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Agnieszka Pollo

Publications and source records attributed to Agnieszka Pollo.

At least 19 recordsLinked to original sources

Extending the Little Red Dot population at intermediate redshift with VIPERS

Little red dots (LRDs) are a recently identified population of compact, red sources characterised by a distinctive V-shaped UV-to-optical continuum and broad emission lines. Their physical structure and evolution remain uncertain, while their properties at intermediate redshifts are largely unexplored. We identify and characterise LRD-like sources at 0.5 0.5, bridging local and high-redshift studies. Their abundance, compact morphology, environmental properties, and multi-wavelength emission provide new constraints on the evolution and physical origin of this population.

astro-ph.GA

Rubin J122659.4+090236: An Extremely Low Surface Brightness Galaxy Candidate Discovered in the Rubin LSST Early Data Preview 2

We report the serendipitous discovery of an exceptionally low surface brightness galaxy (LSBG) candidate, Rubin J122659.4+090236, in Rubin Observatory imaging of the interacting NGC 4410 system, identified in the Cosmic Treasure Chest public release. 2D Sérsic modelling of the Rubin g, r, and i images reveals a nearly round system with a shallow profile (n ~ 0.4), an effective radius of R_e ~ 6'', and central surface brightnesses of $μ_{0,g}=27.52\pm0.04$, $μ_{0,r}=27.62\pm0.07$, and $μ_{0,i}=27.04\pm0.08$ mag arcsec$^{-2}$. EAZY photo-z fitting favours an intermediate-z solution at z~0.3, while a low-redshift solution at z~0.028, consistent with the NGC 4410 system, is also permitted by a restricted EAZY fit over 0<z<0.1 without imposing a redshift prior. These alternatives imply substantially different physical interpretations, ranging from a diffuse dwarf-like system to an exceptionally extended background LSBG. This discovery demonstrates Rubin's sensitivity to extremely diffuse galaxies and highlights the potential of the LSST survey to uncover large samples of such elusive systems across wide areas, enabling systematic studies of the LSBG population and its role in galaxy evolution.

astro-ph.GA

CORN -- Chronometers of Relic Nature I: The first estimate of the expansion rate of the Universe using compact relic galaxies

Measuring the expansion rate of the Universe is a central challenge in cosmology. Independent and robust methods are essential to validate existing measurements and assess potential systematic effects. We employ the cosmic chronometer (CC) approach, which uses the differential age evolution of quiescent galaxies to measure the Hubble parameter H(z) without assuming an underlying cosmological model. In contrast to previous CC studies, we restrict our analysis to relics -- ultra compact massive galaxies (UCMGs) hosting the oldest stellar populations -- thereby minimising uncertainties related to star formation history and merger history. We select a sample of 189 relic galaxies in the redshift range 0.07< z <0.22 from the E-INSPIRE UCMGs catalogue. Using the D_n4000 spectral index of relic galaxies and its redshift evolution, combined with MILES stellar population synthesis models, we derive the differential age relation required to infer H(z). We account not only for metallicity effects but also for the impact of alpha-element enhancement, which has not been explicitly propagated into the systematic uncertainty budget of the D_n4000 cosmic chronometer method. We obtain an independent measurement of H(z=0.15) = 85\pm53 km/s/Mpc. The total uncertainty is dominated by statistical limitations. The systematic component is 13% (8.7% when alpha-enrichment is not propagated), among the tightest estimates in current CC studies. We find that alpha-enrichment plays a major role in the systematic error budget, particularly in the high metallicity regime, and must be properly accounted for in future analyses. We demonstrate the proof of concept that relic galaxies provide a promising pathway to reduce systematic uncertainties in the CC method. The statistical uncertainties, which dominate the error budget, can be significantly reduced by the increase of data volume expected during the next years.

astro-ph.CO

From DES to KiDS: Domain adaptation for cross-survey detection of low-surface-brightness galaxies

