UsefulLinks
Physics
Applied and Interdisciplinary Physics
Computational Physics
1. Introduction to Computational Physics
2. Mathematical Foundations
3. Programming Fundamentals
4. Computer Arithmetic and Error Analysis
5. Root Finding Methods
6. Numerical Differentiation
7. Numerical Integration
8. Linear Systems
9. Eigenvalue Problems
10. Ordinary Differential Equations
11. Partial Differential Equations
12. Monte Carlo Methods
13. Molecular Dynamics
14. Data Analysis and Visualization
15. Applications in Classical Mechanics
16. Applications in Electromagnetism
17. Applications in Quantum Mechanics
18. Applications in Statistical Mechanics
19. Applications in Fluid Dynamics
20. High-Performance Computing
12.
Monte Carlo Methods
12.1.
Random Number Generation
12.1.1.
Pseudorandom Generators
12.1.2.
Linear Congruential Generators
12.1.3.
Mersenne Twister
12.1.4.
Testing Random Numbers
12.2.
Sampling Methods
12.2.1.
Inverse Transform Method
12.2.2.
Rejection Method
12.2.3.
Box-Muller Transform
12.3.
Markov Chain Monte Carlo
12.3.1.
Markov Chains
12.3.2.
Detailed Balance
12.3.3.
Ergodicity
12.3.4.
Metropolis Algorithm
12.3.5.
Metropolis-Hastings Algorithm
12.4.
Advanced Sampling Techniques
12.4.1.
Importance Sampling
12.4.2.
Stratified Sampling
12.4.3.
Antithetic Variates
12.5.
Applications
12.5.1.
Integration
12.5.2.
Optimization
12.5.3.
Statistical Physics
12.5.4.
Quantum Monte Carlo
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11. Partial Differential Equations
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13. Molecular Dynamics