Monte Carlo simulations of disordered systems:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore ; River Edge, N.J.
World Scientific
1992
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| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 |
| Beschreibung: | Print version record |
| Beschreibung: | 1 online resource (xii, 179 pages) illustrations |
| ISBN: | 9789814503310 9814503312 9971506602 9789971506605 |
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| 505 | 8 | |a PREFACE; CONTENTS; Chapter 1 INTRODUCTION; Chapter 2 ELEMENTARY PROBABILITY AND STATISTICS; 2.1 Introduction; 2.2 Probability; 2.3 Random Variable; 2.3.1 Expectation value; 2.3.2 Variance; 2.3.3 Covariance; 2.3.4 Function of a random variable; 2.3.5 Conditional expectation; 2.4 Statistics; 2.4.1 Sample mean; 2.4.2 Sample variance; 2.5 Distribution Functions; 2.5.1 The binomial distribution; 2.5.2 The Gaussian distribution; 2.6 Central Limit Theorem; 2.7 Markov Processes; 2.8 Random Numbers; Chapter 3 NUMERICAL INTEGRATION; 3.1 Introduction; 3.2 The Rectangular Rule | |
| 505 | 8 | |a 3.3 The Trapezoidal Rule3.4 Simpson's Rule; 3.5 Quadrature Rules; 3.6 The Simple Monte Carlo Technique; 3.7 Hit or Miss Monte Carlo Method; 3.8 The Mixed Method; 3.9 Selective Sampling By Monte Carlo; 3.10 Buffon's Needle; Chapter 4 THERMODYNAMICS; 4.1 Introduction; 4.2 The Laws of Thermodynamics; 4.2.1 The zeroth law of thermodynamics; 4.2.2 The first law of thermodynamics; 4.2.3 The second law of thermodynamics; 4.2.4 The third law of thermodynamics; 4.3 Thermodynamic Relations; 4.4 Response and Correlation Functions; 4.5 Phase Transitions; 4.6 Order Parameters | |
| 505 | 8 | |a 4.7 Critical Point Exponents4.8 Ginzburg-Landau Phenomenological Theory of Ferromagnetism; Chapter 5 STATISTICAL MECHANICS; 5.1 Introduction; 5.2 The Microscopic Model; 5.2.1 The classical microscopic model; 5.2.2 The quantum mechanical model; 5.3 Ensembles in Statistical Mechanics; 5.3.1 The Gibbs microcanonical ensemble; 5.3.2 The canonical ensemble; 5.3.3 The grand canonical ensemble; 5.4 Statistical Thermodynamics; 5.5 The Classical Canonical Partition Function; 5.6 Phase Transitions and Critical Exponents; Chapter 6 MODEL SYSTEMS; 6.1 Introduction; 6.2 Basic Model Systems | |
| 505 | 8 | |a 6.2.1 Spatial dimensionality6.2.2 Spin dimensionality; 6.2.3 Interactions; 6.2.4 A typical model system; 6.3 An Exactly Solved Model; 6.4 Mean Field Theory; 6.5 Fluctuations; 6.6 Scaling and Scaling Laws; 6.7 Approximate Techniques; Chapter 7 DISORDERED MODEL SYSTEMS; 7.1 Introduction; 7.2 Disorder; 7.2.1 Annealed disorder; 7.2.2 Quenched disorder; 7.3 Disordered Lattices; 7.3.1 Site percolation; 7.3.2 Bond percolation; 7.4 Diluted Spin Systems; 7.4.1 Site-diluted; 7.4.2 Bond-diluted; 7.5 Disordered Interactions; 7.6 Mixed Systems; 7.7 Fractals | |
| 505 | 8 | |a 7.7.1 Non-random fractals7.7.2 Random fractals; Chapter 8 MONTE CARLO SIMULATIONS; 8.1 Introduction; 8.2 The Monte Carlo Technique; 8.2.1 Importance sampling; 8.2.2 The transition probability; 8.2.3 The master equation; 8.3 The Two-Dimensional Ising Model; 8.3.1 The algorithm; 8.4 Errors; 8.4.1 Statistical errors; 8.4.2 Systematic errors; 8.5 Further Checks on the Simulations; 8.6 Statistical Analysis; 8.6.1 The chi-squared test; 8.7 Final Note; BIBLIOGRAPHY; INDEX. | |
| 505 | 8 | |a This book covers the techniques of computer simulations of disordered systems. It describes how one performs Monte Carlo simulations in condensed matter physics and deals with spin-glasses, percolating networks and the random field Ising model. Other methods mentioned are molecular dynamics and Brownian dynamics. Use of flow-diagrams enables the reader to grasp both the problem and its solution more readily. The book deals with highly complicated problems at a relatively simple level and will be most useful for advanced undergraduate and other courses in computational modelling. Contents: Intr | |
