arXiv subjects

A. M. Muñoz Arancibia

Publications and source records attributed to A. M. Muñoz Arancibia.

14 recordsLinked to original sources

arXiv2026

Simultaneous radio, optical and X-ray monitoring of hard X-ray selected AGN: a variability study

AGN emission is intrinsically variable across the electromagnetic spectrum. Mapping the coupling between the accretion disk, the X-ray corona, and ejection flows is key to understanding the energy flow within the central engine. We characterize the multi-wavelength variability of 14 hard X-ray selected AGN from the INTEGRAL/IBIS catalog in the radio, optical, and X-ray bands, to determine the coupling between these frequencies and how variability relates to the physical properties of the central engine, with emphasis on the radio band. We analyzed multi-epoch observations from AMI-LA at 15 GHz, ZTF in the g and r bands, and Swift/XRT over 2018--2020. Variability was quantified using the normalized excess variance, the fractional variability amplitude, and the Mexican Hat filter at 70- and 200-day timescales. We also characterized the radio-loudness of the sample and evaluated the impact of variability on the Fundamental Plane of black hole activity by comparing time-averaged with strictly simultaneous data. Significant variability is detected in 86% of the sample, with a clear amplitude stratification: the fractional rms amplitude is highest in X-rays, with a median of 30% (11-67%), followed by the optical g and r bands at 19% (2-33%) and 8.5% (0.2-24%), and the radio band at 10% (4-23%). The Mexican Hat analysis reveals a red-noise power spectrum dominated by long-term fluctuations. The sample follows the expected Fundamental Plane scaling; although individual sources shift within the relation due to stochastic fluctuations, this dispersion accounts for only ~3% of the total scatter. Our findings support a core-dominated origin for the 15 GHz emission, likely a compact jet base or a magnetized corona, while differences in variability patterns, radio-loudness, and Fundamental Plane location point toward distinct accretion/ejection processes and degrees of corona-jet coupling.

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arXiv2025

Tuning into spatial frequency space: Satellite and space debris detection in the ZTF alert stream

A significant challenge in the study of transient astrophysical phenomena is the identification of bogus events, among which human-made satellites and debris in Earth orbit remain major contaminants. Existing pipelines effectively identify satellite trails but can miss more complex signatures, such as collections of satellite glints. In the Rubin Observatory era, the scale of operations will increase tenfold compared to its precursor, the Zwicky Transient Facility (ZTF), requiring improvements in classification purity, data compression for informative alerts, and pipeline speed. We explore the use of the 2D Fast Fourier Transform (FFT) on difference images as a tool to enhance machine learning models for satellite detection. Using the ALeRCE single-stamp classifier as a baseline, we adapt its architecture to incorporate a cutout of the FFT of the difference image alongside the standard ZTF image triplet (science, reference, and difference stamps). We evaluate several stamp sizes and resolutions, focusing on regimes where data compression is critical due to alert size limits and real-time constraints. Incorporating the FFT significantly improves satellite classification, especially in the smallest field-of-view model (16 arcsec), where accuracy increases from 72.0\pm2.9% to 87.8\pm1.3%. This demonstrates the FFT's value in compressing and capturing extended satellite features. However, the FFT alone does not match the full-context performance of the 63 arcsec (95.9\pm1.3%) or multiscale (90.6\pm0.8%) models, highlighting the complementary role of spatial context. We show how FFTs can be leveraged to cull satellite and debris signatures from alert streams in current and future time-domain surveys.

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arXiv2024

A Novel Optimal Transport-Based Approach for Interpolating Spectral Time Series: Paving the Way for Photometric Classification of Supernovae

This paper introduces a novel method for creating spectral time series, which can be used for generating synthetic light curves for photometric classification but also for applications like K-corrections and bolometric corrections. This approach is particularly valuable in the era of large astronomical surveys, where it can significantly enhance the analysis and understanding of an increasing number of SNe, even in the absence of extensive spectroscopic data. methods: By employing interpolations based on optimal transport theory, starting from a spectroscopic sequence, we derive weighted average spectra with high cadence. The weights incorporate an uncertainty factor for penalizing interpolations between spectra that show significant epoch differences and lead to a poor match between the synthetic and observed photometry. results: Our analysis reveals that even with phase difference of up to 40 days between pairs of spectra, optical transport can generate interpolated spectral time series that closely resemble the original ones. Synthetic photometry extracted from these spectral time series aligns well with observed photometry. The best results are achieved in the V band, with relative residuals of less than 10% for 87% and 84% of the data for type Ia and II, respectively. For the B, g, R and r bands, the relative residuals are between 65% and 87% within the previously mentioned 10% threshold for both classes. The worse results correspond to the i and I bands where, in the case, of SN~Ia the values drop to 53% and 42%, respectively. conclusions: We introduce a new method for constructing spectral time series for individual SNe starting from a sparse spectroscopic sequence, and demonstrate its capability to produce reliable light curves that can be used for photometric classification.