Low-surface-brightness galaxies (LSBGs) are vital for understanding galaxy formation, but their diffuse nature makes them challenging to detect. Upcoming large-scale surveys are expected to uncover large numbers of LSBGs, requiring robust automated methods to identify them across heterogeneous datasets. As a precursor to the Legacy Survey of Space and Time (LSST) and Euclid, we explore domain adaptation techniques for cross-survey LSBG identification. Using models trained on the Dark Energy Survey (DES), we search for LSBGs in the Kilo-Degree Survey Data Release 5 (KiDS DR5). We used an ensemble consisting of one convolutional neural network (CNN) and two transformer models trained on DES cutouts and applied to KiDS DR5 imaging data. Structural parameters were estimated with galfitm, and photometric redshifts and stellar population properties were estimated through spectral energy distribution fitting with CIGALE. We identify 20,180 LSBGs and 434 ultra-diffuse galaxies (UDGs) in KiDS DR5. Their structural parameters are similar to known LSBGs from DES and the Hyper Suprime-Cam SSP Survey (HSC-SSP). The KiDS-LSBGs follow a continuous size-luminosity relation connecting classical dwarf galaxies and UDGs, and their colours are bimodal ($\sim73\%$ blue, $\sim27\%$ red). Cross-matching with spectroscopic and cluster catalogues provides redshifts for 4,913 systems, enabling a systematic characterisation of the star-forming main sequence of LSBGs. Strong environmental trends are evident, with cluster LSBGs and UDGs exhibiting redder colours and reduced star formation compared to non-cluster systems. We demonstrate that domain adaptation enables robust cross-survey LSBG identification with deep learning models, providing a scalable pathway for constructing homogeneous LSBG catalogues for the LSST and Euclid era.

astro-ph.GA

Design and preliminary performance study of the broad-band spectrometer detector for POLAR-2

POLAR-2, the successor of the POLAR experiment aboard China's Tiangong-2 space lab, is set to be deployed on the China Space Station. The POLAR-2 mission aims to conducting high-precision polarization measurements of high-energy transients with a primary focus on Gamma-Ray Bursts (GRBs), following POLAR's pioneering accurate polarization measurements of GRB prompt emission. One of the key advancements in POLAR-2 is the inclusion of a dedicated Broad-band Spectrometer Detector (BSD) instrument, designed to provide precise measurements of GRB location and spectral parameters, which are critical inputs for accurate polarization analysis of POLAR-2's dedicated High-energy Polarimetry Detector (HPD), which is made of plastic scintillator bars array. BSD employs a coded-aperture mask imaging technique and pixelated GAGG scintillation crystals, offering a wide half-coded field of view of ~132° x 125° and an operational energy range of 10-1000 keV. Simulation results indicate that the instrument can achieve a localization accuracy of approximately 1.5° for faint GRBs similar to GRB 170817A, satisfying the core requirements of GRB polarimetry with HPD. BSD also has moderate capability for GRB polarimetry, particularly at several hundred keV energy. This paper outlines the preliminary design of BSD and presents an overall evaluation of its expected scientific performance, based on extensive Monte Carlo simulations and preliminary ground-based calibration tests.

astro-ph.IM

The optical-infrared relation for active galactic nuclei: The role of contaminations

The main objective is to calibrate the OPT-IR luminosity relation for quasars, focusing on accurate estimations of dusty torus and accretion disk luminosities. We analyzed contaminations related to host galaxies, particularly from polar dust, the interstellar medium, and stellar emission that affect the optical and infrared. We used a sample of nearly 400 quasars with photometrical observations and spectroscopical redshift divided into four redshift bins (0.7-2.4). Full spectral energy distribution (SED) fitting was performed with the CIGALE code, and results were compared with simplified photometric luminosity estimates. The impact of non-active galactic nucleus components and the role of polar dust in the fitting process were assessed. We show that for sources with a disk luminosity above 10^45 [erg/s], the photometric estimates are consistent with SED-based values. While polar dust contributes marginally to luminosity, its presence significantly alters SED fitting, particularly the torus opening angle and cold dust properties. In the optical domain, stellar emission is the dominant contamination. In the infrared, disk emission and cold dust play major roles. We propose two empirical calibrations for the OPT-IR relation. We conclude that the optical band is dominated by the accretion disk component above 10^45 or 10^46 [erg/s] depending on redshift, while IR luminosity is dominated by the dusty torus emission above 1.6 $\times$ 10^45 or 2 $\times$ 10^46 [erg/s] depending on the redshift. In this high-luminosity regime, simplified photometric methods yield reliable disk and torus luminosity estimates. The aim of the analysis we present is to test the parameter space in order to build a well behaving OPT-IR nonlinear luminosity relation for quasars that could serve as a cosmological probe.

