208 citations · 2.3k across the 64 of their papers we have counts for
11 papers · 1 filter
pop-cosmos: Disentangling galaxy properties from observables using data-driven approaches
Benedict Van den Bussche, Sinan Deger, Hiranya V. Peiris +6
The physical processes that shape a galaxy's spectrum are strongly degenerate in observations, obscuring which processes act independently. Leveraging the pop-cosmos generative gal…
pop-cosmos: Galaxy size evolution across structural and star-formation classifications in COSMOS-Web
Madalina N. Tudorache, Hiranya V. Peiris, Stephen Thorp +7
Galaxy sizes are correlated with stellar mass and redshift, as characterised by size scaling relations. The inferred forms of these scaling relations are sensitive to how galaxies…
pop-cosmos: Redshifts and physical properties of KiDS-1000 galaxies
Anik Halder, Hiranya V. Peiris, Stephen Thorp +8
Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak lensing surveys with millions of sources. We address this gap by applying th…
pop-cosmos: Star formation over 12 Gyr from generative modelling of a deep infrared-selected galaxy catalogue
Sinan Deger, Hiranya V. Peiris, Stephen Thorp +5
We study star formation over 12 Gyr using pop-cosmos, a generative model trained on 26-band photometry of 420,000 COSMOS2020 galaxies (IRAC Ch.1 ). The model learns distributi…
pop-cosmos: Insights from generative modeling of a deep, infrared-selected galaxy population
Stephen Thorp, Hiranya V. Peiris, Gurjeet Jagwani +6
We present an extension of the pop-cosmos model for the evolving galaxy population up to redshift . The model is trained on distributions of observed colors and magnitudes,…
pop-cosmos: A comprehensive picture of the galaxy population from COSMOS data
Justin Alsing, Stephen Thorp, Sinan Deger +4
We present pop-cosmos: a comprehensive model characterizing the galaxy population, calibrated to ( selected) galaxies from the Cosmic Evolution Survey (COSMOS) with…
Mapping Interstellar Dust with Gaussian Processes
Andrew C. Miller, Lauren Anderson, Boris Leistedt +3
Interstellar dust corrupts nearly every stellar observation, and accounting for it is crucial to measuring physical properties of stars. We model the dust distribution as a spatial…
Red clump stars and Gaia: Calibration of the standard candle using a hierarchical probabilistic model
Keith Hawkins, Boris Leistedt, Jo Bovy +1
Distances to individual stars in our own Galaxy are critical in order to piece together the nature of its velocity and spatial structure. Core helium burning red clump (RC) stars h…
Improving \textsl{Gaia} parallax precision with a data-driven model of stars
Lauren Anderson, David W. Hogg, Boris Leistedt +2
Converting a noisy parallax measurement into a posterior belief over distance requires inference with a prior. Usually this prior represents beliefs about the stellar density distr…
A new perspective on turbulent Galactic magnetic fields through comparison of linear polarisation decomposition techniques
J. -F. Robitaille, A. M. M. Scaife, E. Carretti +8
We compare two rotationally invariant decomposition techniques on linear polarisation data: the spin-2 spherical harmonic decomposition in two opposite parities, the - and -m…
No galaxy left behind: accurate measurements with the faintest objects in the Dark Energy Survey
E. Suchyta, E. M. Huff, J. Aleksić +72
Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have have rel…