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Unsupervised machine learning for transient discovery in deeper, wider, faster light curves
(Oxford University Press, 2020)
Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced exceeding astronomers’ ability for manual ...
Considerations for optimizing the photometric classification of supernovae from the Rubin observatory
(IOP Publishing, 2022)
The Vera C. Rubin Observatory will increase the number of observed supernovae (SNe) by an order of
magnitude; however, it is impossible to spectroscopically confirm the class for all SNe discovered. Thus,
photometric ...
Optimization of the observing cadence for the Rubin observatory legacy survey of space and time: A pioneering process of community-focused experimental design
(IOP Publishing, 2022)
Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the
National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr ...
Practical galaxy morphology tools from deep supervised representation learning
(Oxford University Press, 2022)
Astronomers have typically set out to solve supervised machine learning problems by creating their own representations
from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question ...
The Impact of Observing Strategy on Cosmological Constraints with LSST
(2022)
The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely ...
Designing an optimal LSST deep drilling program for cosmology with type Ia supernovae
(American Astronomical Society, 2023)
The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) is forecast to collect a large sample of
Type Ia supernovae (SNe Ia) expected to be instrumental in unveiling the nature of dark energy. The feat, ...
Impact of Rubin observatory cadence choices on supernovae photometric classification
(American Astronomical Society, 2023)
The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will discover an unprecedented
number of supernovae (SNe), making spectroscopic classification for all the events infeasible. LSST will thus rely
on ...
Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
(The Astrophysical Journal Supplement Series, 2023)
The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will discover an unprecedented number of supernovae (SNe), making spectroscopic classification for all the events infeasible. LSST will thus rely on ...
A unique, ring-like radio source with quadrilateral structure detected with machine learning
(Oxford University Press, 2023)
We report the discovery of a unique object in the MeerKAT Galaxy Cluster Le gacy Survey (MGCLS) using the machine learning anomaly detection framework ASTRONOMALY. This strange, ring-like source is 30 from the MGCLS field ...