The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public, but we request that all who plan to attend register in advance.

Monitoring the fidelity of the LIGO detectors

The detection of gravitational waves depends on LIGO’s ability to discriminate authentic signals from instrumental noise. To improve this capability, the LIGO Scientific Collaboration employs hardware injections, controlled, simulated signals introduced directly into the detectors. These injections validate the analysis pipelines and refine the calibration of the detector. This study focuses on continuous- wave signals from the initial phase of the fourth observing run (O4a), using simulated emissions from rapidly rotating neutron stars as benchmarks to assess sensitivity and data-processing efficiency. The analysis employs a template generation approach that uses complex conjugates to align observational data with theoretical signal templates and offers probabilistic validation of detected signals. An investigation explores the role of hardware injections in the refinement of software models and the maintenance of the timing and amplitude. By utilizing daily diagnostic plots for a diverse array of synthetic neutron star signals, including both binary and isolated systems, the detector’s responsiveness is evaluated over a broad frequency spectrum. The results emphasize the importance of hardware injections in sustaining calibration standards and affirming LIGO’s reliability in gravitational wave detection

Preet Baxi, Physics and Scientific Computing

Preet Baxi is an innovative Data Scientist and Algorithm Developer with experience in scientific computing, data pipeline optimization, and business data analysis. Specializing in developing advanced algorithms and has worked extensively in gravitational wave data analysis, contributing to cutting-edge research in astrophysics. Currently working in large language models (LLMs), focusing on their development and optimization.

Fast Summation for Geophysical Fluid Dynamics

Fast Summation refers to a family of techniques for the fast approximation of N-body sums. While traditionally fast summation has been applied to problems coming from astrophysics or electrodynamics, many problems in geophysical fluid dynamics can be rewritten as the computation of a spherical convolution, and when these integrals are discretized, the resulting problem is a N-body problem. In this talk, I discuss a novel spherical tree code/fast multipole method based on barycentric Lagrange interpolation, as well as applications to problems coming from geophysical fluid dynamics, including tidal modeling and the problem of computing Self Attraction and Loading in the ocean model MOM6.

Anthony Chen, Applied and Interdisciplinary Mathematics and Scientific Computing

Anthony Chen is a 4th year in Applied and Interdisciplinary Mathematics working on fast summation for problems in geophysics.