arXiv subjects

T. Mkrtchyan

Publications and source records attributed to T. Mkrtchyan.

4 recordsLinked to original sources

arXiv2026

Photometric redshifts for active galactic nuclei with LePHARE for the Vera C. Rubin Observatory

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 depend on their means of selection. Upcoming large-scale surveys such as LSST will identify many AGN, but analysis tools are not optimized for them. The limited number of photometric bands in these surveys impacts the calculation of photometric redshifts for AGN, which are essential for scientific advancement. We use LePHARE to demonstrate the impact that a limited number of bands and erroneous assumptions have on the determination of the photometric redshifts of AGN. We conduct tests on six AGN samples selected using X-ray, radio, infrared, variability, color, and spectroscopic criteria in the COSMOS field, using photometry from HSC-CLAUDS, which is closest in depth and wavelength coverage to LSST. We present the LSST pipeline for LePHARE within the Redshift Assessment Infrastructure Layers (RAIL), facilitating comparison between SED fitting and machine learning algorithms. AGN that appear as point-like sources in optical data will be assigned highly unreliable photometric redshifts if they are processed using galaxy templates. Additionally, shallow all-sky surveys (like eROSITA, WISE, and ZTF) miss many AGN. As a result, these "hidden" AGN are often misidentified as galaxies in public survey data, leading to incorrect photometric redshift. We provide the configurations that are suggested for each type of AGN alongside measures of expected performance as a function of redshift, magnitude, and selection. To facilitate studies with a panchromatic view of AGN, we also release photometric redshifts and posterior distributions for all AGN sources identified in the COSMOS field using the six criteria, based on 28-band photometry.

astro-ph.GA↗

arXiv2026

VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features

Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral energy distribution (SED) fitting suffers from color-redshift degeneracies, particularly for AGNs whose power-law continua hide the strong spectral features required to anchor redshift estimates. While AGN variability provides additional constraining power, existing frameworks require multi-band light curves that are not always available. This work presents VAR-PZnn, a fully connected mixture density network that integrates 26 variability features extracted from ZTF g-band light curves with optical photometry from Pan-STARRS1, mid-infrared (MIR) photometry from CatWISE, and, for a subsample, NIR photometry from UKIDSS. The model is trained and tested on 72,728 spectroscopically confirmed AGNs/QSOs spanning 0.01 < z < 4.5 and g-band magnitudes from 17 to 21.5. For the main sample, we achieve \sigma_{NMAD} = 0.058 and an outlier fraction of \eta = 8.2%, which reduces to 5.4% when the 10% of sources with the highest predicted uncertainty are excluded. An ablation study demonstrates that MIR photometry provides the dominant constraint for photo-z accuracy, while variability features serve as a secondary refiner. Using UKIDSS NIR data as a proxy for future synergies between LSST and space-based missions like Euclid and Roman, we obtain \eta = 13.3% without MIR data and \eta = 4.6% when MIR is available. We benchmark against Low-Resolution Templates (LRT) SED fitting (\eta = 28.7%) and the VAR-PZ framework; applying single-band VAR-PZ priors worsens LRT performance to \eta = 39.4% due to single-band light-curve degeneracies, confirmed via simulations (\eta = 27.6% to 28.1%). This framework provides a scalable approach for the Legacy Survey of Space and Time (LSST).

astro-ph.GA↗

arXiv2026

4MOST ChANGES: Catalog of high-redshift quasar candidates (4.5 < $z$ < 7) selected with SED fitting

The identification of high-redshift quasars ($z > 4.5$) is critical for studying the early Universe, supermassive black hole growth, and cosmic reionization. Most known high-redshift quasars are located in the northern hemisphere, leaving the southern sky largely unexplored. As part of the 4-meter Multi-Object Spectroscopic Telescope (4MOST) and Chilean AGN/Galaxy Extragalactic Survey (ChANGES) S1604 survey, we aim to create a large catalog of high-redshift quasar candidates in the southern hemisphere using multiwavelength photometry and Spectral Energy Distribution (SED) fitting, with the goal of spectroscopic follow-up with 4MOST. We construct a multi-band photometric catalog by combining optical data from DELVE DR2 and DECaLS DR10, near-infrared data from VHS DR5 with an additional field of VIKING, mid-infrared data from AllWISE, and optical astrometry from Gaia DR3. After applying morphological and color-based cuts, we perform SED fitting using quasar and brown dwarf templates. Statistical outputs, including $\chi^2$, BIC, and F-test are used to rank and select candidates. Our final catalog contains 6104 high-redshift quasar candidates within $4.5 < z < 7$, with detections in 7 or more photometric bands satisfying our SED-based selection criteria (BIC > 0 and F-test > 10). Spectroscopic validation using NTT/EFOSC2 and Palomar/NGPS confirmed 3 high-redshift quasars at $z > 5$ out of 6 observed candidates.

astro-ph.GA↗

arXiv2025

VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability

The Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/optical/NIR monitoring of a significant fraction of these objects. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshifts estimates which are traditionally much less reliable for AGN than for inactive galaxies. This work presents a novel methodology to constrain the photometric redshift of AGNs that leverages the effects of cosmological time dilation, and of the luminosity and wavelength dependence of AGN variability. Specifically, we assume that the variability can be modeled as a damped random walk (DRW) process, and adopt a parametric model to characterize the DRW timescale ($\tau$) and asymptotic amplitude of the variability (SF$_\infty$) based on the redshift, the rest-frame wavelength, and the AGN luminosity. We construct variability-based photo-$z$ priors by modeling the observed variability using the expected DRW parameters at a given redshift. These variability-based photometric redshift (VAR-PZ) priors are then combined with traditional SED fitting to improve the redshift estimates from SED fitting. Validation is performed using observational data from the SDSS, demonstrating significant reduction in catastrophic outliers by more than 10% in comparison with SED fitting techniques and improvements in redshift precision. The simulated light curves with both SDSS and LSST-like cadences and baselines confirm that, VAR-PZ will be able to constrain the photometric redshifts of SDSS-like AGNs by bringing the outlier fractions down to below 7% from 32% (SED-alone) at the end of the survey.

astro-ph.GA↗