arXiv subjects

Paula Sánchez-Sáez

Publications and source records attributed to Paula Sánchez-Sáez.

At least 19 recordsLinked to original sources

arXiv2026

The Intermediate-Mass Black Hole Reverberation Mapping Project: Scientific Overview and Sample Characteristics

Recent discoveries with the James Webb Space Telescope of massive black holes at high redshift have highlighted fundamental questions about black hole seed formation and the coevolution of black holes with their host galaxies. Because the initial seed population cannot yet be observed directly, nearby intermediate-mass black holes provide a complementary fossil record of black hole formation and early growth. Motivated by this opportunity, we present the Intermediate-Mass Black Hole Reverberation Mapping (IMBH-RM) project and construct a homogeneous Sloan Digital Sky Survey sample of active broad-line IMBHs by uniformly reanalyzing literature candidates with consistent spectral decomposition and black hole mass estimation. Our sample contains 192 reliable IMBH candidates at $z\lesssim0.3$ with $\log(M_{\rm BH}/M_\odot)<6$, including four particularly compelling sources with $\log(M_{\rm BH}/M_\odot)<5$. The primary goal of IMBH-RM is to obtain reliable black hole masses from direct measurements and characteristic sizes of the broad-line region and accretion disk for a carefully selected subsample. These measurements will provide robust low-mass anchors for calibrating single-epoch black hole mass estimates and extending black hole--galaxy scaling relations into the IMBH regime. By building a statistically meaningful reverberation-mapped sample spanning $10^4-10^6\,M_\odot$, we aim to constrain the local IMBH mass distribution and place observational constraints on competing black hole seed formation scenarios. The future Multi-Channel Imager aboard the Chinese Space-station Survey Telescope provides a particularly promising platform for achieving these goals.

astro-ph.GA↗

arXiv2026

AGNFormer I: Reconstruction of AGN spectra using a probabilistic transformer model

We explore how an uncertainty-aware transformer-based architecture can leverage information embedded across the entire observed optical spectra of AGN, focusing on the algorithm's ability to predict unseen or masked parts of luminous AGN spectra. This provides a direct probe of the learnable correlations between AGN continua and broad lines. We introduce AGNFormer, a transformer model trained to predict the mean expected flux and variance in masked spectral regions (major broad lines to ${\pm}10^{4}$kms$^{-1}$; missing halves), inputting rest-frame spectral fluxes and uncertainties across the entire redshift range of the SDSS DR16 Quasar Catalogue. We evaluate the performance of the model on both full (no S/N limit) and high-quality (S/N > 10) spectral samples using the negative-log likelihood, and via comparisons with existing C IV and ly-a reconstruction algorithms. The model successfully reconstructs unseen AGN broad lines to better than 10-16% (4-8%) of the flux for the full (S/N > 10) test sets, up to an error floor of $\approx$2-6% of the flux at S/N $\approx$ 40, while predictions for larger unseen halves grow to 12-25% (5-15%) of the flux the further away they are from the cut-off wavelength of the seen input spectrum. Predictions faithfully reproduce the broad AGN spectral diversity across the entire optical and UV QSO main sequence parameter spaces, including both Gaussian and Lorentzian profile regimes, Feii complexes, and narrow emission lines. Performance is similar or better compared to previous spectral reconstruction algorithms. The high precision of the broad-line region reconstruction demonstrates that the method successfully aggregates information across the spectrum and highlights how the AGN continuum and weaker lines/complexes have the potential to assist astronomers in the extraction of the entire wealth of information embedded in AGN spectra.

astro-ph.GA↗

arXiv2026

Fast and Flexible Characterisation of Astronomical Light Curves Using Multi-Time Attention

