arXiv subjects

Elias Kyritsis

Publications and source records attributed to Elias Kyritsis.

6 recordsLinked to original sources

arXiv2026

Low-hard to high-soft spectral state transitions in the faintest early-X-ray-detected optical tidal disruption event TDE 2025aarm

We report the X-ray and optical spectroscopic properties of TDE 2025aarm, the second closest tidal disruption event (TDE) discovered to date. The proximity of this source, combined with a deep and intense X-ray monitoring campaign spanning six months, allowed us to probe the source down to an unprecedented 0.2-10 keV luminosity of $\sim7\times10^{39}$ erg s$^{-1}$ close to the optical peak. This renders TDE 2025aarm the faintest early-X-ray-detected TDE to date. After the first X-ray detection, the source brightened by nearly two orders of magnitude, reaching a peak luminosity of $\sim5\times10^{41}$ erg s$^{-1}$ about four months after the optical peak. Through time-resolved X-ray spectral analysis, we find that TDE 2025aarm evolved from an initially hard, power-law-dominated X-ray state into a softer, disk-dominated state as the luminosity increased, before hardening again at later times. Such low-hard-to-high-soft state transitions are commonly observed in black hole X-ray binaries (XRBs) but have not previously been reported in thermal TDEs. We show that the spectral evolution can be described by variations in the relative contributions of an accretion disk and a Comptonizing component, qualitatively resembling the disk--corona evolution observed in XRBs. We also present the results of our optical spectroscopic follow-up campaign with HET/LRS2, confirming the TDE classification and revealing NIII Bowen fluorescence features. The extremely faint early-time X-ray emission of TDE 2025aarm further supports the idea that the historical dichotomy between X-ray-bright and X-ray-undetected TDEs is largely driven by selection effects related to the depth, cadence, and duration of X-ray follow-up observations. TDE 2025aarm therefore provides new insight into both the accretion physics of TDEs and the possible universality of accretion across several orders of magnitude in black hole mass.

astro-ph.HE↗

arXiv2026

Spectroscopic redshifts of selected flat-spectrum radio sources I

We present the first results of a spectroscopic campaign carried out as part of the Search for Milli-Lenses (SMILE) program, which aims to constrain the prevalence of gravitational lens systems on milli-arcsecond angular scales (milli-lenses) using high-resolution Very Long Baseline Interferometry (VLBI) imaging. The SMILE parent sample contains ~ 5000 radio-loud active galaxies, selected as a flux-limited, complete subsample of CLASS (The Cosmic Lens All-Sky Survey) sources. We compiled redshift information for the full sample from multiple literature and catalog sources and found that 491 sources have no available redshift estimate, either spectroscopic or photometric. A further 948 sources have only photometric redshifts, many of which show substantial discrepancies between catalogs. Reliable redshifts are essential for VLBI radio-source studies because they convert angular measurements into physical linear scales, enable estimates of intrinsic luminosities and jet kinematics, and allow robust cosmological and population studies. To address this key limitation for lensing and population studies, we initiated a dedicated spectroscopic campaign to secure reliable redshifts for as many targets as possible. This paper focuses on the brightest sources in the SMILE sample. We report newly determined spectroscopic redshifts for 6 targets out of 15 observed with the Skinakas 1.3 m telescope.

astro-ph.CO↗

arXiv2026

Prescriptions for the stochasticity effect on the integrated X-ray luminosity of star-forming galaxies:Implications for selecting star-forming galaxies and AGN in X-ray surveys

(abridged) The integrated X-ray luminosity (Lx) of star-forming galaxies is dominated by high-mass X-ray binary (HMXB) populations. The discrete nature of these populations introduces stochastic sampling effects that distort the X-ray Luminosity Function (XLF) and bias observed scaling relations. We investigate how stochastic sampling of the HMXB XLF affects the predicted integrated Lx across a wide range of star-formation and metallicity conditions, quantifying the scatter to provide a statistical framework for interpreting X-ray observations. Using Monte Carlo simulations, we derive Lx distributions over a broad grid of star-formation rate (SFR) and metallicity values. By measuring statistical quantities describing these distributions, we parametrize the luminosity scatter by fitting surfaces to the upper and lower Lx bounds as functions of SFR and metallicity. We provide practical prescriptions to compute the expected Lx for given SFR and metallicity, fully accounting for stochastic effects without rerunning costly XLF sampling. Applying these to local and high-redshift samples shows stochasticity must be considered before attributing Lx differences to intrinsic properties. A simulation study across z=0.5-5 reveals mild redshift evolution of stochastic scatter, with minimum scatter at z~2.5. Our prescriptions quantify biases in scaling relations introduced by flux-limited surveys. At low redshifts, stochastic effects can raise Lx by up to 1 dex, overlapping with the low-luminosity AGN regime and biasing source classification in deep surveys. These prescriptions offer a framework for constraining scatter, quantifying extreme outliers, and refining X-ray source classification in current and future surveys.

