1. Molecular dynamics -- 1.1. Single particle -- 1.2. Time reversibility -- 1.3. Multiple particles -- 1.4. Randomness -- 1.5. Further reading -- 1.6. Problems -- 1.7. Challenges 2. Ising model -- 2.1. Monte Carlo method -- 2.2. Ising model -- 2.3. Critical temperature -- 2.4. Critical mixtures -- 2.5. Further reading -- 2.6. Problems -- 2.7. Challenges 3. Forest fires -- 3.1. Forest growth and fire ignition -- 3.2. Power-law behavior -- 3.3. Further reading -- 3.4. Problems -- 3.5. Challenges 4. The game of life -- 4.1. One-dimensional cellular automata -- 4.2. Conway's game of life -- 4.3. Majority rule -- 4.4. Further reading -- 4.5. Problems -- 4.6. Challenges 5. Brownian dynamics -- 5.1. Random walks and universality -- 5.2. Discrete white noise -- 5.3. Brownian motion -- 5.4. Optical tweezers -- 5.5. Further reading -- 5.6. Problems -- 5.7. Challenges 6. Anomalous diffusion -- 6.1. Anomalous diffusion exponent -- 6.2. Regularization and normalization -- 6.3. Models of anomalous diffusion -- 6.4. Anomalous diffusion in a non-homogeneous force field -- 6.5. Further reading -- 6.6. Problems -- 6.7. Challenges 7. Multiplicative noise -- 7.1. A minimal discrete-time model -- 7.2. Position-dependent noise -- 7.3. Stochastic integrals -- 7.4. The spurious drift -- 7.5. Drift and diffusion measurement -- 7.6. Particles close to an interface -- 7.7. Further reading -- 7.8. Problems -- 7.9. Challenges 8. The Vicsek model -- 8.1. The standard Vicsek model -- 8.2. The effect of delay -- 8.3. Non-metric and non-reciprocal interactions -- 8.4. Further reading -- 8.5. Problems -- 8.6. Challenges 9. Living crystals -- 9.1. Active Brownian motion -- 9.2. Mean square displacement -- 9.3. Living crystals -- 9.4. Aligning interactions -- 9.5. Further reading -- 9.6. Problems -- 9.7. Challenges 10. Sensory delay -- 10.1. A light-sensitive robot -- 10.2. Single robot with a sensory delay -- 10.3. Multiple robots with sensory delay -- 10.4. Further reading -- 10.5. Problems -- 10.6. Challenges 11. Disease spreading -- 11.1. The agent-based SIR model -- 11.2. Disease transmission as a function of the infection rate -- 11.3. Extended SIR models -- 11.4. Lockdown strategies -- 11.5. Further reading -- 11.6. Problems -- 11.7. Challenges 12. Network models -- 12.1. The adjacency matrix -- 12.2. Path length, diameter, and clustering coefficient -- 12.3. Erd�ios-R�enyi random graphs -- 12.4. Watts-Strogatz small-world graphs -- 12.5. Albert-Barab�asi preferential-growth graphs -- 12.6. Further reading -- 12.7. Problems -- 12.8. Challenges 13. Evolutionary games -- 13.1. The prisoner's dilemma -- 13.2. Evolutionary games on a lattice -- 13.3. Multiple strategies -- 13.4. Further readings -- 13.5. Problems -- 13.6. Challenges 14. Ecosystems -- 14.1. Lotka-Volterra model -- 14.2. The logistic growth model -- 14.3. Mutualism -- 14.4. Competition -- 14.5. Further reading -- 14.6. Problems -- 14.7. Challenges 15. Ant-colony optimization -- 15.1. The minimum path length problem -- 15.2. Ants at work -- 15.3. Interruptions, accidents, and randomness -- 15.4. Further reading -- 15.5. Problems -- 15.6. Challenges 16. The Sugarscape -- 16.1. Models of segregation -- 16.2. The Sugarscape -- 16.3. Further reading -- 16.4. Problems -- 16.5. Challenges.
This book deals with the most fundamental and essential techniques to simulate complex systems, from the dynamics of molecules to the spreading of diseases, from optimization using ant colonies to the simulation of the Game of Life.
Undergraduate and graduate students.
Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Aykut Argun is a PhD student in Physics at Gothenburg University. His research interests are optical trapping and manipulation, statistical physics, soft matter, active matter, machine learning technique applied to experimental data Analysis. Agnese Callegari is a researcher at the Physics Department of Gothenburg University. Her research interests are optical trapping and manipulation, statistical physics, soft matter, active matter. Giovanni Volpe is a Professor at the Physics Department of the University of Gothenburg University, where he leads the Active Matter Group. His research interests include soft matter, optical trapping and manipulation, statistical mechanics, brain connectivity, and machine learning.
9780750338431 9780750338424
10.1088/978-0-7503-3843-1 doi
Computer simulation. Computational complexity. Statistical physics. Mathematics and computation.