astro-ph.GA

Redshift Classification of Optical Gamma-Ray Bursts using Supervised Learning

Gamma-ray bursts (GRBs) are among the most luminous explosions in the Universe and serve as powerful probes of the early cosmos. However, the rapid fading of their afterglows and the scarcity of spectroscopic measurements make photometric classification crucial for timely high-redshift identification. We present an ensemble machine learning framework for redshift classification of GRBs based solely on their optical plateau and prompt emission properties. Our dataset comprises 171 long GRBs observed by the Swift UVOT and more than 450 ground-based telescopes. The analysis pipeline integrates robust statistical techniques, including M-estimator outlier rejection, multivariate imputation using Multiple Imputation by Chained Equations, and Least Absolute Shrinkage and Selection Operator feature selection, followed by a SuperLearner ensemble combining parametric, semi-parametric, and non-parametric algorithms. The optimal model, trained on raw optical data with outlier removal at a redshift threshold of z equals 2.0, achieves a true positive rate of 74 percent and an area under the curve of 0.84, maintaining balanced generalization between training and test sets. At higher thresholds, such as z equals 3.0, the classifier sustains strong discriminative power with an area under the curve of 0.88. Validation on an independent GRB sample yields 97 percent overall accuracy, perfect specificity, and an ensemble area under the curve of 0.93. Compared to previous prompt- and X-ray-based classifiers, our optical framework offers enhanced sensitivity to high-redshift events, improved robustness against data incompleteness, and greater applicability to ground-based follow-up. We also publicly release a web application that enables real-time redshift classification, facilitating rapid identification of candidate high-redshift GRBs for cosmological studies.

astro-ph.HE

Why the Northern Hemisphere Needs a 30-40 m Telescope and the Science at Stake: A Low Surface Brightness Science Case

The Extragalactic Low Surface Brightness (LSB, $μ_V\gtrsim 27$ mag/arcsec$^2$) Universe represents a crucial, yet largely unseen, frontier in modern astrophysics. This faint realm holds the keys to completing our understanding of galaxy evolution, hierarchical assembly, and even the fundamental nature of dark matter. Our current theoretical models are inherently incomplete, largely mirroring the properties of the brightest, most easily observed objects. To overcome this critical bias and unlock the secrets of this realm, a transformative leap in observational capability is required. A 30 to 40m class telescope, leveraging unprecedented sensitivity and spatial resolution, especially with adaptive optics, is the essential tool to fundamentally probe these faint, low-density stellar regimes. This white paper details the transformative LSB science that such a facility, strategically positioned in the Northern Hemisphere (NH) to access crucial nearby structures and rich environments, can achieve.

