arXiv subjects

R. S. de Souza

Publications and source records attributed to R. S. de Souza.

At least 19 recordsLinked to original sources

arXiv2026

Galaxy interactions in void substructures: Morphology and stellar populations of two triplets from CAVITY

Context. Cosmic voids are underdense regions of the Universe that provide a unique environment to study galaxy evolution in relative isolation. Galaxy triplets in voids are rare systems where local interactions may strongly influence galaxy properties. Aims. We study the stellar populations, morphologies, mass assembly histories, and dynamical properties of six galaxies belonging to two void triplets from the Calar Alto Void Integral-field Treasury surveY (CAVITY): CAVITY5273X and VGS31. Methods. We used integral-field unit spectroscopy and performed full spectral fitting with the FADO code, which models stellar and nebular emission simultaneously. Spatially resolved maps of stellar age, metallicity, and star formation rate were reconstructed using the integrated nested Laplace approximation. Morphological properties were derived using morfometryka, emission-line diagnostics were applied, and mass assembly functions were computed. Stellar masses and metallicities were compared to the mass-metallicity relation for void galaxies. Results. The two triplets show different evolutionary behaviours. CAVITY52731 is a massive quenched galaxy hosting an active galactic nucleus, while its companions and all galaxies in VGS31 are dominated by young stellar populations and recent star formation. Five galaxies experienced rapid stellar mass growth in the last 2 Gyr. Disturbed morphologies, including asymmetries and tidal features, indicate ongoing interactions. Galaxies in CAVITY5273X follow the expected void mass-metallicity relation, while VGS31 members show significant deviations. Conclusions. Our results show that local interactions can drive significant galaxy evolution even in the most underdense cosmic environments.

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arXiv2025

The Milky Way in motion: gauging stellar trajectories that shape the Galactic thin disc

As stars traverse the Milky Way, their orbits evolve through perturbations that alter their orbital radii. These changes arise from two mechanisms: churning, which modifies angular momentum, and blurring, which induces eccentric orbits without major angular momentum change. To assess whether churning or blurring dominates the dynamical evolution of Gaia-ESO stars, we refine Galactic chemical-evolution models by constructing finer grids that span a wider age range. Using a generalised additive model (GAM), we estimate stellar birth radii beyond the limits of binned metallicity models and compare them with dynamical parameters derived from Gaia parallaxes and proper motions, and Galpy. Our metallicity-stratified sample, grouped through hierarchical clustering of 21 chemical abundances, reveals clear migratory signatures: metal-rich stars formed in the inner disc preferentially move outwards, while more metal-poor stars formed at larger radii tend to migrate inwards. About 75% of stars show signs of churning, while the remainder are largely undisturbed or shaped by blurring. These patterns vary among chemical groups, likely reflecting interactions with the Galactic bar and spiral arms.

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arXiv2025

Probing the origins. II. Unravelling lithium depletion and stellar motion: Intrinsic stellar properties drive depletion, not kinematics

In Paper I, we classified a stellar sample from the thin disc with a broad range in metallicity as being churned outward or inward, or blurred/undisturbed. In this paper (Paper II), we delve deeper by analysing our entire metallicity-stratified sample along with their dynamic properties, focusing on the connection between radial migration and Li depletion. We analyse the chemo-dynamics of a set of 1188 thin disc dwarf stars observed by the \textit{Gaia}-ESO survey, previously classified into six metallicity-stratified groups via Hierarchical Clustering (HC). We examine several features, such as effective temperatures, masses, and dynamic properties. We also implement a parametric survival analysis using penalised splines (logistic distribution) to quantify how stellar properties and motion (or migration) direction jointly influence Li depletion patterns. We find that stars in our sample that appear to have churned outward are predominantly Li-depleted, regardless of their metallicities. These stars are also the oldest, coldest, and least massive compared to those in the same HC group that have either churned inward or kept their orbital radii. Our survival analysis confirms temperature as the primary driver of Li depletion, followed by metallicity and age, while migration direction shows negligible influence. The increasing proportion of outward-churned stars with higher metallicity (and older ages) indicates their dominant influence on the overall trend observed in the [Fe/H]-A(Li) space for stellar groups with [Fe/H]>0. The survival model reinforces that the observed Li depletion stems primarily from intrinsic stellar properties (cool temperatures, higher metallicity, old ages) rather than migration history. This suggests the metallicity-dependent depletion pattern emerges through stellar evolution rather than Galactic dynamical processes.

