activity
20212026
most citedImproving the reliability of photometric redshift with machine learning

30 citations · 63 across the 6 of their papers we have counts for

collaborators

7 papers

astro-ph.IM2026

Vera C. Rubin LSST Synthetic Magnitudes derived from Gaia XP Spectra

Oleksandra Razim, Krešimir Tisanič, Lovro Palaversa

Context. In the context of Milky Way studies, the Vera C. Rubin Observatory's Legacy Survey of Space and Time is often described as a deep extension of the Gaia survey. In the futu…

astro-ph.SR2026

A Pilot Study to Verify the RR Lyrae Candidates with Vera C. Rubin Observatory Early Alerts

Chow-Choong Ngeow, Anupam Bhardwaj, Sarang Shah +2

We present a pilot study using the Vera C. Rubin Observatory early alerts to verify RR Lyrae candidates in the Pan-STARRS1, the Dark Energy Survey, and the Next-Generation Virgo Cl…

astro-ph.IM2026

Toward decision-aware AI for LSST-scale time-domain astronomy

C. R. Bom, A. Mahabal, F. Bianco +27

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will generate approximately (10^7) alerts per night, pushing time-domain astronomy beyond pipelines that trea…

astro-ph.SR2025★ 2 cited

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…

astro-ph.GA2025★ 3 cited

Time Evolution of Mg II in SDSS J2320+0024: Implications for a Subparsec Binary Supermassive Black Hole System

Marta Fatović, Dragana Ilić, Andjelka B. Kovačević +8

Here we present results from our spectroscopic follow-up of SDSS J2320+0024, a candidate binary supermassive black hole (SMBH) with a suspected sub-pc separation, identified by a 2…

astro-ph.IM2021★ 30 cited

Improving the reliability of photometric redshift with machine learning

Oleksandra Razim, Stefano Cavuoti, Massimo Brescia +3

In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of g…

astro-ph.IM2021★ 28 cited

Photometric redshifts with machine learning, lights and shadows on a complex data science use case

Massimo Brescia, Stefano Cavuoti, Oleksandra Razim +3

The current role of data-driven science is constantly increasing its importance within Astrophysics, due to the huge amount of multi-wavelength data collected every day, characteri…