astro-ph.IM

POLAR-2 -- Latest Developments of the Next Generation GRB Polarimeter

Gamma-Ray Bursts (GRBs) are among the most energetic events in the Universe. Despite over 50 years of research and measurements their prompt emission remains poorly understood, with key questions surrounding the structure of relativistic jets, magnetic field configurations, and dominant radiation mechanisms. Polarization measurements are critical in resolving these uncertainties. The POLAR mission, operational in 2016-2017 on Tiangong-2, provided the most statistically significant GRB polarization data. Its results indicated low time-averaged polarization with hints of temporal evolution. However, POLAR's limited sensitivity, small effective area, and restricted energy range prevented more detailed time- and energy-resolved analyses in addition to a larger sample of GRB polarization measurements. POLAR-2 is designed to address these limitations by offering a fourfold increase in effective area (at least) and an extended energy range of 30-800 keV by utilizing Silicon Photomultipliers (SiPMs) and an updated module design, enabling the differentiation of competing GRB emission models. The instrument comprises of 100 polarimeter modules (each with 64 plastic scintillator bars), wherein the polarization angle is extracted through Compton Scattering of the gammas. The polarimeter module design was validated during an ESRF beam test campaign in 2023. The instrument was developed by a joint effort of Switzerland, China, Poland and Germany and is planned for launch in 2027. Currently, POLAR-2 is in its production phase with the first module targets being produced. We will provide an overview of the current status of the development.

astro-ph.IM

Environmental dependence of galaxy properties in the southern GAMA regions

Using data from the Galaxy and Mass Assembly (GAMA) survey, we investigate how galaxy properties correlate with the local environment, focusing on the two southern regions of the survey (G02 and G23) that have not previously been examined in this context. We employ two-point and marked correlation functions to quantify the environmental dependence of galaxy color, stellar mass, luminosity across the $u$, $g$, $r$, $J$, and $K$ bands, as well as star formation rate (SFR) and specific star formation rate (sSFR). We also assess the impact of redshift incompleteness and cosmic variance on these clustering measurements. Our results show that $u-r$ and $g-r$ colors are most strongly correlated with local overdensity, followed by stellar mass. The sSFR exhibits a clear inverse relationship with density of the environment, consistent with the trend observed for $u$-band luminosity, which traces young stellar populations. In contrast, galaxies brighter in the $g$, $J$, and $K$ bands preferentially inhabit denser regions. By comparing our measurements from the southern regions with those from the equatorial regions of GAMA, we find that cosmic variance does not significantly influence our conclusions. However, redshift incompleteness affects the clustering measurements, as revealed through comparisons of subsets within the G02 region. The measured correlations provide key constraints for models of galaxy assembly across mass and environment, while the environmental trends in color and near-infrared luminosity offer a means to trace stellar mass growth and quenching with redshift.

astro-ph.GA

Gamma-Ray Burst Polarimetry with the POLAR and POLAR-2 missions

Gamma-Ray Bursts are among the most powerful and violent events in the Universe. Despite over half a century of observations of these transient sources, many open questions remain about their nature and the physical emission mechanisms at play. Polarization measurements of the GRB prompt gamma-ray emission have long been theorized to be able to answer most of these questions. Early polarization measurements did not allow to draw clear conclusions because of limited significance. With the aim of better characterizing the polarization of these prompt emissions, a compact Gamma-Ray polarimeter called POLAR has been sent to space as part of the Tiangong-2 Chinese space lab for 6 months of operations starting September 2016. The instrument detected 55 GRBs as well as several pulsars. Time-integrated polarization analysis of the 14 brightest detected GRBs has shown that the prompt emission is lowly polarized or fully unpolarized. However, time-resolved analysis depicted strong hints of an evolving polarization angle within single pulses, washing out the polarization degree in time-integrated analyses. Energy-resolved polarization analysis has shown no constraining results due to limited statistics. Hence, a more sensitive $γ$-ray polarimeter is required to perform detailed energy and time-resolved polarization analysis of the prompt gamma-ray emission of GRBs. Based on the success of the POLAR mission, a larger-scale instrument, approved for launch to the China Space Station (CSS) in 2027, is currently being developed by a Swiss, Chinese, Polish, and German collaboration. Thanks to its large sensitivity in the 20-800~keV range, POLAR-2 will produce polarization measurements of at least 50 GRBs per year with a precision equal to or higher than the best results published by POLAR, allowing for good quality time and energy resolved analysis.

astro-ph.HE

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. [Abridged]

astro-ph.CO

Automated quasar continuum estimation using neural networks: a comparative study of deep-learning architectures

