Fast Fisher Matrices and Lazy Likelihoods

TL;DR

This paper introduces a computationally efficient method for calculating Fisher matrices and likelihoods in gravitational wave analysis, avoiding full waveform computations and accelerating Bayesian inference.

Contribution

It presents an alternative technique that significantly reduces computational costs in gravitational wave data analysis by bypassing full waveform calculations.

Findings

Method achieves faster Fisher matrix computation

Speeds up Bayesian inference on real data

Reduces computational resources needed

Abstract

Theoretical studies in gravitational wave astronomy often require the calculation of Fisher Information Matrices and Likelihood functions, which in a direct approach entail the costly step of computing gravitational waveforms. Here I describe an alternative technique that sidesteps the need to compute full waveforms, resulting in significant computational savings. I describe how related techniques can be used to speed up Bayesian inference applied to real gravitational wave data.