astro-ph.GA↗

arXiv2023

A versatile classification tool for galactic activity using optical and infrared colors

(abridged) The overwhelming majority of diagnostic tools for galactic activity are focused on active galaxies. Passive or dormant galaxies are often excluded from these diagnostics which usually employ emission line features. In this work, we use infrared and optical colors in order to build an all-inclusive galactic activity diagnostic tool that can discriminate between star-forming, AGN, LINER, composite, and passive galaxies, and which can be used in local and low-redshift galaxies. We explore classification criteria based on infrared colors from the 3 WISE bands supplemented with optical colors from the u, g, and r SDSS bands. From these we aim to find the minimal combination of colors for optimal results. Furthermore, to mitigate biases related to aperture effects, we introduce a new WISE photometric scheme combing different sized apertures. We develop a diagnostic tool using machine learning methods that includes both active and passive galaxies under one unified scheme using 3 colors. We find that the combination of W1-W2, W2-W3, and g-r colors offers good performance while the broad availability of these colors for a large number of galaxies ensures wide applicability on large galaxy samples. The overall accuracy is $\sim$81% while the achieved completeness for each class is $\sim$81% for star-forming, $\sim$56% for AGN, $\sim$68% for LINER, $\sim$65% for composite, and $\sim$85% for passive galaxies. Our diagnostic provides a significant improvement over existing IR diagnostics by including all types of active, as well as passive galaxies, and extending them to the local Universe. The inclusion of the optical colors improves their performance in identifying low-luminosity AGN which are generally confused with star-forming galaxies, and helps to identify cases of starbursts with extreme mid-IR colors which mimic obscured AGN galaxies, a well-known problem for most IR diagnostics.

astro-ph.GA↗

arXiv2023

A versatile classification tool for galactic activity using optical and infrared colors

We use the Random Forest (RF) algorithm to develop a tool for automated activity classification of galaxies into 5 different classes: Star-forming (SF), AGN, LINER, Composite, and Passive. We train the algorithm on a combination of mid-IR (WISE) and optical photometric data while the true labels (activity classes) are based on emission line ratios. Our classifier is built to be redshift-agnostic and it is applicable to objects up to z $\sim$0.1. It reaches a completeness $>$80 % for SF and Passive galaxies, and $\sim$60 % for AGN. Applying it to an all-sky galaxy catalog (HECATE) reveals a large population of low-luminosity AGNs outside the AGN locus in the standard mid-IR diagnostics.

astro-ph.GA↗

arXiv2023

Star-formation rate and stellar mass calibrations based on infrared photometry and their dependence on stellar population age and extinction

The stellar mass ($M_\star$) and the star-formation rate (SFR) are among the most important features that characterize galaxies. Measuring these fundamental properties accurately is critical for understanding the present state of galaxies, and their history. This work explores the dependence of the IR emission of galaxies on their extinction, and the age of their stellar populations (SPs). It aims at providing accurate IR SFR and $M_\star$ calibrations that account for SP age and extinction while quantifying their scatter. We use the CIGALE spectral energy distribution (SED) fitting code to create models of galaxies with a wide range of star-formation histories, dust content, and interstellar medium properties. We fit the relations between $M_\star$ and SFR with IR and optical photometry of the model-galaxy SEDs with the MCMC method, and perform a machine-learning random forest analysis on the same data set in order to validate the latter. This work provides calibrations for the SFR using a combination of the WISE bands 1 and 3, or the JWST F200W and F2100W bands. It also provides mass-to-light ratio calibrations based on the WISE band-1, or the JWST band F200W, along with the optical $u-r$ or $g-r$ colors. These calibrations account for the biases attributed to the SP age, while they are given in the form of extinction-dependent and extinction-independent relations. They show robust estimations while minimizing the scatter and biases throughout a wide range of SFRs and stellar masses. The SFR calibration offers better results, especially in dust-free or passive galaxies where the contributions of old SPs or biases from the lack of dust are significant. Similarly, the $M_\star$ calibration yields significantly better results for dusty/high-SFR galaxies where dust emission can otherwise bias the estimations.

astro-ph.GA↗