Context. Ongoing and upcoming large spectroscopic surveys are drastically increasing the number of observed quasar spectra, requiring the development of fast and accurate automated methods to estimate spectral continua. Aims. This study evaluates the performance of three neural networks (NN) - an autoencoder, a convolutional NN (CNN), and a U-Net - in predicting quasar continua within the rest-frame wavelength range of $1020~\textÅ$ to $2000~\textÅ$. The ability to generalize and predict galaxy continua within the range of $3500~\textÅ$ to $5500~\textÅ$ is also tested. Methods. The performance of these architectures is evaluated using the absolute fractional flux error (AFFE) on a library of mock quasar spectra for the WEAVE survey, and on real data from the Early Data Release observations of the Dark Energy Spectroscopic Instrument (DESI) and the VIMOS Public Extragalactic Redshift Survey (VIPERS). Results. The autoencoder outperforms the U-Net, achieving a median AFFE of 0.009 for quasars. The best model also effectively recovers the Ly$α$ optical depth evolution in DESI quasar spectra. With minimal optimization, the same architectures can be generalized to the galaxy case, with the autoencoder reaching a median AFFE of 0.014 and reproducing the D4000n break in DESI and VIPERS galaxies.

astro-ph.GA

Gamma-ray Bursts as Distance Indicators by a Statistical Learning Approach

Gamma-ray bursts (GRBs) can be probes of the early universe, but currently, only 26% of GRBs observed by the Neil Gehrels Swift Observatory GRBs have known redshifts ($z$) due to observational limitations. To address this, we estimated the GRB redshift (distance) via a supervised statistical learning model that uses optical afterglow observed by Swift and ground-based telescopes. The inferred redshifts are strongly correlated (a Pearson coefficient of 0.93) with the observed redshifts, thus proving the reliability of this method. The inferred and observed redshifts allow us to estimate the number of GRBs occurring at a given redshift (GRB rate) to be 8.47-9 $yr^{-1} Gpc^{-1}$ for $1.9<z<2.3$. Since GRBs come from the collapse of massive stars, we compared this rate with the star formation rate highlighting a discrepancy of a factor of 3 at $z<1$.

astro-ph.HE

GRB Redshift Estimation using Machine Learning and the Associated Web-App

Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as currently, only 12% of GRBs have known redshifts due to observational biases. Aims. We aim to address the shortage of GRBs with measured redshifts, enabling us to fully realize their potential as valuable cosmological probes Methods. Following Dainotti et al. (2024c), we have taken a second step to overcome this issue by adding 30 more GRBs to our ensemble supervised machine learning training sample, an increase of 20%, which will help us obtain better redshift estimates. In addition, we have built a freely accessible and user-friendly web app that infers the redshift of long GRBs (LGRBs) with plateau emission using our machine learning model. The web app is the first of its kind for such a study and will allow the community to obtain redshift estimates by entering the GRB parameters in the app. Results. Through our machine learning model, we have successfully estimated redshifts for 276 LGRBs using X-ray afterglow parameters detected by the Neil Gehrels Swift Observatory and increased the sample of LGRBs with known redshifts by 110%. We also perform Monte Carlo simulations to demonstrate the future applicability of this research. Conclusions. The results presented in this research will enable the community to increase the sample of GRBs with known redshift estimates. This can help address many outstanding issues, such as GRB formation rate, luminosity function, and the true nature of low-luminosity GRBs, and enable the application of GRBs as standard candles

