Computational Methods for Physics

In House

Manager: Suyash Kumar

Contact: suyashsep12@gmail.com

Applications: Open

Learning Objectives: Simulation, Machine Learning, Programming (Python, Octave)

With the advent of computational power, the use of programming skills is becoming more central to both experimental and theoretical avenues of Physics. While labs deal very thoroughly with data analysis and plotting, two things often neglected are simulations and predictive models – and these can be great assets to a Physicist in order to extend and deepen their knowledge about physical systems. This project focuses on exactly these two aspects – simulation of various physical phenomena and development of predictive models via machine learning – and hopes to add to the already diverse skill set of Physics majors.