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arXiv2025

Probing the origins. I. Generalised Additive Model inference of birth radii for Milky Way stars in the solar vicinity

We employ a Generalised Additive Model (GAM) to address the limitations inherent in radial metallicity gradients predicted by chemical evolution models, thereby facilitating the estimation of birth radii for the thin disc stars in our sample based on their ages and chemical composition. We then juxtapose the birth radius predictions derived from the GAM with the calculated guiding radii, among other dynamic parameters. Metal-rich stars, formed in the inner regions of the Milky Way, seem to be predominantly churned outward. Their metal-poor counterparts, formed in the outer thin disc, exhibit the opposite behaviour. The proportion of blurred/undisturbed stars generally increases with decreasing metallicity when compared to their churned counterparts. Approximately $3/4$ of the sample has been affected by (inward or outward) churning, while the remaining $\sim 1/4$ has either been influenced by blurring or remained undisturbed. These percentages vary considerably across different metallicity-stratified groups. Also, a large age gap is identified between churned and blurred/undisturbed sub-samples within each HC-based group, being the outward-churned stars systematically the oldest, inward-churned stars the youngest, and blurred/undisturbed stars in intermediate ages. We also detect significant differences in angular momenta in the $z$ component, for stars that have either churned inward or outward, when compared to their blurred/undisturbed counterparts. Additionally, we observe the potential effects of the pericentric passage of the Sagittarius dwarf galaxy in our most metal-poor subset of stars, formed in the outer disc. Finally, we estimate that the Sun's most probable birth radius is $7.08 \pm 0.24$ kpc, with a 3$σ$ range spanning from 6.46 to 7.81 kpc, in agreement with previous studies.

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arXiv2024

ELEPHANT: ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients

Context. Transient astronomical events that exhibit no discernible association with a host galaxy are commonly referred to as hostless. These rare phenomena are associated with extremely energetic events, and they can offer unique insights into the properties and evolution of stars and galaxies. However, the sheer number of transients captured by contemporary high-cadence astronomical surveys renders the manual identification of all potential hostless transients impractical. Therefore, creating a systematic identification tool is crucial for studying these elusive events. Aims. We present the ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients (ELEPHANT), a framework for filtering hostless transients in astronomical data streams. Methods. We used Fink to access all the ZTF alerts produced between January/2022 and December/2023, selecting only those associated with extragalactic transients. We then processed the associated stamps using a sequence of image analysis techniques to retrieve hostless candidates. Results. We find that less than 2% of all analyzed transients are potentially hostless. Among them, approximately 10% have a spectroscopic class reported on TNS, with Type Ia supernova being the most common class, followed by SLSN. Among the hostless candidates retrieved by our pipeline, there was SN 2018ibb, which has been proposed to be a PISN candidate; and SN 2022ann, one of only five known SNe Icn. When no class is reported on TNS, the dominant classes are QSO and SN candidates, the former obtained from SIMBAD and the latter inferred using the Fink ML classifier. Conclusions. ELEPHANT represents an effective strategy to filter extragalactic events within large and complex astronomical alert streams. There are many applications for which this pipeline will be useful, ranging from transient selection for follow-up to studies of transient environments.

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arXiv2023

Enabling the discovery of fast transients: A kilonova science module for the Fink broker

We describe the fast transient classification algorithm in the center of the kilonova (KN) science module currently implemented in the Fink broker and report classification results based on simulated catalogs and real data from the ZTF alert stream. We used noiseless, homogeneously sampled simulations to construct a basis of principal components (PCs). All light curves from a more realistic ZTF simulation were written as a linear combination of this basis. The corresponding coefficients were used as features in training a random forest classifier. The same method was applied to long (>30 days) and medium (<30 days) light curves. The latter aimed to simulate the data situation found within the ZTF alert stream. Classification based on long light curves achieved 73.87% precision and 82.19% recall. Medium baseline analysis resulted in 69.30% precision and 69.74% recall, thus confirming the robustness of precision results when limited to 30 days of observations. In both cases, dwarf flares and point Type Ia supernovae were the most frequent contaminants. The final trained model was integrated into the Fink broker and has been distributing fast transients, tagged as KN_candidates, to the astronomical community, especially through the GRANDMA collaboration. We showed that features specifically designed to grasp different light curve behaviors provide enough information to separate fast (KN-like) from slow (non-KN-like) evolving events. This module represents one crucial link in an intricate chain of infrastructure elements for multi-messenger astronomy which is currently being put in place by the Fink broker team in preparation for the arrival of data from the Vera Rubin Observatory Legacy Survey of Space and Time.

