When things grow many: complexity, universality and emergence in nature
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Oxford
Oxford University Press
[2022]
|
| Schriftenreihe: | Oxford graduate texts
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | xi, 286 Seiten Illustrationen, Diagramme 246 mm |
| ISBN: | 9780198861881 |
Internformat
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Datensatz im Suchindex
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| adam_text |
Contents 1 Introduction 1.1 2 Ideal gas 2.1 3 Fluctuations of the İdeal gas Rubber bands 3.1 3.2 3.3 3.4 3.5 4 Building The game Analysis Simulation Independent folk How often does the prediction go wrong? Percolitis An epidemic model Discussion Behavior of the order parameternear the critical point Approach to equilibrium Discreteness and fluctuations* Self-organized criticality (SOC):Applications to galaxies and mean field theory 4.7 The truth about percolitis 4.8 Abstract percolation 4.9 Percolation applications 4.10 True epidemiology 4.1 4.2 4.3 4.4 4.5 4.6 5 Ferromagnetism 5.1 5.2 5.3 6 Curie-Weiss ferromagnets Magnetization Fluctuations greater than \/Ñ Maximum entropy methods 6.1 6.2 6.3 Information Maximum entropy Using maximum entropy to study Supreme Court voting 1 2 6 8 11 11 11 13 15 17 19 19 22 24 25 30 34 38 42 44 45 50 55 57 60 63 63 66 71
x Contents 7 Power laws 7.1 Power laws are scale free 7.2 Diffusion 7.3 Preferential attachment (the rich get richer) 7.4 Exponential functions of exponential distributions 7.5 Superposition of exponentials 7.6 Critical phenomena and self-organized criticality(SOC) 76 78 79 81 84 85 85 8 Universality, renormalization and critical phenomena 8.1 The nearest neighbor one-dimensional Ising model 89 90 9 Social sciences 9.1 Econophysics 9.2 Stock market bubbles andcrashes 9.3 Linguistics 9.4 Power laws for cities 9.5 Urban discrimination 9.6 Voter models and elections 9.7 Crowd control 9.8 Traffic 104 105 110 115 119 121 128 131 133 10 Biological sciences 10.1 Firefly synchronization 10.2 Biorobotics and glass 10.3 Gene distributions 10.4 Flocking 10.5 Kuramoto model 10.6 Ecology 10.7 Neurology 140 140 147 151 156 162 171 176 11 Physical sciences 11.1 Power laws for luminescence 11.2 Large scale structure 11.3 Galactic morphology 180 180 184 187 12 Putting it all together 191 Appendix A Notation 196 Appendix В Background instatistical physics 198 Appendix C Fractals 204 Appendix D Review of probability D.l Basics D.2 Counting D.3 The central limit theorem D.4 Markov processes D.5 Stochastic dynamics 206 206 210 211 213 214
Contents D.6 The notion, of probability D.7 Stirling’s approximation D.8 Exercises in probability xi 216 216 218 Appendix E The van der Waals gas 221 Appendix F The logistic map 223 Appendix G Lagrange multipliers 226 G.l Two variables, one constraint G.2 Generalization, more than one constraint G.3 Example Appendix H Complexity in the observable representation H.l The observable representation 226 227 228 229 229 Appendix I A Quotation 239 Appendix J Solutions to exercises 240 References 261 Index 278 |
| adam_txt |
Contents 1 Introduction 1.1 2 Ideal gas 2.1 3 Fluctuations of the İdeal gas Rubber bands 3.1 3.2 3.3 3.4 3.5 4 Building The game Analysis Simulation Independent folk How often does the prediction go wrong? Percolitis An epidemic model Discussion Behavior of the order parameternear the critical point Approach to equilibrium Discreteness and fluctuations* Self-organized criticality (SOC):Applications to galaxies and mean field theory 4.7 The truth about percolitis 4.8 Abstract percolation 4.9 Percolation applications 4.10 True epidemiology 4.1 4.2 4.3 4.4 4.5 4.6 5 Ferromagnetism 5.1 5.2 5.3 6 Curie-Weiss ferromagnets Magnetization Fluctuations greater than \/Ñ Maximum entropy methods 6.1 6.2 6.3 Information Maximum entropy Using maximum entropy to study Supreme Court voting 1 2 6 8 11 11 11 13 15 17 19 19 22 24 25 30 34 38 42 44 45 50 55 57 60 63 63 66 71
