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# 10820PHYS401200
# 電腦與計算物理 Computational Physics

## Instructor
* Prof. Pochung Chen.
* R521, Physics building.
* pcchen {at} phys {dot} nthu {dott} edu {dot} tw .

## Time
* M5M6M7.

## Room
* R501, Physics building.

## Syllabus

## Development Environment Setup
Check list
* Python: Anaconda Python Distribution.
  * Python packages: numpy scipy jupyterlab matplotlib.
* Git: Git for windows/mac.

### Python 3
* Install [Anaconda Python Distribution](https://www.anaconda.com/distribution/), Python 3.x version.
  * “Just Me” (Windows), Install for me only (macOS).
* Use [conda](https://conda.io/projects/conda/en/latest/index.html) to create a virtual environment. conda 4.7.x
  * [Starting conda](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#starting-conda).
    * Window: From the Start menu, search for and open "Anaconda Prompt."
  * [Managing environments](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-environments) 
    * Check conda version: `conda --version`
      * `conda update -n base -c defaults conda`
    * Create a new environment: `conda create --name mydev`
    * To use, or "activate" the new environment: `conda activate mydev`
      * `conda install numpy scipy jupyterlab matplotlib`
    * To see a list of all your packages: `conda list`
    * To see a list of all your environments: `conda info --envs`
    * Change your current environment back to the default (base): `conda activate`

#### Packages and references
  * [Numpy](https://numpy.org)
  * [SciPy](https://www.scipy.org)
  * [JupyterLab](https://jupyterlab.readthedocs.io)
  * [Matplotlib](http://matplotlib.org)
  * [Scipy Lecture Notes](https://scipy-lectures.org)

#### Tensor Network related
* Install [pyuni10 (v2.1.2)](https://anaconda.org/uni10/pyuni10) from anaconda cloud.
  * `conda install -c uni10 pyuni10'

### Git version control system
  * [Git official website](https://git-scm.com)
  * `git clone URL`
  * `git status`
  * `git add filenames`
  * `git commit`
  * `git push`

### Github
* [NTHU-Phys-Qubit](https://github.com/NTHU-Phys-Qubit)
* [10820PHYS401200](https://github.com/NTHU-Phys-Qubit/10820PHYS401200)

## Reference
* [Introduction to Monte Carlo methods for an Ising Model of a Ferromagnet](https://arxiv.org/abs/0803.0217) by Jacques Kotze.
* [Everything You Wanted to Know About Data Analysis and Fitting but Were Afraid to Ask](https://www.springer.com/la/book/9783319190501) by Peter Young. 
  * [arXiv](https://arxiv.org/abs/1210.3781) version.
* [Computational Studies of Quantum Spin Systems](https://arxiv.org/abs/1101.3281) by Anders W. Sandvik.
* [The density-matrix renormalization group in the age of matrix product states](https://doi.org/10.1016/j.aop.2010.09.012) by Ulrich Schollwöck.
* [Prof. Frank Pollmann](http://tccm.pks.mpg.de)
  * [comp-phys](https://www.pks.mpg.de/~frankp/comp-phys/)
* [Prof. Xin Wan](http://zimp.zju.edu.cn/~xinwan/)
  * [Understand the MPS formalism and the iTEBD algorithm](http://zimp.zju.edu.cn/~xinwan/courses/qiqc15/projects.php)
* [Note for iTEBD](https://www.dropbox.com/s/ubhe70yy6zo528i/Notepad_iTEBD_Tor10.pdf?dl=0)
* [Supervised Learning with Quantum-Inspired Tensor Networks](https://arxiv.org/abs/1605.05775).
  * [Sample codes](https://github.com/emstoudenmire/TNML)
* [Learning Relevant Features of Data with Multi-scale Tensor Networks](https://arxiv.org/abs/1801.00315)  
* [Unsupervised Generative Modeling Using Matrix Product States](https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.031012)
* [Deep Learning and Quantum Programming" Spring School @ Song Shan Lake](https://github.com/QuantumBFS/SSSS)
* [Towards Quantum Machine Learning with Tensor Networks](https://iopscience.iop.org/article/10.1088/2058-9565/aaea94/meta)
* [Tree Tensor Networks for Generative Modeling](https://arxiv.org/abs/1901.02217)

## Python
* [Python.org](https://www.python.org)
  * [Anaconda Distribution](https://www.anaconda.com/distribution/)
    * [Download](https://www.anaconda.com/distribution/#download-section)
* [Jupyter](https://jupyter.org)
* [Numpy](http://www.numpy.org)
* [Matplotlib](https://matplotlib.org)
* [PyFormat](https://pyformat.info)
* [UNI10](https://uni10.gitlab.io) Universal Tensor Network Library.
  * [Tor10](https://github.com/kaihsin/Tor10) A Generic Tensor-Network library that is designed for quantum simulation, base on the pytorch.