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arXiv2024

SDSS1335+0728: The awakening of a $\sim 10^6 M_{\odot}$ black hole

The galaxy SDSS1335+0728, which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). Its behaviour suggests that SDSS1335+0728 hosts a $\sim 10^6 M_{\odot}$ black hole (BH) that is currently in the process of `turning on'. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. We used archival photometry and spectroscopic data to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift, SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We find that: (a) since 2021, the UV flux is four times brighter than the flux reported by GALEX in 2004; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1-W2 WISE colour has become redder; (c) since February 2024, the source has begun showing X-ray emission; (d) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (e) broad emission lines are not detected; and (f) the [OIII] line increased its flux $\sim 3.6$ years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. We conclude that the variations observed in SDSS1335+0728 could be either explained by an AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGN observed in the process of activating. If the latter, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour.

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arXiv2024

Physical Properties of Type II Supernovae Inferred from ZTF and ATLAS Photometric Data

We report an analysis of a sample of 186 spectroscopically confirmed Type II supernova (SN) light curves (LCs) obtained from a combination of Zwicky Transient Facility (ZTF) and Asteroid Terrestrial-impact Last Alert System (ATLAS) observations. We implement a method to infer physical parameters from these LCs using hydrodynamic models that take into account the progenitor mass, the explosion energy, and the presence of circumstellar matter (CSM). The CSM is modelled via the mass loss rate, wind acceleration at the surface of the progenitor star with a $β$ velocity law, and the CSM radius. We also infer the time of explosion, attenuation (A$_V$), and the redshift for each SN. Our results favor low-mass progenitor stars (M$_{ZAMS}$\,$<$14\,$M_\odot$) with a dense CSM ($\dot{M}$ $>$ 10$^{-3}$ [M$_\odot$ yr$^{-1}$], a CSM radius of $\sim$ 10$^{15}$ cm, and $β$ $>$ 2). Additionally, we find that the redshift inferred from the supernova LCs is significantly more accurate than that inferred using the host galaxy photometric redshift, suggesting that this method could be used to infer more accurate host galaxy redshifts from large samples of SNe II in the LSST era. Lastly, we compare our results with similar works from the literature.

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arXiv2024

ATAT: Astronomical Transformer for time series And Tabular data

The advent of next-generation survey instruments, such as the Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST), is opening a window for new research in time-domain astronomy. The Extended LSST Astronomical Time-Series Classification Challenge (ELAsTiCC) was created to test the capacity of brokers to deal with a simulated LSST stream. We describe ATAT, the Astronomical Transformer for time series And Tabular data, a classification model conceived by the ALeRCE alert broker to classify light-curves from next-generation alert streams. ATAT was tested in production during the first round of the ELAsTiCC campaigns. ATAT consists of two Transformer models that encode light curves and features using novel time modulation and quantile feature tokenizer mechanisms, respectively. ATAT was trained on different combinations of light curves, metadata, and features calculated over the light curves. We compare ATAT against the current ALeRCE classifier, a Balanced Hierarchical Random Forest (BHRF) trained on human-engineered features derived from light curves and metadata. When trained on light curves and metadata, ATAT achieves a macro F1-score of 82.9 +- 0.4 in 20 classes, outperforming the BHRF model trained on 429 features, which achieves a macro F1-score of 79.4 +- 0.1. The use of Transformer multimodal architectures, combining light curves and tabular data, opens new possibilities for classifying alerts from a new generation of large etendue telescopes, such as the Vera C. Rubin Observatory, in real-world brokering scenarios.