| 650 | 7 | |a SCIENCE / System Theory |2 bisacsh | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING / Operations Research |2 bisacsh | |
| 650 | 7 | |a Monte-Carlo, Méthode de |2 ram | |
| 650 | 7 | |a Ordre et désordre (physique) |2 ram | |
| 650 | 7 | |a Monte-Carlo-Simulation |2 swd | |
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Datensatz im Suchindex
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| author | Jain, S. |
| author_facet | Jain, S. |
| author_role | aut |
| author_sort | Jain, S. |
| author_variant | s j sj |
| building | Verbundindex |
| bvnumber | BV043781064 |
| collection | ZDB-4-EBA |
| contents | PREFACE; CONTENTS; Chapter 1 INTRODUCTION; Chapter 2 ELEMENTARY PROBABILITY AND STATISTICS; 2.1 Introduction; 2.2 Probability; 2.3 Random Variable; 2.3.1 Expectation value; 2.3.2 Variance; 2.3.3 Covariance; 2.3.4 Function of a random variable; 2.3.5 Conditional expectation; 2.4 Statistics; 2.4.1 Sample mean; 2.4.2 Sample variance; 2.5 Distribution Functions; 2.5.1 The binomial distribution; 2.5.2 The Gaussian distribution; 2.6 Central Limit Theorem; 2.7 Markov Processes; 2.8 Random Numbers; Chapter 3 NUMERICAL INTEGRATION; 3.1 Introduction; 3.2 The Rectangular Rule 3.3 The Trapezoidal Rule3.4 Simpson's Rule; 3.5 Quadrature Rules; 3.6 The Simple Monte Carlo Technique; 3.7 Hit or Miss Monte Carlo Method; 3.8 The Mixed Method; 3.9 Selective Sampling By Monte Carlo; 3.10 Buffon's Needle; Chapter 4 THERMODYNAMICS; 4.1 Introduction; 4.2 The Laws of Thermodynamics; 4.2.1 The zeroth law of thermodynamics; 4.2.2 The first law of thermodynamics; 4.2.3 The second law of thermodynamics; 4.2.4 The third law of thermodynamics; 4.3 Thermodynamic Relations; 4.4 Response and Correlation Functions; 4.5 Phase Transitions; 4.6 Order Parameters 4.7 Critical Point Exponents4.8 Ginzburg-Landau Phenomenological Theory of Ferromagnetism; Chapter 5 STATISTICAL MECHANICS; 5.1 Introduction; 5.2 The Microscopic Model; 5.2.1 The classical microscopic model; 5.2.2 The quantum mechanical model; 5.3 Ensembles in Statistical Mechanics; 5.3.1 The Gibbs microcanonical ensemble; 5.3.2 The canonical ensemble; 5.3.3 The grand canonical ensemble; 5.4 Statistical Thermodynamics; 5.5 The Classical Canonical Partition Function; 5.6 Phase Transitions and Critical Exponents; Chapter 6 MODEL SYSTEMS; 6.1 Introduction; 6.2 Basic Model Systems 6.2.1 Spatial dimensionality6.2.2 Spin dimensionality; 6.2.3 Interactions; 6.2.4 A typical model system; 6.3 An Exactly Solved Model; 6.4 Mean Field Theory; 6.5 Fluctuations; 6.6 Scaling and Scaling Laws; 6.7 Approximate Techniques; Chapter 7 DISORDERED MODEL SYSTEMS; 7.1 Introduction; 7.2 Disorder; 7.2.1 Annealed disorder; 7.2.2 Quenched disorder; 7.3 Disordered Lattices; 7.3.1 Site percolation; 7.3.2 Bond percolation; 7.4 Diluted Spin Systems; 7.4.1 Site-diluted; 7.4.2 Bond-diluted; 7.5 Disordered Interactions; 7.6 Mixed Systems; 7.7 Fractals 7.7.1 Non-random fractals7.7.2 Random fractals; Chapter 8 MONTE CARLO SIMULATIONS; 8.1 Introduction; 8.2 The Monte Carlo Technique; 8.2.1 Importance sampling; 8.2.2 The transition probability; 8.2.3 The master equation; 8.3 The Two-Dimensional Ising Model; 8.3.1 The algorithm; 8.4 Errors; 8.4.1 Statistical errors; 8.4.2 Systematic errors; 8.5 Further Checks on the Simulations; 8.6 Statistical Analysis; 8.6.1 The