Tom J. Wilson

CV and Publications

See here to view Tom J. Wilson’s CV, publication list, and talks.

Scientific Research

Tom J. Wilson is a postdoctoral research fellow at the University of Exeter. He is working on the problem of cross-matching photometric catalogues in deep, crowded fields, as part of the LSST:UK consortium. This work further develops from a program he created during his PhD, which highlighted the implications the effects that blended sources can have on the derived properties of astrophysical sources. For his LSST:UK postdoctoral research he is developing software pipelines that will be applied to deep field and time series LSST catalogues, as well as a host of external datasets.

Tom J. Wilson received his MPhys in Physics with Astrophysics from the University of Exeter, UK, in 2013. He analysed the effects of age and distance on the initial mass function of young star clusters. His work included characterisation of the choice of filters in a colour-colour diagram, determining the optimal choice of filters for age independent extinction for low mass stars in young star clusters. This work was instrumental in subsequent analysis of the Taurus star forming region, due to the significant and differential reddening across the region.

Tom J. Wilson has worked with JCMT SCUBA-2 data, making improvements to data reduction of 450μm and 850μm observations. He subsequently worked on the construction of temperature and dust β maps of these observations, including Herschel datasets to supplement the SCUBA-2 data, resulting in published analyses of NGC1333 and W40.

Tom J. Wilson then received his PhD in Physics from the University of Exeter, UK, in 2018, with his thesis “Solving the Catalogue Cross-Match Problem in the Galactic Plane”. Working with Prof. Tim Naylor, his thesis focussed on the effects blended stars have on the astrometric and photometric properties of stars in crowded Galactic fields. He characterised various photometric catalogues by angular resolution and survey completeness, allowing for quantitative comparisons between published datasets, and the levels to which they suffer from the crowding of detected sources. He then constructed a probability-based Bayesian cross-matching process, allowing for the symmetric determination of the same source detected in two photometric catalogues in a robust manner. Tom J. Wilson then combined these two advancements to produce a fully flexible framework for handling the astrometric and photometric perturbations caused by blended sources within the detections of brighter sources, applying the methodology to the cross-matching of Gaia and WISE datasets, the results of which can be found here.

Tom J. Wilson was a postdoctoral researcher at the Space Telescope Science Institute, working with Dr Lou Strolger on supernovae: both in the present with the BUFFALO program and the Hubble Space Telescope, and in the future with the Wide Field Infrared Survey Telescope, optimising its potential survey parameters to produce a dataset of supernovae best suited to determining the Hubble constant.

As an avid astrostatistician, Tom J. Wilson is committed to robust methodology and transparent assumptions, as can be seen from the work he undertook throughout his PhD. He enjoys the deeper understanding obtainable from judicious application of Bayesian statistics, with proper application of Bayes’ (or should that be de Moivre’s?!) theorem to break a problem down into its fundamental properties: prior knowledge and updates to that knowledge with the data likelihood. He occasionally dabbles in exoplanet research, ensuring that the statistical analysis of exoplanet transmission spectra is as thorough as possible, and the results drawn from these challenging datasets are correctly interpreted and well represented.

Software Development and Programming Work

Tom J. Wilson is also working on the development of the AstroPy photutils codebase. Here he is leveraging his expertise in photometry, and specifically work with point-spread functions, to expand on and improve the photutils code surrounding the fitting of point sources in astronomical images.

He is also developing the open source photometric catalogue cross-match code macauff, a statistically robust code for the merging of photometric datasets including the effects of blended objects on the positions and fluxes of sources.

Page updated March 2024