We present an unsupervised, data-driven framework for rapid characterisation of astronomical photometric time series using a Multi-Time Attention Network. The model learns time-aware latent representations directly from irregular, partial light curves without heavy preprocessing. Through application on ZTF alert data retrieved with Fink, a community alert broker for Rubin LSST, we demonstrate that the model: (i) produces accurate interpolations with small bias (0.01 mag) and scatter (0.1 mag) even for sparse light curves, (ii) learns a temporally distributed latent space correlating with physically meaningful properties (duration, peak time, variability, color) while being robust to unimportant properties such as observed magnitude and number of observations, (iii) separates general SN and AGN samples despite data being heavily dominated by AGNs, and (iv) generalises to unseen classes: The long-period variable and TDE show good interpolation and sensible latent space placement; however, the model cannot capture RRLyrae's $\sim$0.4-0.5 day pulsation period, which is far below our model's chosen two-day temporal resolution. Attention map analysis reveals the capability of multi-time attention to capture local structure. The model is extremely lightweight (a few hundred kilobytes) and has fast inference ($\sim$0.01 and $\sim$$3\times10^{-4}$ s per light curve on CPU and GPU, respectively) that is independent of the number of observations, unlike GP regression. Our approach offers flexible and scalable characterisation, with high relevance in the Rubin LSST era. We discuss future possibilities to incorporate observational uncertainties and symmetries for robustness and forecasting applications for real-time follow-up.

astro-ph.IM↗

arXiv2026

Evidence for a Delayed UV Counterpart to X-ray Quasi-periodic Eruptions in Ansky

X-ray quasi-periodic eruptions (QPEs) represent a novel population of extreme, repeating nuclear transients whose physical origins remain debated. A defining characteristic of QPEs has been their exclusive detection in the X-ray band, with a notable absence of correlated multi-wavelength counterparts. Here we report the first detection of a recurrent UV response temporally coupled to the X-ray QPE signal in the source Ansky/ZTF19acnskyy. The UV emission displays coherent periodic modulations over five consecutive cycles, systematically lagging the X-ray eruptions by $0.96^{+0.38}_{-0.39}$ days, with a cross-correlation coefficient of $r_{\rm max} \sim 0.6$. We suggest that the detectability of this corresponding signal may be enabled by Ansky's unusually long recurrence timescale, which could reduce the temporal smearing of the UV response seen in more rapid QPEs. The observed delay may correspond to a diffusion timescale associated with heated blobs. However, we cannot exclude the possibility that the lag corresponds to the light-crossing time associated with X-ray irradiation that originates near the central black hole and propagates to the outer UV-emitting region. While numerous QPE models have been proposed, any viable model for Ansky must be able to simultaneously explain the presence of a UV counterpart, its measured time lag, and the previously observed steadily increasing recurrence period.

astro-ph.HE↗

arXiv2026

A positive period derivative in the quasi-periodic eruptions of ZTF19acnskyy

We report the first direct measurement of the period derivative in a quasi-periodic eruption (QPE), finding a smoothly increasing period with $\dot{P}\approx (1.7\pm 0.02)\times10^{-2}$ d d$^{-1}$ in the source ZTF19acnskyy/"Ansky". Most models for QPEs invoke repeated interactions of a stellar-mass orbiting companion around the supermassive black hole (SMBH) in an extreme mass-ratio inspiral (EMRI). In these scenarios, a positive $\dot{P}$ is surprising, but not impossible to produce. We explore several possible explanations for the observed $\dot{P}$, including stable mass-transfer driven by impulsive mass loss events in an EMRI, velocity kicks at pericenter due to tidal interactions with the SMBH, apparent period changes due either to general relativistic precession effects in an EMRI or light travel-time delays in a hierarchical SMBH binary, and mass-transfer variations in a thermal/viscous disk instability model. We find that none of the considered models provides a complete explanation for the data, motivating further work on physical explanations for positive period derivatives in QPEs.

astro-ph.HE↗

arXiv2026

Scavenger hunt: Selection of obscured active galactic nuclei combining multiband optical variability and colors

