Advanced course on Computational Physics and Optimization for Ph.D. and MS students  (Fall 2024)

This course is devoted to advanced and more recent topics in computational methods for physics and including some topics for Optimization.

Link for class *********

Link for my previous lectures on Selected Topics

Link for my previous lectures on Computational Physics (SBU-VPN needed)

Link for my previous lectures on Computational Physics

Link for my lectures on Optimization (Khajeh Nasir Digital Library, SBU VPN needed)

Some topics to teach are as follows:

• Solving coupled Differential Equations and Boundary Value Problems
• Chaotic phenomena
• Probability Distribution functions and transformations
• Correlation functions, Two-point correlation function
• Spectral analysis
• Monte Carlo simulation
• Basic topics for Molecular dynamics simulations
• Simulation by VPython
• Machine learning in Physics
• Topological Based Data Analysis

• Course subjects and program (Download)
• Preliminary Part A (Download)
• Preliminary Part B (Download)
• A good movie presented by Pooyan Goodarzi to connect the server, remotely (Link)
• A good link for shell script programming (Link)
• Some of my bash samples (Download)
• A sample for Linux commands skills (Download)
• A good link for programming tutorials  (Link)
• A good presentation by Kip R. Irvine for number representation (Download)

• Hartmann, Alexander K., and Heiko Rieger. Optimization algorithms in physics. Vol. 2. Berlin: Wiley-Vch, 2002.

• Hartmann, Alexander K., and Heiko Rieger, eds. "New optimization algorithms in physics." (2004): 134411.

• Mezard, Marc, and Andrea Montanari. Information, physics, and computation. Oxford University Press, 2009.

• Computational Physics By RUBIN H. LANDAU, MANUEL JOSE PAEZ and CRISTIAN C. BORDEIANU (See this link)
• A good presentation by Kip R. Irvine for number representation (Download)
• A good text for commands in Fortran, C++, Matlab (Download)
• VPython
• Some necessary things for programming skills (Download)
• A good paper for data analysis in cosmology by Licia Verde, arXiv:0712.3028
• Online numerical recipes (http://www.numerical.recipes)
• My lectures on Errors and PDF (Download) (Download)
• Some of my Python programs (Download)
• Visualization by Matlab (link)
• Discretization approaches (Download) (Download)
• My note about deterministic Fractals (Download) & (see this link)
• A good reference for errors analysis (see this link)
• A proper series for Machine learning (Part 1), (part 2)
• School and Workshop on statistical analysis of stochastic fields (Link) (Link)
• A pedagogical matter for MCMC (Link)

My previous lectures (Link), (Link), (Link) and (Link)

• Preliminary Part (Download)
• Data Science 1 (Download)
• Number Representation (Download) (Download)
• Data Science 2 (Download)
• Error estimation (error estimation) my note included (error estimation)
• TDA (Download)
• A script for plotting figure by Python (Download)
• Quantum Machine Learning (Part1 & Part2) By Narges Eghbali and Anahid Kiani   (Film)
• Non-parametric modeling: Gaussian Processes (Download) By Ali Haghighatgoo
• Simulation-Based-Inferences workshop by Mohammad Hossein Jalali (Download)
• Some examples for numerical analysis by Mathematica By Adeela Afzal (Download)
• A sample for plotting figure by Mathematica with its export commands (Download)

1400816 (Download)  See also (Link)
1400818 (Download)
1400823 (Download)
1400825 (Download)
1400830 (Download)
1400902 (Download)
1400907 (Download)
1400909A (Download) 1400909B (Download)
Related papers for Fisher (Link), (Link), (Link)
1400928 (Download)
1400930 (Download)

Lectures 17 : Genetic Algorithm (Download), (comp990311B) Simple class of Genetic Algorithm- Part A, (comp990313) Simple class of Genetic Algorithm- Part B

Lectures 18 : Machine learning (part 1), (Part 2), Related code

Exams timeline

First midterm will be held at 1403/08/24  Questions with answer-key (Download) & Data (Download)   Send your results in zip format to numericalanalysis1403[at]gmail.com

Final exam  1403/11/01

Exercises:

# Set 1 (Download)  Necessary files (Q2-Part B) (Q2-Part E)

# Set 2 (Download)  Necessary file (DATA) (DATA 2) New version

# Set 3 (Download)  Necessary files (data)

# Set 4 (Download)  Necessary files (data)

# Set 5 (Download) & (Download) (data including 0.2.txt, 0.5.txt and 0.8.txt)

# Set 6 (Download) (1+1)-Dimensional data (Download) & (1+2)-Dimensional data (Download) & (Download)

# Set 7 (Download)

# Set 8 (Download)

# Set 9 (Download)