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arXiv2022

GLADE+: An Extended Galaxy Catalogue for Multimessenger Searches with Advanced Gravitational-wave Detectors

We present GLADE+, an extended version of the GLADE galaxy catalogue introduced in our previous paper for multimessenger searches with advanced gravitational-wave detectors. GLADE+ combines data from six separate but not independent astronomical catalogues: the GWGC, 2MPZ, 2MASS XSC, HyperLEDA, and WISExSCOSPZ galaxy catalogues, and the SDSS-DR16Q quasar catalogue. To allow corrections of CMB-frame redshifts for peculiar motions, we calculated peculiar velocities along with their standard deviations of all galaxies having $B$-band magnitude data within redshift $z=0.05$ using the "Bayesian Origin Reconstruction from Galaxies" formalism. GLADE+ is complete up to luminosity distance $d_L=47^{+4}_{-2}$ Mpc in terms of the total expected $B$-band luminosity of galaxies, and contains all of the brightest galaxies giving 90\% of the total $B$-band and $K$-band luminosity up to $d_L\simeq 130$ Mpc. We include estimations of stellar masses and individual binary neutron star merger rates for galaxies with $W1$ magnitudes. These parameters can help in ranking galaxies in a given gravitational wave localization volume in terms of their likelihood of being hosts, thereby possibly reducing the number of pointings and total integration time needed to find the electromagnetic counterpart.

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arXiv2021

A high pitch angle structure in the Sagittarius Arm

Context: In spiral galaxies, star formation tends to trace features of the spiral pattern, including arms, spurs, feathers, and branches. However, in our own Milky Way, it has been challenging to connect individual star-forming regions to their larger Galactic environment owing to our perspective from within the disk. One feature in nearly all modern models of the Milky Way is the Sagittarius Arm, located inward of the Sun with a pitch angle of ~12 deg. Aims: We map the 3D locations and velocities of star-forming regions in a segment of the Sagittarius Arm using young stellar objects (YSOs) from the Spitzer/IRAC Candidate YSO (SPICY) catalog to compare their distribution to models of the arm. Methods: Distances and velocities for these objects are derived from Gaia EDR3 astrometry and molecular line surveys. We infer parallaxes and proper motions for spatially clustered groups of YSOs and estimate their radial velocities from the velocities of spatially associated molecular clouds. Results: We identify 25 star-forming regions in the Galactic longitude range l~4.0-18.5 deg arranged in a narrow, ~1 kpc long linear structure with a high pitch angle of $ψ= 56$ deg and a high aspect ratio of ~7:1. This structure includes massive star-forming regions such as M8, M16, M17, and M20. The motions in the structure are remarkably coherent, with velocities in the direction of Galactic rotation of $240\pm3$ km/s (slightly higher than average) and slight drifts toward the Galactic center (-4.3 km/s) and in the negative Z direction (-2.9 km/s). The rotational shear experienced by the structure is 4.6 km/s/kpc. Conclusions: The observed 56 deg pitch angle is remarkably high for a segment of the Sagittarius Arm. We discuss possible interpretations of this feature as a substructure within the lower pitch angle Sagittarius Arm, as a spur, or as an isolated structure.

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arXiv2019

UV bright red-sequence galaxies: how do UV upturn systems evolve in redshift and stellar mass?