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arXiv2023

The ALMA Frontier Fields Survey. VI. Lensing-corrected 1.1mm number counts in Abell 2744, MACSJ0416.1-2403, MACSJ1149.5+2223, Abell 370 and Abell S1063

[abridged] Probing the faint end of the number counts at mm wavelengths is important to identify the origin of the extragalactic background light in this regime. Aided by strong gravitational lensing, ALMA observations towards massive galaxy clusters have opened a window to disentangle this origin, allowing to resolve sub-mJy dusty star-forming galaxies. We aim to derive number counts at 1.1 mm down to flux densities fainter than 0.1 mJy, based on ALMA observations towards five Hubble Frontier Fields (FF) galaxy clusters, following a statistical approach to correct for lensing effects. We created a source catalog that includes 29 ALMA 1.1 mm continuum detections down to a 4.5sigma significance. We derived source intrinsic flux densities using public lensing models. We folded the uncertainties in both magnifications and source redshifts into the number counts through Monte Carlo simulations. We derive cumulative number counts over two orders of magnitude down to 0.01 mJy after correction for lensing effects. Cosmic variance estimates are all exceeded by uncertainties in our median combined cumulative counts that come from both our Monte Carlo simulations and Poisson statistics. Our number counts are consistent to 1sigma with most of recent ALMA estimates and galaxy evolution models. However, below 0.1 mJy, they are lower by 0.4 dex compared to two deep ALMA studies but consistent with ASPECS-LP to 1sigma. Importantly, the flattening found for our cumulative counts extends further to 0.01 mJy. Our results bring further support in line of the flattening of the number counts reported previously by us and ASPECS-LP, which has been interpreted by a recent galaxy evolution model as a measurement of the "knee" of the infrared luminosity function at high redshift. Our estimates of the contribution to the EBL in the FFs suggest that we may be resolving most of the EBL at 1.1mm down to 0.01 mJy.

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arXiv2023

Persistent and occasional: searching for the variable population of the ZTF/4MOST sky using ZTF data release 11

We present a variability, color and morphology based classifier, designed to identify transients, persistently variable, and non-variable sources, from the Zwicky Transient Facility (ZTF) Data Release 11 (DR11) light curves of extended and point sources. The main motivation to develop this model was to identify active galactic nuclei (AGN) at different redshift ranges to be observed by the 4MOST ChANGES project. Still, it serves as a more general time-domain astronomy study. The model uses nine colors computed from CatWISE and PS1, a morphology score from PS1, and 61 single-band variability features computed from the ZTF DR11 g and r light curves. We trained two versions of the model, one for each ZTF band. We used a hierarchical local classifier per parent node approach, where each node was composed of a balanced random forest model. We adopted a 17-class taxonomy, including non-variable stars and galaxies, three transient classes, five classes of stochastic variables, and seven classes of periodic variables. The macro averaged precision, recall and F1-score are 0.61, 0.75, and 0.62 for the g-band model, and 0.60, 0.74, and 0.61, for the r-band model. When grouping the four AGN classes into one single class, its precision, recall, and F1-score are 1.00, 0.95, and 0.97, respectively, for both the g and r bands. We applied the model to all the sources in the ZTF/4MOST overlapping sky, avoiding ZTF fields covering the Galactic bulge, including 86,576,577 light curves in the g-band and 140,409,824 in the r-band. Only 0.73\% of the g-band light curves and 2.62\% of the r-band light curves were classified as stochastic, periodic, or transient with high probability ($P_{init}\geq0.9$). We found that, in general, more reliable results are obtained when using the g-band model. Using the latter, we identified 384,242 AGN candidates, 287,156 of which have $P_{init}\geq0.9$.

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arXiv2023

Multiwavelength monitoring of the nucleus in PBC J2333.9-2343: the giant radio galaxy with a blazar-like core

PBC J2333.9-2343 is a giant radio galaxy at z = 0.047 with a bright central core associated to a blazar nucleus. If the nuclear blazar jet is a new phase of the jet activity, then the small orientation angle suggest a dramatic change of the jet direction. We present observations obtained between September 2018 and January 2019 (cadence larger than three days) with Effeslberg, SMARTS-1.3m, ZTF, ATLAS, Swift, and Fermi-LAT, and between April-July 2019 (daily cadence) with SMARTS-1.3m and ATLAS. Large (>2x) flux increases are observed on timescales shorter than a month, which are interpreted as flaring events. The cross correlation between the SMARTS-1.3m monitoring in the NIR and optical shows that these data do not show significant time lag within the measured errors. A comparison of the optical variability properties between non-blazars and blazars AGN shows that PBC J2333.9-2343 has properties more comparable to the latter. The SED of the nucleus shows two peaks, that were fitted with a one zone leptonic model. Our data and modelling shows that the high energy peak is dominated by External Compton from the dusty torus with mild contribution from Inverse Compton from the jet. The derived jet angle of 3 degrees is also typical of a blazar. Therefore, we confirm the presence of a blazar-like core in the center of this giant radio galaxy, likely a Flat Spectrum Radio Quasar with peculiar properties.

