Chakradhar Rangi

Chakradhar Rangi

Doctoral candidate in computational physics

Louisiana State University

Welcome!

I’m a Physics PhD candidate at Louisiana State University, where I build computational models to understand the strange world of quantum materials.

My research lies at the intersection of computational physics and condensed matter theory. I specialize in developing advanced numerical algorithms to simulate complex phenomena in strongly correlated and disordered quantum systems. A core part of my work involves the development and application of quantum embedding theories, such as Dynamical Mean-Field Theory, to probe the non-equilibrium dynamics of these systems. I’m also captivated by the fascinating physics of non-Hermitian quantum phenomena, including the non-Hermitian skin effect. At LSU, I am fortunate to be mentored by Prof. Juana Moreno and Dr. Ka-Ming Tam.

My journey in physics includes a BS-MS Dual Degree from the Indian Institute of Science Education and Research Bhopal. For my MS thesis, I contributed to the LITESOPH project by developing efficient scientific codes to model non-adiabatic dynamics. I’ve also had the privilege of applying my skills in diverse settings, including a summer internship at Los Alamos National Laboratory modeling non-linear light-matter interactions and as a long-term research visitor at Jawaharlal Nehru Center for Advanced Scientific Studies.

When I’m not running simulations, I enjoy playing cricket, table tennis, and chess. I’m an avid chess player on Chess.com (rapid controls are my favorite). Fancy a game? Challenge me: qtinkerer.

I’m always open to discussing physics, new research, or potential collaborations. Feel free to explore my publications, or connect with me on LinkedIn.

Peer Reviewer: Physical Review B, Physical Review A, Chaos

Interests
  • Computational Condensed Matter Physics
  • Non-Hermitian Topological Phases
  • AI for Science
  • Quantitative Finance
Education
  • Ph.D. in Physics, 2021 - Present

    LSU

  • BS-MS in Physics, 2020

    IISER Bhopal

Projects

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Beyond Black and White: Adapting Models to Visual Domain Shift

Beyond Black and White: Adapting Models to Visual Domain Shift

Demonstrated Unsupervised Domain Adaptation (UDA) from MNIST to MNIST-M using MMD and Domain-Adversarial Neural Networks (DANN) in PyTorch.

Quantifying Negative Convexity in Mortgage-Backed Securities

Quantifying Negative Convexity in Mortgage-Backed Securities

Developed a quantitative framework to model the cash flows and price sensitivity of Mortgage-Backed Securities (MBS). The primary focus is investigating the phenomenon of Negative Convexity—the asymmetric risk profile caused by the embedded homeowner prepayment option.

Bee Health Early Warning System - Erdos Institute Data Science Bootcamp

Bee Health Early Warning System - Erdos Institute Data Science Bootcamp

Developed a model to predict the Bee Hive health using localized weather data and a standardized checklist of health indicators.

Real-Space Dynamical Mean-Field Theory (R-DMFT) for non-Hermitian strongly correlated systems

Real-Space Dynamical Mean-Field Theory (R-DMFT) for non-Hermitian strongly correlated systems

A Python implementation of Real-Space Dynamical Mean-Field Theory (R-DMFT) designed to handle non-Hermitian Hamiltonians using IPT impurity solver.

crangi.github.io

crangi.github.io

Personal research and portfolio website built with Hugo, hosted on GitHub, and automatically deployed via GitHub Pages.

Erdos Institute Quant Finance Bootcamp

Erdos Institute Quant Finance Bootcamp

A series of mini-projects implementing Modern Portfolio Theory, volatility modeling, and risk-management strategies using Python and stochastic calculus.

MS Thesis

MS Thesis

Development of a Python Code for modelling Trajectory Surface Hopping on Ab Initio Potential Energy Surfaces

Recent Publications

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