Computational Statistical Physics: From Billards to Monte-CarloSpringer Science & Business Media, 2002 - 300 sivua In recent years statistical physics has made significant progress as a result of advances in numerical techniques. While good textbooks exist on the general aspects of statistical physics, the numerical methods and the new developments based on large-scale computing are not usually adequately presented. In this book 16 experts describe the application of methods of statistical physics to various areas in physics such as disordered materials, quasicrystals, semiconductors, and also to other areas beyond physics, such as financial markets, game theory, evolution, and traffic planning, in which statistical physics has recently become significant. In this way the universality of the underlying concepts and methods such as fractals, random matrix theory, time series, neural networks, evolutionary algorithms, becomes clear. The topics are covered by introductory, tutorial presentations. |
Sisältö
I | 1 |
III | 2 |
IV | 7 |
V | 9 |
VI | 13 |
VII | 14 |
VIII | 15 |
X | 17 |
XCV | 139 |
XCVI | 141 |
XCVII | 142 |
XCVIII | 144 |
XCIX | 150 |
C | 151 |
CI | 153 |
CIII | 155 |
XI | 18 |
XIII | 20 |
XIV | 22 |
XV | 26 |
XVI | 28 |
XVII | 29 |
XVIII | 31 |
XIX | 32 |
XX | 33 |
XXI | 34 |
XXII | 35 |
XXIII | 37 |
XXV | 40 |
XXVI | 42 |
XXVII | 43 |
XXVIII | 45 |
XXXI | 46 |
XXXII | 47 |
XXXIII | 49 |
XXXIV | 51 |
XXXV | 53 |
XXXVI | 55 |
XXXVIII | 57 |
XL | 58 |
XLI | 60 |
XLII | 64 |
XLIII | 65 |
XLIV | 66 |
XLV | 68 |
XLVI | 69 |
XLVII | 70 |
XLVIII | 71 |
XLIX | 74 |
L | 75 |
LI | 77 |
LIII | 79 |
LIV | 80 |
LV | 83 |
LVI | 85 |
LVII | 86 |
LVIII | 87 |
LIX | 90 |
LX | 92 |
LXI | 93 |
LXII | 94 |
LXIII | 96 |
LXIV | 97 |
LXVI | 98 |
LXVII | 100 |
LXVIII | 103 |
LXIX | 105 |
LXX | 107 |
LXXI | 108 |
LXXII | 109 |
LXXIII | 110 |
LXXIV | 111 |
LXXV | 113 |
LXXVII | 114 |
LXXVIII | 115 |
LXXIX | 117 |
LXXX | 121 |
LXXXI | 123 |
LXXXII | 124 |
LXXXIII | 126 |
LXXXIV | 127 |
LXXXVI | 128 |
LXXXVIII | 131 |
XC | 132 |
XCII | 133 |
XCIII | 136 |
XCIV | 138 |
CIV | 156 |
CVII | 159 |
CVIII | 162 |
CIX | 164 |
CX | 166 |
CXI | 169 |
CXII | 170 |
CXIII | 173 |
CXIV | 176 |
CXV | 180 |
CXVI | 181 |
CXVII | 182 |
CXVIII | 183 |
CXX | 185 |
CXXI | 187 |
CXXII | 188 |
CXXIII | 189 |
CXXIV | 191 |
CXXVI | 193 |
CXXVIII | 194 |
CXXIX | 196 |
CXXX | 197 |
CXXXII | 198 |
CXXXIII | 200 |
CXXXIV | 201 |
CXXXVI | 204 |
CXXXVII | 207 |
CXXXVIII | 208 |
CXXXIX | 209 |
CXL | 211 |
CXLII | 214 |
CXLIII | 217 |
CXLIV | 220 |
CXLV | 221 |
CXLVI | 224 |
CXLVII | 226 |
CXLIX | 227 |
CL | 228 |
CLI | 230 |
CLII | 231 |
CLIII | 233 |
CLIV | 236 |
CLV | 238 |
CLVI | 239 |
CLVIII | 241 |
CLIX | 243 |
CLX | 247 |
CLXI | 248 |
CLXII | 250 |
CLXIII | 251 |
CLXIV | 252 |
CLXV | 255 |
CLXVI | 256 |
CLXVII | 259 |
CLXVIII | 262 |
CLXIX | 268 |
CLXX | 272 |
CLXXI | 277 |
CLXXII | 279 |
CLXXIV | 280 |
CLXXV | 282 |
CLXXVI | 283 |
CLXXVIII | 285 |
CLXXX | 286 |
CLXXXI | 287 |
CLXXXIII | 289 |
CLXXXIV | 291 |
CLXXXV | 293 |
295 | |
Muita painoksia - Näytä kaikki
Computational Statistical Physics: From Billiards to Monte Carlo K.-H. Hoffmann,Michael Schreiber Rajoitettu esikatselu - 2013 |
Computational Statistical Physics: From Billiards to Monte Carlo K.-H. Hoffmann,Michael Schreiber Esikatselu ei käytettävissä - 2010 |
Yleiset termit ja lausekkeet
algorithm aperiodic assembly line average billiard bond percolation boundary Brownian calculated chaotic classical cluster complex configuration constraints correlation length corresponding critical exponents critical point curve defined density described dimension discussed disorder distribution dynamics eigenvalues electrons energy landscape energy levels ensemble equation example exciton exponential finite fluctuations fractal given Hamiltonian interactions Ising model iteration K.H. Hoffmann lattice Lett level repulsion linear localized magnetic matrix elements methods microscopic mixed strategy motion NaSch model Nash equilibria obtained optimization orbit parameter particles payoff payoff matrix perceptron percolation phase space Phys player potential prediction probability problem properties quantum critical quantum phase transition random relaxation scaling Schreiber sequence shown in Fig shows simple simulated annealing simulations solution specific heat spin glasses Springer statistical mechanics statistical physics steps stochastic strategy structure temperature theory thermal threshold tree values vector velocity weight zero