The so-called ultraviolet (UV) upturn of elliptical galaxies is a phenomenon characterised by the up-rise of their fluxes in bluer wavelengths, typically in the 1,200-2,500A range. This work aims at estimating the rate of occurrence of the UV upturn over the entire red-sequence population of galaxies that show significant UV emission. This assessment is made considering it as function of three parameters: redshift, stellar mass, and -- what may seem counter-intuitive at first -- emission-line classification. We built a multiwavelength spectro-photometric catalogue from the Galaxy Mass Assembly survey, together with aperture-matched data from Galaxy Evolution Explorer Medium-Depth Imaging Survey (MIS) and Sloan Digital Sky Survey, covering the redshift range between 0.06 and 0.40. From this sample, we analyse the UV emission among UV bright galaxies, by selecting those that occupy the red-sequence locus in the (NUV-r) x (FUV-NUV) chart; then, we stratify the sample by their emission-line classes. To that end, we make use of emission-line diagnostic diagrams, focusing the analysis in retired/passive lineless galaxies. Then, a Bayesian logistic model was built to simultaneously deal with the effects of all galaxy properties (including emission-line classification or lack thereof). The main results show that retired/passive systems host an up-rise in the fraction of UV upturn or redshifts between 0.06 and 0.25, followed by an in-fall up to 0.35. Additionally, we show that the fraction of UV upturn hosts rises with increasing stellar mass.

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arXiv2019

The Southern Photometric Local Universe Survey (S-PLUS): improved SEDs, morphologies and redshifts with 12 optical filters

The Southern Photometric Local Universe Survey (S-PLUS) is imaging ~9300 deg^2 of the celestial sphere in twelve optical bands using a dedicated 0.8 m robotic telescope, the T80-South, at the Cerro Tololo Inter-American Observatory, Chile. The telescope is equipped with a 9.2k by 9.2k e2v detector with 10 um pixels, resulting in a field-of-view of 2 deg^2 with a plate scale of 0.55"/pixel. The survey consists of four main subfields, which include two non-contiguous fields at high Galactic latitudes (8000 deg^2 at |b| > 30 deg) and two areas of the Galactic plane and bulge (for an additional 1300 deg^2). S-PLUS uses the Javalambre 12-band magnitude system, which includes the 5 u, g, r, i, z broad-band filters and 7 narrow-band filters centered on prominent stellar spectral features: the Balmer jump/[OII], Ca H+K, H-delta, G-band, Mg b triplet, H-alpha, and the Ca triplet. S-PLUS delivers accurate photometric redshifts (delta_z/(1+z) = 0.02 or better) for galaxies with r < 20 AB mag and redshift < 0.5, thus producing a 3D map of the local Universe over a volume of more than 1 (Gpc/h)^3. The final S-PLUS catalogue will also enable the study of star formation and stellar populations in and around the Milky Way and nearby galaxies, as well as searches for quasars, variable sources, and low-metallicity stars. In this paper we introduce the main characteristics of the survey, illustrated with science verification data highlighting the unique capabilities of S-PLUS. We also present the first public data release of ~336 deg^2 of the Stripe-82 area, which is available at http://datalab.noao.edu/splus.

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arXiv2019

Assessing the photometric redshift precision of the S-PLUS survey: the Stripe-82 as a test-case

In this paper we present a thorough discussion about the photometric redshift (photo-z) performance of the Southern Photometric Local Universe Survey (S-PLUS). This survey combines a 7 narrow + 5 broad passband filter system, with a typical photometric-depth of r$\sim$21 AB. For this exercise, we utilize the Data Release 1 (DR1), corresponding to 336 deg$^{2}$ from the Stripe-82 region. We rely on the \texttt{BPZ2} code to compute our estimates, using a new library of SED models, which includes additional templates for quiescent galaxies. When compared to a spectroscopic redshift control sample of $\sim$100k galaxies, we find a precision of $σ_{z}<$0.8\%, $<$2.0\% or $<$3.0\% for galaxies with magnitudes r$<$17, $<$19 and $<$21, respectively. A precision of 0.6\% is attained for galaxies with the highest \texttt{Odds} values. These estimates have a negligible bias and a fraction of catastrophic outliers inferior to 1\%. We identify a redshift window (i.e., 0.26$<z<$0.32) where our estimates double their precision, due to the simultaneous detection of two emission-lines in two distinct narrow-bands; representing a window opportunity to conduct statistical studies such as luminosity functions. We forecast a total of $\sim$2M, $\sim$16M and $\sim$32M galaxies in the S-PLUS survey with a photo-z precision of $σ_{z}<$1.0\%, $<$2.0\% and $<$2.5\% after observing 8000 $deg^{2}$. We also derive redshift Probability Density Functions, proving their reliability encoding redshift uncertainties and their potential recovering the $n(z)$ of galaxies at $z<0.4$, with an unprecedented precision for a photometric survey in the southern hemisphere.