chi-squared test; 8.7 Final Note; BIBLIOGRAPHY; INDEX. This book covers the techniques of computer simulations of disordered systems. It describes how one performs Monte Carlo simulations in condensed matter physics and deals with spin-glasses, percolating networks and the random field Ising model. Other methods mentioned are molecular dynamics and Brownian dynamics. Use of flow-diagrams enables the reader to grasp both the problem and its solution more readily. The book deals with highly complicated problems at a relatively simple level and will be most useful for advanced undergraduate and other courses in computational modelling. Contents: Intr |
| ctrlnum | (ZDB-4-EBA)ocn880147944 (OCoLC)880147944 (DE-599)BVBBV043781064 |
| dewey-full | 003/.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 003 - Systems |
| dewey-raw | 003/.7 |
| dewey-search | 003/.7 |
| dewey-sort | 13 17 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| id | DE-604.BV043781064 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:34:56Z |
| institution | BVB |
| isbn | 9789814503310 9814503312 9971506602 9789971506605 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029192124 |
| oclc_num | 880147944 |
| open_access_boolean | |
| owner | DE-1046 DE-1047 |
| owner_facet | DE-1046 DE-1047 |
| physical | 1 online resource (xii, 179 pages) illustrations |
| psigel | ZDB-4-EBA ZDB-4-EBA FAW_PDA_EBA |
| publishDate | 1992 |
| publishDateSearch | 1992 |
| publishDateSort | 1992 |
| publisher | World Scientific |
| record_format | marc |
| spelling | Jain, S. Verfasser aut Monte Carlo simulations of disordered systems S. Jain Singapore ; River Edge, N.J. World Scientific 1992 1 online resource (xii, 179 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Print version record PREFACE; CONTENTS; Chapter 1 INTRODUCTION; Chapter 2 ELEMENTARY PROBABILITY AND STATISTICS; 2.1 Introduction; 2.2 Probability; 2.3 Random Variable; 2.3.1 Expectation value; 2.3.2 Variance; 2.3.3 Covariance; 2.3.4 Function of a random variable; 2.3.5 Conditional expectation; 2.4 Statistics; 2.4.1 Sample mean; 2.4.2 Sample variance; 2.5 Distribution Functions; 2.5.1 The binomial distribution; 2.5.2 The Gaussian distribution; 2.6 Central Limit Theorem; 2.7 Markov Processes; 2.8 Random Numbers; Chapter 3 NUMERICAL INTEGRATION; 3.1 Introduction; 3.2 The Rectangular Rule 3.3 The Trapezoidal Rule3.4 Simpson's Rule; 3.5 Quadrature Rules; 3.6 The Simple Monte Carlo Technique; 3.7 Hit or Miss Monte Carlo Method; 3.8 The Mixed Method; 3.9 Selective Sampling By Monte Carlo; 3.10 Buffon's Needle; Chapter 4 THERMODYNAMICS; 4.1 Introduction; 4.2 The Laws of Thermodynamics; 4.2.1 The zeroth law of thermodynamics; 4.2.2 The first law of thermodynamics; 4.2.3 The second law of thermodynamics; 4.2.4 The third law of thermodynamics; 4.3 Thermodynamic Relations; 4.4 Response and Correlation Functions; 4.5 Phase Transitions; 4.6 Order Parameters 4.7 Critical Point Exponents4.8 Ginzburg-Landau Phenomenological Theory of Ferromagnetism; Chapter 5 STATISTICAL MECHANICS; 5.1 Introduction; 5.2 The Microscopic Model; 5.2.1 The classical microscopic model; 5.2.2 The quantum mechanical model; 5.3 Ensembles in Statistical Mechanics; 5.3.1 The Gibbs microcanonical ensemble; 5.3.2 The canonical ensemble; 5.3.3 The grand canonical ensemble; 5.4 Statistical Thermodynamics; 5.5 The Classical Canonical Partition Function; 5.6 Phase Transitions and Critical Exponents; Chapter 6 MODEL SYSTEMS; 6.1 Introduction; 6.2 Basic Model Systems 6.2.1 Spatial dimensionality6.2.2 Spin dimensionality; 6.2.3 Interactions; 6.2.4 A typical model system; 6.3 An Exactly Solved