Detecting GW signals from extreme mass ratio inspirals using convolutional autoencoders
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Updated
Nov 7, 2024 - Jupyter Notebook
Detecting GW signals from extreme mass ratio inspirals using convolutional autoencoders
Dark-siren cosmology with LISA EMRIs — end-to-end engine (GPU EMRI simulation, Fisher/CRB, GLADE+ completeness-corrected H0 inference) with an instructive book
Mathematica scripts used to produce the results presented in https://doi.org/10.1103/PhysRevD.111.104006
Master Thesis - New numerical methods for the computation of the self-force around Black Holes
Python pipeline for comparing EMRI surrogate and EOBNRv2HM gravitational wave models across extreme mass ratios. Quantifies waveform mismatch, merger-region error, and computation time. Includes diagnostics that identified a float32 precision bug in the EMRI surrogate model. Built for HPC.
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