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arXiv2019

Gaia DR2 unravels incompleteness of nearby cluster population: New open clusters in the direction of Perseus

Open clusters (OCs) are popular tracers of the structure and evolutionary history of the Galactic disk. The OC population is often considered to be complete within 1.8 kpc of the Sun. The recent Gaia Data Release 2 (DR2) allows the latter claim to be challenged. We perform a systematic search for new OCs in the direction of Perseus using precise and accurate astrometry from Gaia DR2. We implement a coarse-to-fine search method. First, we exploit spatial proximity using a fast density-aware partitioning of the sky via a k-d tree in the spatial domain of Galactic coordinates, (l, b). Secondly, we employ a Gaussian mixture model in the proper motion space to quickly tag fields around OC candidates. Thirdly, we apply an unsupervised membership assignment method, UPMASK, to scrutinise the candidates. We visually inspect colour-magnitude diagrams to validate the detected objects. Finally, we perform a diagnostic to quantify the significance of each identified overdensity in proper motion and in parallax space We report the discovery of 41 new stellar clusters. This represents an increment of at least 20% of the previously known OC population in this volume of the Milky Way. We also report on the clear identification of NGC 886, an object previously considered an asterism. This letter challenges the previous claim of a near-complete sample of open clusters up to 1.8 kpc. Our results reveal that this claim requires revision, and a complete census of nearby open clusters is yet to be found.

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arXiv2019

Astro2020 Science White Paper: The Next Decade of Astroinformatics and Astrostatistics

Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and large astronomical surveys, it is becoming clear that future advances will also rely heavily on how those data are analyzed and interpreted. New methodologies derived from advances in statistics, computer science, and machine learning are beginning to be employed in sophisticated investigations that are not only bringing forth new discoveries, but are placing them on a solid footing. Progress in wide-field sky surveys, interferometric imaging, precision cosmology, exoplanet detection and characterization, and many subfields of stellar, Galactic and extragalactic astronomy, has resulted in complex data analysis challenges that must be solved to perform scientific inference. Research in astrostatistics and astroinformatics will be necessary to develop the state-of-the-art methodology needed in astronomy. Overcoming these challenges requires dedicated, interdisciplinary research. We recommend: (1) increasing funding for interdisciplinary projects in astrostatistics and astroinformatics; (2) dedicating space and time at conferences for interdisciplinary research and promotion; (3) developing sustainable funding for long-term astrostatisics appointments; and (4) funding infrastructure development for data archives and archive support, state-of-the-art algorithms, and efficient computing.

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arXiv2019

A case study of hurdle and generalized additive models in astronomy: the escape of ionizing radiation

The dark ages of the Universe end with the formation of the first generation of stars residing in primeval galaxies. These objects were the first to produce ultraviolet ionizing photons in a period when the cosmic gas changed from a neutral state to an ionized one, known as Epoch of Reionization (EoR). A pivotal aspect to comprehend the EoR is to probe the intertwined relationship between the fraction of ionizing photons capable to escape dark haloes, also known as the escape fraction ($f_{esc}$), and the physical properties of the galaxy. This work develops a sound statistical model suitable to account for such non-linear relationships and the non-Gaussian nature of $f_{esc}$. This model simultaneously estimates the probability that a given primordial galaxy starts the ionizing photon production and estimates the mean level of the $f_{esc}$ once it is triggered. The model was employed in the First Billion Years simulation suite, from which we show that the baryonic fraction and the rate of ionizing photons appear to have a larger impact on $f_{esc}$ than previously thought. A naive univariate analysis of the same problem would suggest smaller effects for these properties and a much larger impact for the specific star formation rate, which is lessened after accounting for other galaxy properties and non-linearities in the statistical model.