## Git & Github repository

## Homework
* [Homework-1 GitHub Classroom link](https://classroom.github.com/a/4jPRbsOu), due on 4/13/2020.
* [Homework-2 GitHub Classroom link](https://classroom.github.com/a/pn5w_3az), due on 4/13/2020.
* [Homework-3 GitHub Classroom link](https://classroom.github.com/a/s8QuHXSZ)
  * https://journals.aps.org/pr/abstract/10.1103/PhysRev.185.832
* [Homework-4 GitHub Classroom link](https://classroom.github.com/a/pIFWZMyg)
  * https://journals.aps.org/prb/abstract/10.1103/PhysRevB.86.045139
* [Homework-5 GitHub Classroom link](https://classroom.github.com/a/y3IMqBip)

### Weekly schedule
* Week 1: 3/2/2020
  * Introduction.
  * Development environment.
* Week 2: 3/9/2020
  * Numpy, Matplotlib.
  * Git.
* Week 3: 3/16/2020
  * NumPy linear albegra: numpy.linalg 
  * Random walk.
  * Ising model.
* Week 4: 3/23/2020
  * Transfer matrix for classical 1D Ising model.
  * [YouTube](https://youtu.be/oAijmr-D7h4)
  * [Note](https://www.dropbox.com/s/iqvgn6r8dee9x97/CompPhys_20200323.pdf?dl=0)
* Week 5: 3/30/2020
  * Transfer matrix for classical 1D Ising model.
  * [YouTube](https://youtu.be/1B_NRng29Z4)
  * [Note](https://www.dropbox.com/s/txg96jxfook6eoc/CompPhys_20200330.pdf?dl=0)
* Week 6: ~~4/6/2020~~ (No class)
  * 校際活動週(停課一日)
* Week 7: 4/13/2020
  * [YouTube](https://youtu.be/OuxsV06oA1s)
  * [Note](https://www.dropbox.com/s/bgap6m3p729mi3o/CompPhys_20200413.pdf?dl=0)
  * Tensor network diagram.
  * Tensor renormalization group.
  * Singular value decomposition.
  * HW1, HW2 due.
* Week 8: 4/20/2020
  * [YouTube](https://youtu.be/2gqM95h5g6Y)
  * [Note](https://www.dropbox.com/s/03xidg4xg3am9zt/CompPhys_20200420.pdf?dl=0)
  * 2D Ising model, exact solution.
  * 2D Ising model, tensor network representation.
* Week 9: 4/27/2020
  * [Note](https://www.dropbox.com/s/4ylao6whfdd9wmr/CompPhys_20200427.pdf?dl=0)
* Week 10: 5/4/2020
  * [Note](https://www.dropbox.com/s/l3gd79rlahscc9v/CompPhys_20200504.pdf?dl=0)
* Week 11: 5/11/2020
  * [Note](https://www.dropbox.com/s/oiidvujlajtlsjh/CompPhys_20200511.pdf?dl=0)
* Week 12: 5/18/2020
  * [YouTube](https://youtu.be/2B6dZGeH3wg)
  * [Note](https://www.dropbox.com/s/083xpkslqlgs7b8/CompPhys_20200518.pdf?dl=0)
* Week 13: 5/25/2020
* Week 14: 6/1/2020
  * [Note](https://www.dropbox.com/s/rlxq1mevzypevts/CompPhys_20200601.pdf?dl=0)
* Week 15: 6/8/2020
  * [Note](https://www.dropbox.com/s/pkkuiul85mo14es/CompPhys_20200608.pdf?dl=0)
* Week 16: 6/15/2020
* Week 17: 6/22/2020
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