x Contents 7 Power laws 7.1 Power laws are scale free 7.2 Diffusion 7.3 Preferential attachment (the rich get richer) 7.4 Exponential functions of exponential distributions 7.5 Superposition of exponentials 7.6 Critical phenomena and self-organized criticality(SOC) 76 78 79 81 84 85 85 8 Universality, renormalization and critical phenomena 8.1 The nearest neighbor one-dimensional Ising model 89 90 9 Social sciences 9.1 Econophysics 9.2 Stock market bubbles andcrashes 9.3 Linguistics 9.4 Power laws for cities 9.5 Urban discrimination 9.6 Voter models and elections 9.7 Crowd control 9.8 Traffic 104 105 110 115 119 121 128 131 133 10 Biological sciences 10.1 Firefly synchronization 10.2 Biorobotics and glass 10.3 Gene distributions 10.4 Flocking 10.5 Kuramoto model 10.6 Ecology 10.7 Neurology 140 140 147 151 156 162 171 176 11 Physical sciences 11.1 Power laws for luminescence 11.2 Large scale structure 11.3 Galactic morphology 180 180 184 187 12 Putting it all together 191 Appendix A Notation 196 Appendix В Background instatistical physics 198 Appendix C Fractals 204 Appendix D Review of probability D.l Basics D.2 Counting D.3 The central limit theorem D.4 Markov processes D.5 Stochastic dynamics 206 206 210 211 213 214
Contents D.6 The notion, of probability D.7 Stirling’s approximation D.8 Exercises in probability xi 216 216 218 Appendix E The van der Waals gas 221 Appendix F The logistic map 223 Appendix G Lagrange multipliers 226 G.l Two variables, one constraint G.2 Generalization, more than one constraint G.3 Example Appendix H Complexity in the observable representation H.l The observable representation 226 227 228 229 229 Appendix I A Quotation 239 Appendix J Solutions to exercises 240 References 261 Index 278 |
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| spelling | Schulman, Lawrence S. 1941- Verfasser (DE-588)1145528600 aut When things grow many complexity, universality and emergence in nature L. S. Schulman Oxford Oxford University Press [2022] xi, 286 Seiten Illustrationen, Diagramme 246 mm txt rdacontent n rdamedia nc rdacarrier Oxford graduate texts Hier auch später erschienene, unveränderte Nachdrucke bicssc / Mathematical modelling bicssc / Thermodynamics & heat Statistische Mechanik (DE-588)4056999-8 gnd rswk-swf Angewandte Physik (DE-588)4193885-9 gnd rswk-swf Statistische Mechanik (DE-588)4056999-8 s DE-604 Angewandte Physik (DE-588)4193885-9 s Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032963412&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schulman, Lawrence S. 1941- When things grow many complexity, universality and emergence in nature bicssc / Mathematical modelling bicssc / Thermodynamics & heat Statistische Mechanik (DE-588)4056999-8 gnd Angewandte Physik (DE-588)4193885-9 gnd |
| subject_GND | (DE-588)4056999-8 (DE-588)4193885-9 |
| title | When things grow many complexity, universality and emergence in nature |
| title_auth | When things grow many complexity, universality and emergence in nature |
| title_exact_search | When things grow many complexity, universality and emergence in nature |
| title_exact_search_txtP | When things grow many complexity, universality and emergence in nature |
| title_full | When things grow many complexity, universality and emergence in nature L. S. Schulman |
| title_fullStr | When things grow many complexity, universality and emergence in nature L. S. Schulman |
| title_full_unstemmed | When things grow many complexity, universality and emergence in nature L. S. Schulman |
| title_short | When things grow many |
| title_sort | when things grow many complexity universality and emergence in nature |
| title_sub | complexity, universality and emergence in nature |
| topic | bicssc / Mathematical modelling bicssc / Thermodynamics & heat Statistische Mechanik (DE-588)4056999-8 gnd Angewandte Physik (DE-588)4193885-9 gnd |
| topic_facet | bicssc / Mathematical modelling bicssc / Thermodynamics & heat Statistische Mechanik Angewandte Physik |
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