Playing with Differential Equat
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3.2 Nonadditive Entropy S q 41We sh
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3.2 Nonadditive Entropy S q 43This
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3.2 Nonadditive Entropy S q 453.2.2
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3.2 Nonadditive Entropy S q 47we ca
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3.2 Nonadditive Entropy S q 49S BG
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3.2 Nonadditive Entropy S q 51with
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3.2 Nonadditive Entropy S q 53whose
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3.3 Correlations, Occupancy of Phas
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3.4 q-Generalization of the Kullbac
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3.4 q-Generalization of the Kullbac
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3.5 Constraints and Entropy Optimiz
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3.6 Nonextensive Statistical Mechan
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3.7 About the Escort Distribution a
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3.7 About the Escort Distribution a
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3.8 About Universal Constants in Ph
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3.9 Various Other Entropic Forms 10
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Part IIFoundations or Why the Theor
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110 4 Stochastic Dynamical Foundati
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152 5 Deterministic Dynamical Found
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10 -5 1 10 100 100010 -5 1 10 100 1
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Chapter 6Generalizing Nonextensive
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6.2 Further Generalizing 211dydx =
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6.2 Further Generalizing 213∫ W{
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6.2 Further Generalizing 215Then, f
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6.2 Further Generalizing 217If f (
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Part IIIApplications or What for th
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222 7 Thermodynamical and Nonthermo
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Page 524: 7.1 Physics 251Fig. 7.39 Cumulative
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Page 532: 7.1 Physics 2551.25fit in Fig.2Eq.(
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Page 540: 7.2 Chemistry 259Fig. 7.49 (a) Dime
Page 544: 7.2 Chemistry 261Fig. 7.52 d = 2(a)
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Page 552: 7.2 Chemistry 265Fig. 7.58 Log-log
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7.4 Computer Sciences 275Fig. 7.74
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7.5 Biosciences 281Fig. 7.82 Image
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7.8 Scale-Free Networks 283Fig. 7.8
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7.8 Scale-Free Networks 285a1b1cumu
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7.10 Other Sciences 295Fig. 7.102 S
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7.10 Other Sciences 297Fig. 7.105 F
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7.10 Other Sciences 299Fig. 7.109 Z
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7.10 Other Sciences 301Fig. 7.112 C
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Chapter 8Final Comments and Perspec
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8.1 Falsifiable Predictions and Con
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8.2 Frequently Asked Questions 309i
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8.2 Frequently Asked Questions 311B
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8.2 Frequently Asked Questions 313(
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8.2 Frequently Asked Questions 315o
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8.2 Frequently Asked Questions 317p
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8.2 Frequently Asked Questions 319n
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8.2 Frequently Asked Questions 321L
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8.2 Frequently Asked Questions 323(
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8.2 Frequently Asked Questions 3254
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8.3 Open Questions 327This is a fre
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330 Appendix A Useful Mathematical
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336 Appendix B Escort Distributions
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Bibliography1. J.W. Gibbs, Elementa
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Bibliography 34541. A. Rapisarda an
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Bibliography 34784. A.N. Kolmogorov
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Bibliography 349123. T. Schneider,
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Bibliography 351178. A. Campa, A. G
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Bibliography 353230. S. Abe and A.K
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Bibliography 355279. K. Briggs and
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Bibliography 357329. T. Kodama, H.-
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Bibliography 359Italy), eds. C. Bec
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Bibliography 361431. M.J.A. Bolzan,
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Bibliography 363479. T. Cattaert, M
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Bibliography 365528. P.H. Chavanis,
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Bibliography 367579. G.A. Tsekouras
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Bibliography 369631. J. Schulte, No
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Bibliography 371678. D. Fuks, S. Do
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Bibliography 373723. L.J. Yang, M.P
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Bibliography 375767. S. Sun, L. Zha
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Bibliography 377813. S. Abe, Tsalli
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Bibliography 379862. S. Boccaletti,
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382 IndexKekule, ixKepler, xiiKrylo
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