Model; 6.4 Mean Field Theory; 6.5 Fluctuations; 6.6 Scaling and Scaling Laws; 6.7 Approximate Techniques; Chapter 7 DISORDERED MODEL SYSTEMS; 7.1 Introduction; 7.2 Disorder; 7.2.1 Annealed disorder; 7.2.2 Quenched disorder; 7.3 Disordered Lattices; 7.3.1 Site percolation; 7.3.2 Bond percolation; 7.4 Diluted Spin Systems; 7.4.1 Site-diluted; 7.4.2 Bond-diluted; 7.5 Disordered Interactions; 7.6 Mixed Systems; 7.7 Fractals 7.7.1 Non-random fractals7.7.2 Random fractals; Chapter 8 MONTE CARLO SIMULATIONS; 8.1 Introduction; 8.2 The Monte Carlo Technique; 8.2.1 Importance sampling; 8.2.2 The transition probability; 8.2.3 The master equation; 8.3 The Two-Dimensional Ising Model; 8.3.1 The algorithm; 8.4 Errors; 8.4.1 Statistical errors; 8.4.2 Systematic errors; 8.5 Further Checks on the Simulations; 8.6 Statistical Analysis; 8.6.1 The chi-squared test; 8.7 Final Note; BIBLIOGRAPHY; INDEX. This book covers the techniques of computer simulations of disordered systems. It describes how one performs Monte Carlo simulations in condensed matter physics and deals with spin-glasses, percolating networks and the random field Ising model. Other methods mentioned are molecular dynamics and Brownian dynamics. Use of flow-diagrams enables the reader to grasp both the problem and its solution more readily. The book deals with highly complicated problems at a relatively simple level and will be most useful for advanced undergraduate and other courses in computational modelling. Contents: Intr SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Monte-Carlo, Méthode de ram Ordre et désordre (physique) ram Monte-Carlo-Simulation swd Stochastisches System swd Order-disorder models Monte Carlo method Digitial computer simulation Ungeordnetes System (DE-588)4124353-5 gnd rswk-swf Stochastisches System (DE-588)4057635-8 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 s Ungeordnetes System (DE-588)4124353-5 s 1\p DE-604 Stochastisches System (DE-588)4057635-8 s DE-604 Erscheint auch als Druck-Ausgabe Jain, S . Monte Carlo simulations of disordered systems 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Jain, S. Monte Carlo simulations of disordered systems PREFACE; CONTENTS; Chapter 1 INTRODUCTION; Chapter 2 ELEMENTARY PROBABILITY AND STATISTICS; 2.1 Introduction; 2.2 Probability; 2.3 Random Variable; 2.3.1 Expectation value; 2.3.2 Variance; 2.3.3 Covariance; 2.3.4 Function of a random variable; 2.3.5 Conditional expectation; 2.4 Statistics; 2.4.1 Sample mean; 2.4.2 Sample variance; 2.5 Distribution Functions; 2.5.1 The binomial distribution; 2.5.2 The Gaussian distribution; 2.6 Central Limit Theorem; 2.7 Markov Processes; 2.8 Random Numbers; Chapter 3 NUMERICAL INTEGRATION; 3.1 Introduction; 3.2 The Rectangular Rule 3.3 The Trapezoidal Rule3.4 Simpson's Rule; 3.5 Quadrature Rules; 3.6 The Simple Monte Carlo Technique; 3.7 Hit or Miss Monte Carlo Method; 3.8 The Mixed Method; 3.9 Selective Sampling By Monte Carlo; 3.10 Buffon's Needle; Chapter 4 THERMODYNAMICS; 4.1 Introduction; 4.2 The Laws of Thermodynamics; 4.2.1 The zeroth law of thermodynamics; 4.2.2 The first law of thermodynamics; 4.2.3 The second law of thermodynamics; 4.2.4 The third law of thermodynamics; 4.3 Thermodynamic Relations; 4.4 Response and Correlation Functions; 4.5 Phase Transitions; 4.6 Order Parameters 4.7 Critical Point Exponents4.8 Ginzburg-Landau Phenomenological Theory of Ferromagnetism; Chapter 5 STATISTICAL MECHANICS; 5.1 Introduction; 5.2 The Microscopic Model; 5.2.1 The classical microscopic model; 5.2.2 The quantum mechanical model; 5.3 Ensembles in Statistical Mechanics; 5.3.1 The Gibbs microcanonical ensemble; 