astro-ph.HE

The Machine Learning to reconstruct GRB lightcurves

The current knowledge in cosmology deals with open problems whose solutions are still under investigation. The main issue is the so-called Hubble constant ($H_0$) tension, namely, the $4-6 σ$ discrepancy between the local value of $H_0$ obtained with Cepheids+Supernovae Ia (SNe Ia) and the cosmological one estimated from the observations of the Cosmic Microwave Background (CMB). For the investigation of this problem, probes that span all over the redshift $z$ ranges are needed. Cepheids are local objects, SNe Ia reached up to $z=2.9$, and CMB is observed at $z=1100$. In this context, the use of probes at intermediate redshift $z>3$ is auspicious for casting more light on modern cosmology. The Gamma-ray Bursts (GRBs) are particularly suitable for this task, given their observability up to $z=9.4$. The use of GRBs as standardizable candles requires the use of tight and reliable astrophysical correlations and the presence of gaps in the GRB time-domain data represents an obstacle in this sense. In this work, we propose to improve the precision of the lightcurve (LC) parameters through a reconstruction process performed with the functional forms of GRB LCs and the Gaussian Processes (GP). The filling of gaps in the GRB LCs through these processes shows an improvement up to $41.5\%$ on the precision of the LC parameters fitting, which lead to a reduced scatter in the astrophysical correlations and, thus, in the estimation of cosmological parameters.

astro-ph.CO

GRB Redshift Classifier to Follow-up High-Redshift GRBs Using Supervised Machine Learning

Gamma-ray bursts (GRBs) are intense, short-lived bursts of gamma-ray radiation observed up to a high redshift ($z \sim 10$) due to their luminosities. Thus, they can serve as cosmological tools to probe the early Universe. However, we need a large sample of high$-z$ GRBs, currently limited due to the difficulty in securing time at the large aperture Telescopes. Thus, it is painstaking to determine quickly whether a GRB is high$z$ or low$-z$, which hampers the possibility of performing rapid follow-up observations. Previous efforts to distinguish between high$-$ and low$-z$ GRBs using GRB properties and machine learning (ML) have resulted in limited sensitivity. In this study, we aim to improve this classification by employing an ensemble ML method on 251 GRBs with measured redshifts and plateaus observed by the Neil Gehrels Swift Observatory. Incorporating the plateau phase with the prompt emission, we have employed an ensemble of classification methods to enhance the sensitivity unprecedentedly. Additionally, we investigate the effectiveness of various classification methods using different redshift thresholds, $z_{threshold}$=$z_t$ at $z_{t}=$ 2.0, 2.5, 3.0, and 3.5. We achieve a sensitivity of 87\% and 89\% with a balanced sampling for both $z_{t}=3.0$ and $z_{t}=3.5$, respectively, representing a 9\% and 11\% increase in the sensitivity over Random Forest used alone. Overall, the best results are at $z_{t} = 3.5$, where the difference between the sensitivity of the training set and the test set is the smallest. This enhancement of the proposed method paves the way for new and intriguing follow-up observations of high$-z$ GRBs.

astro-ph.HE

Investigating the Redshift Evolution of Lensing Galaxy Density Slopes via Model-Independent Distance Ratios

Strong lensing systems, expected to be abundantly discovered by next-generation surveys, offer a powerful tool for studying cosmology and galaxy evolution. The connection between galaxy structure and cosmology through distance ratios highlights the need to examine the evolution of lensing galaxy mass density profiles. We propose a novel, dark energy-model-independent method to investigate the mass density slopes of lensing galaxies and their redshift evolution using an extended power-law (EPL) model. We employ a non-parametric approach based on Artificial Neural Networks (ANNs) trained on Type Ia Supernovae (SNIa) data to reconstruct distance ratios of strong lensing systems. These ratios are compared with theoretical predictions to estimate the evolution of EPL model parameters. Analyses conducted at three levels, including the combined sample, individual lenses, and binned groups, ensure robust and reliable estimates. A negative trend in the mass density slope with redshift is observed, quantified as $\partialγ/\partial z = -0.20 \pm 0.12$ under a triangular prior for anisotropy. This study demonstrates that the redshift evolution of density slopes in lensing galaxies can be determined independently of dark energy models. Simulations based on LSST Rubin Observatory forecasts, which anticipate 100,000 strong lenses, show that spectroscopic follow-up of just 10 percent of these systems can constrain the redshift evolution coefficient with uncertainty ($Δ\partialγ/\partial z$) to 0.021. This precision distinguishes evolving and non-evolving density slopes, providing new insights into galaxy evolution and cosmology.

astro-ph.CO