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Normalising Flows for Bayesian Gravity Inversion
Henrietta Rakoczi, Abhinav Prasad, Karl Toland +2
Gravity inversion is a commonly applied data analysis technique in the field of geophysics. While machine learning methods have previously been explored for the problem of gravity…
Cosmological Inference using Gravitational Waves and Normalising Flows
Federico Stachurski, Christopher Messenger, Martin Hendry
We present a machine learning approach using normalising flows for inferring cosmological parameters from gravitational wave events. Our methodology is general to any type of compa…
Quantum state preparation of gravitational waves
Fergus Hayes, Sarah Croke, Chris Messenger +1
We detail a quantum circuit capable of efficiently encoding analytical approximations to gravitational wave signal waveforms of compact binary coalescences into the amplitudes of q…
Importance nested sampling with normalising flows
Michael J. Williams, John Veitch, Chris Messenger
We present an improved version of the nested sampling algorithm nessai in which the core algorithm is modified to use importance weights. In the modified algorithm, samples are dra…