Computational Physics

Designing a C++ foundation for simulating rocket flight dynamics using custom 3D vector mathematics, including position, gravity, forces, and navigation-related calculations.

Two Monte Carlo case studies built from first principles: modeling energy deposition in a CERN ATLAS-style calorimeter cell via inverse transform sampling, and simulating a year of stock price paths with geometric Brownian motion.

Public integration layer I built from the upstream SpenderQ framework (galactic-ai/SpenderQ) for the UW Bothell quasar research group: a data-driven Python stack that embeds the Spender convolutional spectrum autoencoder to reconstruct intrinsic quasar continua, mask absorption (including the Lyman-α forest), and batch-process large spectroscopic datasets. Complements the group’s EHVO analysis pipeline as an ML-based continuum fallback when classical normalization is insufficient.

My previous working branch of the UW Bothell quasar research group's collaborative codebase: Python tools for normalizing raw SDSS spectra, flagging absorption troughs, and running cross-correlation, redshift, and variability analyses to isolate extremely high-velocity outflow (EHVO) quasars from the DR16 sample. Using this pipeline I successfully identified the fastest outflow in the universe autonomously; it is scaled to process thousands of spectra at a time. Note: Most up to date codebase is hosted on a private repository, commits to be merged later.

Derived Planck's constant from scratch by measuring the threshold voltage of four LED colors and relating the slope of voltage-vs-frequency to h, landing within 3.7% of the accepted value using a low-cost breadboard circuit.

Built a polarizer-and-double-slit setup to test at what polarization angle a photon's which-path information is erased, mapping interference-fringe visibility against filter angle to pinpoint the laser's dominant polarization axis.