6 citations · 12 across the 7 of their papers we have counts for
8 papers
Photometric redshifts for active galactic nuclei with LePHARE for the Vera C. Rubin Observatory
R. Shirley, M. Salvato, J. Cohen-Tanugi +31
Active Galactic Nuclei (AGN) play a crucial role in galaxy evolution, but they are a minority of extragalactic sources with diverse Spectral Energy Distributions (SEDs), which depe…
LightCurveLynx: Forward Modeling of Time-Domain Surveys with Application to ZTF SN Ia DR2
Mi Dai, Jeremy Kubica, Konstantin Malanchev +5
We present LightCurveLynx, a flexible and extensible software framework for end-to-end forward modeling time-domain light curves. Given the growing need for realistic simulations i…
Diagnosing the Effects of Spectroscopic Training Set Imperfection on Photometric Redshift Performance
Alice Crafford, Alex I. Malz, Tianqing Zhang +11
Most LSST extragalactic science will rely on photometric redshifts (photo-) to extract distance information for the galaxies. However, an incomplete or non-representative traini…
Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)
T. Zhang, E. Charles, J. F. Crenshaw +87
We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and…
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…
Redshift Assessment Infrastructure Layers (RAIL): Rubin-era photometric redshift stress-testing and at-scale production
The RAIL Team, Jan Luca van den Busch, Eric Charles +31
Virtually all extragalactic use cases of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require the use of galaxy redshift information, yet the vast majorit…
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…