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arXiv2021

Searching for changing-state AGNs in massive datasets -- I: applying deep learning and anomaly detection techniques to find AGNs with anomalous variability behaviours

The classic classification scheme for Active Galactic Nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs (CSAGNs). The physical mechanism behind this phenomenon is still a matter of open debate and the samples are too small and of serendipitous nature to provide robust answers. In order to tackle this problem, we need to design methods that are able to detect AGN right in the act of changing-state. Here we present an anomaly detection (AD) technique designed to identify AGN light curves with anomalous behaviors in massive datasets. The main aim of this technique is to identify CSAGN at different stages of the transition, but it can also be used for more general purposes, such as cleaning massive datasets for AGN variability analyses. We used light curves from the Zwicky Transient Facility data release 5 (ZTF DR5), containing a sample of 230,451 AGNs of different classes. The ZTF DR5 light curves were modeled with a Variational Recurrent Autoencoder (VRAE) architecture, that allowed us to obtain a set of attributes from the VRAE latent space that describes the general behaviour of our sample. These attributes were then used as features for an Isolation Forest (IF) algorithm, that is an anomaly detector for a "one class" kind of problem. We used the VRAE reconstruction errors and the IF anomaly score to select a sample of 8,809 anomalies. These anomalies are dominated by bogus candidates, but we were able to identify 75 promising CSAGN candidates.

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arXiv2018

The ALMA Frontier Fields Survey - IV. Lensing-corrected 1.1 mm number counts in Abell 2744, MACSJ0416.1-2403 and MACSJ1149.5+2223

[abridged] Characterizing the number counts of faint, dusty star-forming galaxies is currently a challenge even for deep, high-resolution observations in the FIR-to-mm regime. They are predicted to account for approximately half of the total extragalactic background light at those wavelengths. Searching for dusty star-forming galaxies behind massive galaxy clusters benefits from strong lensing, enhancing their measured emission while increasing spatial resolution. Derived number counts depend, however, on mass reconstruction models that properly constrain these clusters. We estimate the 1.1 mm number counts along the line of sight of three galaxy clusters, i.e. Abell 2744, MACSJ0416.1-2403 and MACSJ1149.5+2223, which are part of the ALMA Frontier Fields Survey. We perform detailed simulations to correct these counts for lensing effects. We use several publicly available lensing models for the galaxy clusters to derive the intrinsic flux densities of our sources. We perform Monte Carlo simulations of the number counts for a detailed treatment of the uncertainties in the magnifications and adopted source redshifts. We find an overall agreement among the number counts derived for the different lens models, despite their systematic variations regarding source magnifications and effective areas. Our number counts span ~2.5 dex in demagnified flux density, from several mJy down to tens of uJy. Our number counts are consistent with recent estimates from deep ALMA observations at a 3$σ$ level. Below $\approx$ 0.1 mJy, however, our cumulative counts are lower by $\approx$ 1 dex, suggesting a flattening in the number counts. In our deepest ALMA mosaic, we estimate number counts for intrinsic flux densities $\approx$ 4 times fainter than the rms level. This highlights the potential of probing the sub-10 uJy population in larger samples of galaxy cluster fields with deeper ALMA observations.

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arXiv2017

The ALMA Frontier Fields Survey III: 1.1 mm Emission Line Identifications in Abell 2744, MACSJ0416.1-2403, MACSJ1149.5+2223, Abell 370, and Abell S1063

Most sub-mm emission line studies of galaxies to date have targeted sources with known redshifts where the frequencies of the lines are well constrained. Recent blind line scans circumvent the spectroscopic redshift requirement, which could represent a selection bias. Our aim is to detect emission lines present in continuum oriented observations. The detection of such lines provides spectroscopic redshift and yields properties of the galaxies. We perform a search for emission lines in the ALMA observations of five Frontier Fields clusters and assess the reliability of our detection by associating line candidates with detected galaxies in deep near-infrared imaging. We find 26 significant emission lines candidates, with observed line fluxes between 0.2-4.6 Jy km s$^{-1}$ and velocity dispersions (FWHM) of 25-600 km s$^{-1}$. Nine of these candidates lie nearby to near-infrared sources, boosting their reliability; in six cases the observed line frequency and strength are consistent with expectations given the photometric redshift and properties of the galaxy counterparts. We present redshift identifications, magnifications and molecular gas estimates for the galaxies with identified lines. We show that two of these candidates likely originate from starburst galaxies, one of which is a jellyfish galaxy, while another two are consistent with being main sequence galaxies based in their depletion times. This work highlights the degree to which serendipitous emission lines can be discovered in large mosaic continuum observations when deep ancillary data are available. The low number of high-significance line detections, however, confirms that such surveys are not as optimal as blind line scans. We stress that Monte Carlo simulations should be used to assess the line detections significances, since using the negative noise suffers from stochasticity and incurs larger uncertainties.