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arXiv2019

Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning

We report a framework for spectroscopic follow-up design for optimizing supernova photometric classification. The strategy accounts for the unavoidable mismatch between spectroscopic and photometric samples, and can be used even in the beginning of a new survey -- without any initial training set. The framework falls under the umbrella of active learning (AL), a class of algorithms that aims to minimize labelling costs by identifying a few, carefully chosen, objects which have high potential in improving the classifier predictions. As a proof of concept, we use the simulated data released after the Supernova Photometric Classification Challenge (SNPCC) and a random forest classifier. Our results show that, using only 12\% the number of training objects in the SNPCC spectroscopic sample, this approach is able to double purity results. Moreover, in order to take into account multiple spectroscopic observations in the same night, we propose a semi-supervised batch-mode AL algorithm which selects a set of $N=5$ most informative objects at each night. In comparison with the initial state using the traditional approach, our method achieves 2.3 times higher purity and comparable figure of merit results after only 180 days of observation, or 800 queries (73% of the SNPCC spectroscopic sample size). Such results were obtained using the same amount of spectroscopic time necessary to observe the original SNPCC spectroscopic sample, showing that this type of strategy is feasible with current available spectroscopic resources. The code used in this work is available in the COINtoolbox: https://github.com/COINtoolbox/ActSNClass .

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arXiv2018

The Overlooked Potential of Generalized Linear Models in Astronomy-II: Gamma regression and photometric redshifts

Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the underlying physical processes of the data. In this article, and the companion papers of this series, we present the set of Generalized Linear Models (GLMs) as a fast alternative method for tackling general astronomical problems, including the ones related to the machine learning paradigm. To demonstrate the applicability of GLMs to inherently positive and continuous physical observables, we explore their use in estimating the photometric redshifts of galaxies from their multi-wavelength photometry. Using the gamma family with a log link function we predict redshifts from the PHoto-z Accuracy Testing simulated catalogue and a subset of the Sloan Digital Sky Survey from Data Release 10. We obtain fits that result in catastrophic outlier rates as low as ~1% for simulated and ~2% for real data. Moreover, we can easily obtain such levels of precision within a matter of seconds on a normal desktop computer and with training sets that contain merely thousands of galaxies. Our software is made publicly available as an user-friendly package developed in Python, R and via an interactive web application (https://cosmostatisticsinitiative.shinyapps.io/CosmoPhotoz). This software allows users to apply a set of GLMs to their own photometric catalogues and generates publication quality plots with minimum effort from the user. By facilitating their ease of use to the astronomical community, this paper series aims to make GLMs widely known and to encourage their implementation in future large-scale projects, such as the Large Synoptic Survey Telescope.

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arXiv2018

Spatial field reconstruction with INLA: Application to IFU galaxy data

Astronomical observations of extended sources, such as cubes of integral field spectroscopy (IFS), encode auto-correlated spatial structures that cannot be optimally exploited by standard methodologies. This work introduces a novel technique to model IFS datasets, which treats the observed galaxy properties as realizations of an unobserved Gaussian Markov random field. The method is computationally efficient, resilient to the presence of low-signal-to-noise regions, and uses an alternative to Markov Chain Monte Carlo for fast Bayesian inference, the Integrated Nested Laplace Approximation (INLA). As a case study, we analyse 721 IFS data cubes of nearby galaxies from the CALIFA and PISCO surveys, for which we retrieve the maps of the following physical properties: age, metallicity, mass and extinction. The proposed Bayesian approach, built on a generative representation of the galaxy properties, enables the creation of synthetic images, recovery of areas with bad pixels, and an increased power to detect structures in datasets subject to substantial noise and/or sparsity of sampling. A snippet code to reproduce the analysis of this paper is available in the COIN toolbox, together with the field reconstructions of the CALIFA and PISCO samples.

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arXiv2017

cosmoabc: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogues. Here we present cosmoabc, a Python ABC sampler featuring a Population Monte Carlo (PMC) variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code is very flexible and can be easily coupled to an external simulator, while allowing to incorporate arbitrary distance and prior functions. As an example of practical application, we coupled cosmoabc with the numcosmo library and demonstrate how it can be used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function. cosmoabc is published under the GPLv3 license on PyPI and GitHub and documentation is available at http://goo.gl/SmB8EX

astro-ph.CO↗