Research Computing with Python

The python tools and numerical methods that I am learning and using for computational research in semiconductor device modeling, parameter extraction, and data analysis are collected in this repository.

Purpose

The aim of this repository is to collect and organize the python skills that I am learning and using for my research project, without getting sidetracked by learning unnecessary python topics.

This repository focuses on numerical computing, scientific data analysis, mathematical modeling, parameter extraction, and visualization.

Python Requirements

The most important libraries and tools that I am going to use are:

• numpy — numerical computing, arrays, mathematical operations
• scipy — optimization, fitting, numerical methods and equation solving
• matplotlib — plotting experimental, simulated, and fitted data
• pandas — structured data analysis

Other libraries may be added as needed during the research.

How I Will Be Using Python for My Research

I will be using python for:

1. Representing and manipulating numerical data
2. Mathematical modeling of semiconductor devices
3. Fitting theoretical models to experimental or reference data
4. Parameter extraction of physical models
5. Evaluating errors and residuals
6. Comparing models or parameters
7. Plotting experimental, simulated, and fitted data

The goal of this repository is not to learn python in general, but to learn the specific computational skills that I need for my research.

Structure

research-computing-with-python/
│
├── README.md
│
├── numpy/
│  └── numpy_notes.py
│
├── scipy/
│  └── scipy_notes.py
│
├── matplotlib/
│  └── matplotlib_notes.py
│
└── pandas/
└── pandas_notes.py