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arXiv2016

The ALMA Frontier Fields survey I: 1.1 mm continuum detections in Abell 2744, MACSJ0416.1-2403 and MACSJ1149.5+2223

Dusty star-forming galaxies are among the most prodigious systems at high redshift (z>1), characterized by high star formation rates and huge dust reservoirs. The bright end of this population has been well characterized in recent years, but considerable uncertainties remain for fainter dusty star-forming galaxies, which are responsible for the bulk of star formation at high redshift and thus play a key role in galaxy growth and evolution. In this first paper of our series, we describe our methods for finding high redshift faint dusty galaxies using millimeter observations with ALMA. We obtained ALMA 1.1 mm mosaic images for three strong-lensing galaxy clusters from the Frontier Fields survey. The 2'x2' mosaics overlap with the deep HST WFC3/IR footprints and encompass the high magnification regions of each cluster. The combination of extremely high ALMA sensitivity and the magnification power of these clusters allows us to systematically probe the sub-mJy population of dusty star-forming galaxies over a large surveyed area. We present a description of the reduction and analysis of the ALMA continuum observations for the galaxy clusters Abell 2744 (z=0.308), MACSJ0416.1-2403 (z=0.396) and MACSJ1149.5+2223 (z=0.543), for which we reach observed rms sensitivities of 55, 59 and 71 $μ$Jy beam$^{-1}$ respectively. We detect 12 dusty star-forming galaxies at S/N>5.0 across the three clusters, all of them presenting coincidence with NIR detected counterparts in the HST images. None of the sources fall close to the lensing caustics, thus they are not strongly lensed. The observed 1.1 mm flux densities for the total sample of galaxies range from 0.41 to 2.82 mJy, with observed effective radii spanning <0.05" to 0.37"$\pm$0.21". The lensing-corrected sizes of the detected sources appear to be in the same range as those measured in brighter samples, albeit with possibly larger dispersion.

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arXiv2014

Chemo-Archaeological Downsizing in a Hierarchical Universe: Impact of a Top Heavy IGIMF

We make use of a semi-analytical model of galaxy formation to investigate the origin of the observed correlation between [a/Fe] abundance ratios and stellar mass in elliptical galaxies. We implement a new galaxy-wide stellar initial mass function (Top Heavy Integrated Galaxy Initial Mass Function, TH-IGIMF) in the semi-analytic model SAG and evaluate its impact on the chemical evolution of galaxies. The SFR-dependence of the slope of the TH-IGIMF is found to be key to reproducing the correct [a/Fe]-stellar mass relation. Massive galaxies reach higher [a/Fe] abundance ratios because they are characterized by more top-heavy IMFs as a result of their higher SFR. As a consequence of our analysis, the value of the minimum embedded star cluster mass and of the slope of the embedded cluster mass function, which are free parameters involved in the TH-IGIMF theory, are found to be as low as 5 solar masses and 2, respectively. A mild downsizing trend is present for galaxies generated assuming either a universal IMF or a variable TH-IGIMF. We find that, regardless of galaxy mass, older galaxies (with formation redshifts > 2) are formed in shorter time-scales (< 2 Gyr), thus achieving larger [a/Fe] values. Hence, the time-scale of galaxy formation alone cannot explain the slope of the [a/Fe]-galaxy mass relation, but is responsible for the big dispersion of [a/Fe] abundance ratios at fixed stellar mass.We further test the hyphothesis of a TH-IGIMF in elliptical galaxies by looking into mass-to-light ratios, and luminosity functions. Models with a TH-IGIMF are also favoured by these constraints. In particular, mass-to-light ratios agree with observed values for massive galaxies while being overpredicted for less massive ones; this overprediction is present regardless of the IMF considered.

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