5.3.2 The canonical ensemble; 5.3.3 The grand canonical ensemble; 5.4 Statistical Thermodynamics; 5.5 The Classical Canonical Partition Function; 5.6 Phase Transitions and Critical Exponents; Chapter 6 MODEL SYSTEMS; 6.1 Introduction; 6.2 Basic Model Systems 6.2.1 Spatial dimensionality6.2.2 Spin dimensionality; 6.2.3 Interactions; 6.2.4 A typical model system; 6.3 An Exactly Solved Model; 6.4 Mean Field Theory; 6.5 Fluctuations; 6.6 Scaling and Scaling Laws; 6.7 Approximate Techniques; Chapter 7 DISORDERED MODEL SYSTEMS; 7.1 Introduction; 7.2 Disorder; 7.2.1 Annealed disorder; 7.2.2 Quenched disorder; 7.3 Disordered Lattices; 7.3.1 Site percolation; 7.3.2 Bond percolation; 7.4 Diluted Spin Systems; 7.4.1 Site-diluted; 7.4.2 Bond-diluted; 7.5 Disordered Interactions; 7.6 Mixed Systems; 7.7 Fractals 7.7.1 Non-random fractals7.7.2 Random fractals; Chapter 8 MONTE CARLO SIMULATIONS; 8.1 Introduction; 8.2 The Monte Carlo Technique; 8.2.1 Importance sampling; 8.2.2 The transition probability; 8.2.3 The master equation; 8.3 The Two-Dimensional Ising Model; 8.3.1 The algorithm; 8.4 Errors; 8.4.1 Statistical errors; 8.4.2 Systematic errors; 8.5 Further Checks on the Simulations; 8.6 Statistical Analysis; 8.6.1 The chi-squared test; 8.7 Final Note; BIBLIOGRAPHY; INDEX. This book covers the techniques of computer simulations of disordered systems. It describes how one performs Monte Carlo simulations in condensed matter physics and deals with spin-glasses, percolating networks and the random field Ising model. Other methods mentioned are molecular dynamics and Brownian dynamics. Use of flow-diagrams enables the reader to grasp both the problem and its solution more readily. The book deals with highly complicated problems at a relatively simple level and will be most useful for advanced undergraduate and other courses in computational modelling. Contents: Intr SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Monte-Carlo, Méthode de ram Ordre et désordre (physique) ram Monte-Carlo-Simulation swd Stochastisches System swd Order-disorder models Monte Carlo method Digitial computer simulation Ungeordnetes System (DE-588)4124353-5 gnd Stochastisches System (DE-588)4057635-8 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| subject_GND | (DE-588)4124353-5 (DE-588)4057635-8 (DE-588)4240945-7 |
| title | Monte Carlo simulations of disordered systems |
| title_auth | Monte Carlo simulations of disordered systems |
| title_exact_search | Monte Carlo simulations of disordered systems |
| title_full | Monte Carlo simulations of disordered systems S. Jain |
| title_fullStr | Monte Carlo simulations of disordered systems S. Jain |
| title_full_unstemmed | Monte Carlo simulations of disordered systems S. Jain |
| title_short | Monte Carlo simulations of disordered systems |
| title_sort | monte carlo simulations of disordered systems |
| topic | SCIENCE / System Theory bisacsh TECHNOLOGY & ENGINEERING / Operations Research bisacsh Monte-Carlo, Méthode de ram Ordre et désordre (physique) ram Monte-Carlo-Simulation swd Stochastisches System swd Order-disorder models Monte Carlo method Digitial computer simulation Ungeordnetes System (DE-588)4124353-5 gnd Stochastisches System (DE-588)4057635-8 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd |
| topic_facet | SCIENCE / System Theory TECHNOLOGY & ENGINEERING / Operations Research Monte-Carlo, Méthode de Ordre et désordre (physique) Monte-Carlo-Simulation Stochastisches System Order-disorder models Monte Carlo method Digitial computer simulation Ungeordnetes System |
| work_keys_str_mv | AT jains montecarlosimulationsofdisorderedsystems |