As wide-field optical surveys such as Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) begin operations, time-domain astronomy is facing a data revolution, paving the road for new, expanded variability studies. This work leverages the complementary power of optical variability and color selection to identify active galactic nuclei (AGN), focusing on optimizing the identification of obscured AGN, typically more challenging to distinguish from inactive galaxies based on optical variability alone. The analysis is designed to provide valuable insights in the context of performance preview for the LSST, albeit using a scaled-down version of the LSST dataset. We present the first combined AGN selection based on g+r+i band light curves from the VST-COSMOS survey, spanning 3.3 yr. We identify AGN candidates independently in each band using a random forest (RF) classifier trained on features mainly related to optical variability, along with six optical/infrared colors and a morphology indicator. We subsequently merge the three band-specific samples in order to enhance selection purity and reliability. We then focus on defining a subset of features that significantly improve the identification of obscured AGN. The RF classifiers yield a consistent performance across the three bands, highlighting the critical role of contamination. Using the combined three-band plus color selection we successfully recover $58^{+9}_{-8}\%$ of all AGN and $69^{+10}_{-8}\%$ of the known obscured AGN that have been independently confirmed in all three bands. When requiring confirmation in two out of the three bands, these fractions increase to $69^{+10}_{-8}\%$ and $80^{+10}_{-9}\%$, respectively. We also demonstrate that, while combining variability features with colors is crucial to improve obscured AGN selection, relying solely on color features returns a markedly higher contamination rate.

astro-ph.GA↗

arXiv2026

Discovery of crested quasi-periodic eruptions following the most luminous SRG/eROSITA tidal disruption event

We report the discovery of complex flaring activity from the galactic nucleus hosting the five-year-old tidal disruption event eRASSt J234402.9-352640 (J2344). With Einstein Probe and XMM-Newton observations, we detected highly structured soft X-ray variability. Through temporal decomposition of the XMM-Newton light curve and time-resolved spectral analysis, we identified broad, thermal flares recurring every $\sim$12 hours and lasting $\sim$2 hours, consistent with quasi-periodic eruptions (QPEs). Remarkably, these QPEs are accompanied by an unprecedented crest of hotter, shorter flares, each lasting between 5 and 30 minutes. These flares are predominantly found in the rising phases of the QPEs, although they also appear throughout the quiescence. These findings establish J2344 as a new member of the QPE emitter population and uncover a previously unobserved phenomenology that challenges current models of QPEs. In this letter, we present the phenomenological properties of this unique source and discuss possible interpretations within the framework of extreme-mass-ratio inspirals.

astro-ph.HE↗

arXiv2025

The evolution of obscured AGN across cosmic time -- A large quasar survey for the 2040s

We propose a large quasar demographic optical multi-object spectroscopic (MOS) survey targeting over 50 million AGN candidates up to the highest redshifts possible in the optical (z~6.5), with repeat visits, using a variety of selection criteria available by 2040. A large MOS survey combining all AGN selection methods is the only way to unify a diverse range of different obscured AGN populations within a single, variability- and spectroscopy-based framework, rather than as disjoint classes selected by different methods.

astro-ph.GA↗

arXiv2025

Scalable and Robust Multiband Modeling of AGN Light Curves in Rubin-LSST

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will monitor tens of millions of active galactic nuclei (AGNs) for a period of 10 years with an average cadence of 3 days in six broad photometric bands. This unprecedented dataset will enable robust characterizations of AGN UV/optical variability across a wide range of AGN physical properties. However, existing tools for modeling AGN light curves are not yet capable of fully leveraging the volume, cadence, and multiband nature of LSST data. We present EzTaoX, a scalable light curve modeling tool designed to take advantage of LSST's multiband observations to simultaneously characterize AGN UV/optical stochastic variability and measure interband time delays. EzTaoX achieves a speed increase of $\sim 10^2-10^4 \times$ on CPUs over current tools with similar capabilities, while maintaining equal or better accuracy in recovering simulated variability properties. This performance gain enables continuum time-delay measurements for all AGNs discovered by LSST -- both in the Wide Fast Deep survey and the Deep Drilling Fields -- thereby opening new opportunities to probe AGN accretion-flow geometries. In addition, EzTaoX's multiband capability allows robust characterization of AGN stochastic variability down to hourly timescales, facilitating the identification of accreting low-mass AGNs -- such as those residing in dwarf galaxies -- through their distinctive variability signatures.

astro-ph.GA↗

arXiv2025

The Intermediate-Mass Black Hole Reverberation Mapping Project: First Detection of Mid-Infrared Lags in Prototypical IMBHs in NGC 4395 and POX 52

