activity
20202026
most citedQuaia, the Gaia-unWISE Quasar Catalog: An All-Sky Spectroscopic Quasar Sample

72 citations · 383 across the 20 of their papers we have counts for

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Showing astro-ph.GAShow all

6 papers · 1 filter

astro-ph.GA2025

Quasar clustering and duty cycle measurements at with the Gaia-unWISE Catalog

Mariona Giner Mascarell, Anna-Christina Eilers, Kate Storey-Fisher

We measure the two-point correlation function of a uniformly selected, all-sky sample of 1.3 million quasars with magnitudes from the Gaia--unWISE Quasar Catalog…

astro-ph.GA2023★ 72 cited

Quaia, the Gaia-unWISE Quasar Catalog: An All-Sky Spectroscopic Quasar Sample

Kate Storey-Fisher, David W. Hogg, Hans-Walter Rix +4

We present a new, all-sky quasar catalog, Quaia, that samples the largest comoving volume of any existing spectroscopic quasar sample. The catalog draws on the 6,649,162 quasar can…

astro-ph.GA2021★ 37 cited

Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

Kate Storey-Fisher, Marc Huertas-Company, Nesar Ramachandra +5

The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection m…

astro-ph.GA2021★ 50 cited

The Low Redshift Circumgalactic Medium in Simba

Sarah Appleby, Romeel Davé, Daniele Sorini +2

We examine the properties of the low-redshift circumgalactic medium (CGM) around star-forming and quenched galaxies in the Simba cosmological hydrodynamic simulations, focusing on…

astro-ph.GA2020★ 3 cited

Anomaly Detection in Astronomical Images with Generative Adversarial Networks

Kate Storey-Fisher, Marc Huertas-Company, Nesar Ramachandra +4

We present an anomaly detection method using Wasserstein generative adversarial networks (WGANs) on optical galaxy images from the wide-field survey conducted with the Hyper Suprim…

astro-ph.GA2020★ 58 cited

Detecting outliers in astronomical images with deep generative networks

Berta Margalef-Bentabol, Marc Huertas-Company, Tom Charnock +5

With the advent of future big-data surveys, automated tools for unsupervised discovery are becoming ever more necessary. In this work, we explore the ability of deep generative net…