6 citations · 13 across the 9 of their papers we have counts for
9 papers
Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid
Aritra Ghosh, Drew Oldag, Michael Tauraso +29
The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-domain data at scales that inc…
photoD with Rubin's Data Preview 1: first stellar photometric distances and deficit of faint blue stars. Stellar distances with Rubin's DP1
L. Palaversa, E. Donev, Ž. Ivezić +96
Aims: We investigate the utility of Rubin's Data Preview 1 for estimating stellar number density profile in the Milky Way halo. Methods: Stellar broad-band near-UV to near-IR $ugri…
A Systematic Search for Main-Sequence Dipper Stars Using the Zwicky Transient Facility
Anastasios Tzanidakis, James R. A. Davenport, Neven Caplar +8
Main-sequence dipper stars, characterized by irregular and often aperiodic luminosity dimming events, offer a unique opportunity to explore the variability of circumstellar materia…
Variability-finding in Rubin Data Preview 1 with LSDB
Konstantin Malanchev, Melissa DeLucchi, Neven Caplar +56
The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in t…
Optical Counterparts to X-ray sources in LSST DP1
Yuankun, Wang, Eric C. Bellm +9
We present a crossmatch between a combined catalog of X-ray sources and the Vera C. Rubin Observatory Data Preview 1 (DP1) to identify optical counterparts. The six fields targeted…
PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy
Lovro Palaversa, Željko Ivezić, Neven Caplar +14
As demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently with Gaia data, broadband near-UV to near-IR stellar photometry can be used to estimate dist…
Using LSDB to enable large-scale catalog distribution, cross-matching, and analytics
Neven Caplar, Wilson Beebe, Doug Branton +9
The Vera C. Rubin Observatory will generate an unprecedented volume of data, including approximately 60 petabytes of raw data and around 30 trillion observed sources, posing a sign…
DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST
Grant Merz, Xin Liu, Samuel Schmidt +11
Photometric redshifts will be a key data product for the Rubin Observatory Legacy Survey of Space and Time (LSST) as well as for future ground and space-based surveys. The need for…
Superphot+: Realtime Fitting and Classification of Supernova Light Curves
Kaylee M. de Soto, Ashley Villar, Edo Berger +9
Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential of large samples of observations obtained from wide-field photometric…