The search for robust evidence of intermediate-mass black holes (IMBHs) is crucial for understanding black hole seeding process and the formation of supermassive black holes in the early Universe. NGC 4395 and POX 52 are two prototypical IMBH hosts, both exhibiting multi-line evidence of low-mass black hole activity. Here, we report the first detection of mid-infrared (MIR) lags in response to optical variability, with measurements of $3.0^{+2.4}_{-1.9}$ days for NGC 4395 and $35.2^{+14.2}_{-11.7}$ days for POX~52 at $3.4$ $μ$m, respectively, using archival optical data and observations from the Wide-field Infrared Survey Explorer (WISE). This detection provides the first reverberation evidence of low-mass black hole activity in POX 52. The time lags of these two low-mass, low-luminosity active galactic nuclei (AGNs) generally follow the extent of the $R_{\rm dust}-L_{\rm 5100}$ relation found in higher-mass AGNs. Based on an empirical relation between the broad-line region and dusty torus size, we constrain the black hole mass of POX 52 to log($M_{\rm BH}$/$M_\odot$) = 5.5 $\pm$ 0.37 (systemic and statistical errors), confirming its IMBH nature. Furthermore, long-term optical continuum monitoring of POX 52 reveals a mild inter-band lag of $\lesssim$ 1 day. However, no significant intranight variability was detected during its one-night, high-cadence monitoring, which we attribute to the longer duty cycle of fast variability in POX 52 compared to that in NGC 4395.

astro-ph.GA↗

arXiv2025

A new Bowen Fluorescence Flare and Extreme Coronal Line Emitter discovered by SRG/eROSITA

The nuclear transient eRASSt J012026.5-292727 (J012026 hereafter) was discovered in the second SRG/eROSITA all-sky survey (eRASS2). The source appeared more than one order of magnitude brighter than the eRASS1 upper limits (peak eRASS2 0.2-2.3 keV flux of 1.14 x 10^-12 erg cm^-2 s^-1), and with a soft X-ray spectrum (photon index Gamma = 4.3). Over the following months, the X-ray flux started decaying, with significant flaring activity on both hour- and year-timescales. By inspecting the multiwavelength light curves of time-domain wide-field facilities, we detected a strong mid-infrared flare, evolving over 2 years, and a weaker optical counterpart. Follow-up optical spectroscopy revealed transient features, including redshifted Balmer lines (FWHM ~1500 km/s), strong Fe II emission, He II and Bowen lines, and high-ionization iron coronal lines. One spectrum showed a triple-peaked H-beta line, consistent with emission from a face-on elliptical disk. The spectroscopic features and the slow evolution of the event place J012026 within the classifications of Bowen fluorescence flares (BFFs) and extreme coronal line emitters (ECLEs). BFFs have been associated with rejuvenated accreting SMBHs, although the mechanism triggering the onset of the new accretion flow is still unclear, while ECLEs have been linked to the disruption of stars in gas-rich environments. The association of J012026 to both classes, combined with the multi-wavelength information, suggests that BFFs could be, at least in some cases, due to tidal disruption events (TDEs). The observed X-ray variability, uncommon in standard TDEs, adds complexity to these families of nuclear transients. These results highlight the diverse phenomenology of nuclear accretion events and demonstrate the value of systematic X-ray surveys, such as eROSITA and Einstein Probe, for uncovering such transients and characterizing their physical origin.

astro-ph.HE↗

arXiv2025

Navigating AGN variability with self-organizing maps

Context. The classification of active galactic nuclei (AGNs) is a challenge in astrophysics. Variability features extracted from light curves offer a promising avenue for distinguishing AGNs and their subclasses. This approach would be very valuable in sight of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Aims. Our goal is to utilize self-organizing maps (SOMs) to classify AGNs based on variability features and investigate how the use of different subsets of features impacts the purity and completeness of the resulting classifications. Methods. We derived a set of variability features from light curves, similar to those employed in previous studies, and applied SOMs to explore the distribution of AGNs subclasses. We conducted a comparative analysis of the classifications obtained with different subsets of features, focusing on the ability to identify different AGNs types. Results. Our analysis demonstrates that using SOMs with variability features yields a relatively pure AGNs sample, though completeness remains a challenge. In particular, Type 2 AGNs are the hardest to identify, as can be expected. These results represent a promising step toward the development of tools that may support AGNs selection in future large-scale surveys such as LSST.

