Toward a hyper-empirical gravitational wave source localization routine based on the Northstar algorithm (Tom McClain)

On campus: this project is scheduled to begin on 6/23/2025 and run for 8 weeks, finishing on 8/15/2025.

Project Description

The primary purpose of this research project is to determine if it is possible to build a hyper-empirical gravitational wave source localization routine around the Northstar algorithm I developed some years ago. This routine would use empirical signal modeling techniques similar to those (presumably) used by neural networks to perform source localization very quickly (i.e., on the same time scales as a neural network) while maintaining full control over parameter choices and failure modes (like the traditional approach using numerical templates from general relativity). Depending upon the success or failure of the initial builds, the project may also include testing or refinement of the routine, from small tweaks in program parameters up full runs on realistic data sets using cutting-edge GPUs on Amazon Web Services.

Prerequisites

The ideal candidate would have completed PHYS 111, PHYS 112, and CS 111, and would have at least a small amount of experience with SciPy or NumPy. But the most important criteria is engagement; interested students should apply regardless of previous experience.

Special Comments

Project Information (subject to change)

Estimated Start Date: 6/23/2025

Estimated End Date: 8/15/2025

Estimated Project Duration: 8 weeks

Maximum Number of Students Sought: 3

Research Location: On campus

Contact Information: Tom McClain (email: mcclaint@wlu.edu)