Gaussian process regression for astronomical time series

S Aigrain, D Foreman-Mackey - Annual Review of Astronomy …, 2023 - annualreviews.org
The past two decades have seen a major expansion in the availability, size, and precision of
time-domain data sets in astronomy. Owing to their unique combination of flexibility …

The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys

F Lanusse - Publications of the Astronomical Society of Australia, 2023 - cambridge.org
The amount and complexity of data delivered by modern galaxy surveys has been steadily
increasing over the past years. New facilities will soon provide imaging and spectra of …

SALT3: An improved type ia supernova model for measuring cosmic distances

WD Kenworthy, DO Jones, M Dai… - The Astrophysical …, 2021 - iopscience.iop.org
A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool
for measuring precise and accurate distances across a large redshift range and constraining …

The Young Supernova Experiment: survey goals, overview, and operations

DO Jones, RJ Foley, G Narayan, J Hjorth… - The Astrophysical …, 2021 - iopscience.iop.org
Time-domain science has undergone a revolution over the past decade, with tens of
thousands of new supernovae (SNe) discovered each year. However, several observational …

Machine learning for observational cosmology

K Moriwaki, T Nishimichi… - Reports on Progress in …, 2023 - iopscience.iop.org
An array of large observational programs using ground-based and space-borne telescopes
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …

The young supernova experiment data release 1 (YSE DR1): light curves and photometric classification of 1975 supernovae

PD Aleo, K Malanchev, S Sharief… - The Astrophysical …, 2023 - iopscience.iop.org
Abstract We present the Young Supernova Experiment Data Release 1 (YSE DR1),
comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr …

First impressions: early-time classification of supernovae using host-galaxy information and shallow learning

A Gagliano, G Contardo… - The Astrophysical …, 2023 - iopscience.iop.org
Substantial effort has been devoted to the characterization of transient phenomena from
photometric information. Automated approaches to this problem have taken advantage of …

Unveiling the Universe with emerging cosmological probes

M Moresco, L Amati, L Amendola, S Birrer… - Living Reviews in …, 2022 - Springer
The detection of the accelerated expansion of the Universe has been one of the major
breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave …

Cosmological results from the RAISIN survey: using Type Ia Supernovae in the near infrared as a novel path to measure the dark energy equation of state

DO Jones, KS Mandel, RP Kirshner… - The Astrophysical …, 2022 - iopscience.iop.org
Abstract Type Ia supernovae (SNe Ia) are more precise standardizable candles when
measured in the near-infrared (NIR) than in the optical. With this motivation, from 2012 to …

Searching for changing-state agns in massive data sets. i. applying deep learning and anomaly-detection techniques to find agns with anomalous variability behaviors

P Sánchez-Sáez, H Lira, L Martí… - The Astronomical …, 2021 - iopscience.iop.org
The classic classification scheme for active galactic nuclei (AGNs) was recently challenged
by the discovery of the so-called changing-state (changing-look) AGNs. The physical …