astro-ph.IM↗

arXiv2025

Selection of optically variable active galactic nuclei via a random forest algorithm

Context. A defining characteristic of active galactic nuclei (AGN) that distinguishes them from other astronomical sources is their stochastic variability, which is observable across the entire electromagnetic spectrum. Upcoming optical wide-field surveys, such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time, are set to transform astronomy by delivering unprecedented volumes of data for time domain studies. This data influx will require the development of the expertise and methodologies necessary to manage and analyze it effectively. Aims. This project focuses on optimizing AGN selection through optical variability in wide-field surveys and aims to reduce the bias against obscured AGN. We tested a random forest (RF) algorithm trained on various feature sets to select AGN. The initial dataset consisted of 54 observations in the r-band and 25 in the g-band of the COSMOS field, captured with the VLT Survey Telescope over a 3.3-year baseline. Methods. Our analysis relies on feature sets derived separately from either band plus a set of features combining data from both bands, mostly characterizing AGN on the basis of their variability properties and obtained from their light curves. We trained multiple RF classifiers using different subsets of selected features and assessed their performance via targeted metrics. Results. Our tests provide valuable insights into the use of multiband and multivisit data for AGN identification. We compared our findings with previous studies and dedicated part of the analysis to potential enhancements in selecting obscured AGN. The expertise gained and the methodologies developed here are readily applicable to datasets from other ground- and space-based missions.

astro-ph.GA↗

arXiv2025

Discovery of Quasi-periodic Eruptions in the Tidal Disruption Event and Extreme Coronal Line Emitter AT2022upj: implications for the QPE/TDE fraction and a connection to ECLEs

Quasi-periodic eruptions (QPEs) are recurring soft X-ray transients emerging from the vicinity of supermassive black holes (SMBHs) in nearby, low-mass galaxy nuclei; about ten QPE hosts have been identified thus far. Here we report the \textit{NICER} discovery of QPEs in the optically-selected Tidal Disruption Event (TDE) and Extreme Coronal Line Emitter (ECLE) AT2022upj, exhibiting a large spread in recurrence times from 0.5-3.5 days, durations from 0.3-1 days, peak luminosities from $10^{42.5-43.0}$ erg s$^{-1}$, and erratic flare profiles. A wealth of evidence now links at least some QPEs to the newly-formed accretion flows emerging from TDEs; AT2022upj is the third QPE reported in an optically discovered TDE. Marginalizing over the uncertain distributions of QPE peak luminosity, recurrence time, delay after TDE peak, and lifetime, we use the burgeoning sample to make a Bayesian estimate that the fraction of optical TDEs resulting in QPEs within 5 years post-disruption is $9^{+9}_{-5}$\%. Along with AT2019qiz, AT2022upj also marks the second of the three optical TDE+X-ray QPEs showing coronal line emission, suggesting ECLEs may represent a subset of TDEs particularly efficient at forming QPEs and/or that sustained QPE X-ray emission contributes to coronal line emission in some galaxy nuclei.

astro-ph.HE↗

arXiv2025

Rapidly varying ionization features in a Quasi-periodic Eruption: a homologous expansion model for the spectroscopic evolution

Quasi-Periodic Eruptions (QPEs) are recurring bursts of soft X-ray emission from supermassive black holes (SMBHs), which a growing class of models explains via extreme mass-ratio inspirals (EMRIs). QPEs exhibit blackbody-like emission with significant temperature evolution, but the minimal information content of their almost pure-thermal spectra has limited physical constraints. Here we study the recently discovered QPEs in ZTF19acnskyy (``Ansky''), which show absorption-like features evolving dramatically within eruptions and correlating strongly with continuum temperature and luminosity, further probing the conditions underlying the emission surface. The absorption features are well-described by dense ionized plasma of column density $N_{\rm H}\gtrsim 10^{21}$ cm$^{-2}$, blueshift $0.06\lesssim v/c \lesssim 0.4$, and either collisional or photoionization equilibrium. With high-resolution spectra, we also detect ionized blueshifted emission lines suggesting a nitrogen over-abundance of $21.7^{+18.5}_{-11.0}\times$ solar. We interpret our results with orbiter-disk collisions in an EMRI system, in which each impact drives a shock that locally heats the disk and expels X-ray emitting debris undergoing radiation pressure-driven homologous expansion. We explore an analytical toy model that links the rapid change in absorption lines to the evolution of the ionization parameter and the photosphere radius, and suggest that $\sim 10^{-3}M_\odot$ ejected per eruption with expansion velocities up to $v_{\rm max}\sim 0.15c$, can reproduce the absorption features. With these assumptions, we show a P Cygni profile in a spherical expansion geometry qualitatively matches the observed line profiles. Our work takes a first step towards extending existing physical models for QPEs to address their implications for spectral line formation.

