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Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning
Edward Higson, Will Handley, Michael Hobson +1
We present a principled Bayesian framework for signal reconstruction, in which the signal is modelled by basis functions whose number (and form, if required) is determined by the d…
Physical modelling of galaxy clusters detected by Planck
Kamran Javid, Malak Olamaie, Yvette C. Perrott +5
We present a comparison of mass estimates for galaxy cluster candidates from the second Planck catalogue (PSZ2) of Sunyaev-Zel'dovich sources. We compare the mass values obtai…
Comparison of physical and observational galaxy cluster modelling
Kamran Javid, Yvette C. Perrott, Michael P. Hobson +3
We present a comparison between three cluster models applied to data obtained by the Arcminute Microkelvin Imager radio interferometer system. The physical model (PM) parameterises…
Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations
Alvin J. K. Chua, Sonke Hee, Will J. Handley +5
Extreme-mass-ratio-inspiral observations from future space-based gravitational-wave detectors such as LISA will enable strong-field tests of general relativity with unprecedented p…
An alternative approach to modelling a cosmic void and its effect on the cosmic microwave background
Do Young Kim, Anthony N. Lasenby, Michael P. Hobson
We apply our tetrad-based approach for constructing spherically-symmetric solutions in general relativity to modelling a void, and compare it with the standard Lemaître-Tolman-Bond…
nestcheck: diagnostic tests for nested sampling calculations
Edward Higson, Will Handley, Mike Hobson +1
Nested sampling is an increasingly popular technique for Bayesian computation, in particular for multimodal, degenerate problems of moderate to high dimensionality. Without appropr…