astro-ph.HE↗

arXiv2025

Discovery of extreme Quasi-Periodic Eruptions in a newly accreting massive black hole

Quasi-periodic eruptions (QPEs) are rapid, recurring X-ray bursts from supermassive black holes, believed to result from interactions between accretion disks and surrounding matter. The galaxy SDSS1335+0728, previously stable for two decades, exhibited an increase in optical brightness in December 2019, followed by persistent Active Galactic Nucleus (AGN)-like variability for 5 years, suggesting the activation of a $\sim$10$^6\;M_\odot$ black hole. From February 2024, X-ray emission has been detected, revealing extreme $\sim$4.5-day QPEs with the highest fluxes and amplitudes, longest time scales, largest integrated energies, and a $\sim$25-day super-period. Low-significance UV variations are reported for the first time in a QPE host, likely related to the long timescales and large radii from which the emission originates. This discovery broadens the possible formation channels for QPEs, suggesting they are not linked solely to tidal disruption events but more generally to newly formed accretion flows, which we are witnessing in real time in a turn-on AGN candidate.

astro-ph.HE↗

arXiv2023

Optical variability in Quasars: Scaling with black hole mass and Eddington ratio depend on the observed timescales

Quasars emission is highly variable, and this variability gives us clues to understand the accretion process onto supermassive black holes. We can expect variability properties to correlate with the main physical properties of the accreting black hole, i.e., its mass and accretion rate. It has been established that the relative amplitude of variability anti-correlates with the accretion rate.The dependence of the variance on black hole mass has remained elusive, and contradicting results, including positive, negative, or no correlation, have been reported. In this work, we show that the key to these contradictions lies in the timescales of variability studied (e.g., the length of the light curves available). By isolating the variance on different timescales as well as mass and accretion rate bins we show that there is indeed a negative correlation between black hole mass and variance and that this anti-correlation is stronger for shorter timescale fluctuations. The behavior can be explained in terms of a universal variability power spectrum for all quasars, resembling a broken power law where the variance is constant at low temporal frequencies and then drops continuously for frequencies higher than a characteristic frequency $f_b$, where $f_b$ correlates with the black hole mass. Furthermore, to explain all the variance results presented here, not only the normalization of this power spectrum must anti-correlate with the accretion rate, but also the shape of the power spectra at short timescales must depend on this parameter as well.

astro-ph.GA↗

arXiv2023

Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier Categories

With the increasing volume of astronomical data generated by modern survey telescopes, automated pipelines and machine learning techniques have become crucial for analyzing and extracting knowledge from these datasets. Anomaly detection, i.e. the task of identifying irregular or unexpected patterns in the data, is a complex challenge in astronomy. In this paper, we propose Multi-Class Deep Support Vector Data Description (MCDSVDD), an extension of the state-of-the-art anomaly detection algorithm One-Class Deep SVDD, specifically designed to handle different inlier categories with distinct data distributions. MCDSVDD uses a neural network to map the data into hyperspheres, where each hypersphere represents a specific inlier category. The distance of each sample from the centers of these hyperspheres determines the anomaly score. We evaluate the effectiveness of MCDSVDD by comparing its performance with several anomaly detection algorithms on a large dataset of astronomical light-curves obtained from the Zwicky Transient Facility. Our results demonstrate the efficacy of MCDSVDD in detecting anomalous sources while leveraging the presence of different inlier categories. The code and the data needed to reproduce our results are publicly available at https://github.com/mperezcarrasco/AnomalyALeRCE.

cs.LG↗