Repositorio DSpace :: Examinando por Autor "Sarro Baro, Luis Manuel"

Examinando por Autor "Sarro Baro, Luis Manuel"

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A Bayesian Graphical Model for Frequency Recovery of Periodic Variable Stars
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2014-02-27) Delgado, Hector E.; Sarro Baro, Luis Manuel
This thesis has been developed in the context of the recently launched European Space Agency’s Gaia mission. The thesis has addressed the problem of determining the probability distributions of the real physical parameters for a variable star population, given their recovered values by the Data Processing and Analysis Consortium (DPAC) from the telemetry of the satellite. These recovered values are affected by a number of stochastic errors and systematic biases due to the aliasing phenomenon as a product of the Gaia scanning law, the optical and photometric resolution of the satellite and the algorithms used in the recovery process. The purpose of the thesis has been to model the data recovery process and infer the real distributions for the frequencies, apparent Gmagnitudes and amplitudes for a Large Magellanic Cloud (LMC) classic Cepheid star population. A two level Bayesian graphical model was constructed with the aid of a domain expert to model the recovery process and a Markov chain Monte Carlo (MCMC) algorithm specified to perform the inference. The system was implemented in the declarative BUGS language. The system was trained from a set of recovered data from an artificially generated real distribution of LMC Cepheids. The system was tested by comparing the parameters of the artificially generated real distributions with the distributions inferred by the MCMC algorithm. The results obtained have shown that the system remove successfully the systematic biases and is able to infer correctly the real frequency distribution. The results have also shown a correct inference for the real apparent magnitudes in the G band. Nevertheless, the results obtained for the case of the real amplitude distribution have not allowed to establish significant conclusions.
Análisis estadístico de indicadores de juventud en espectros RP de estrellas enanas ultrafrías de Gaia
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial, 2023-03-14) Diez Tabara, Daniel; Sarro Baro, Luis Manuel
Durante la misión espacial del telescopio Gaia de la Agencia Espacial Europea se obtendrán una gran cantidad de datos de objetos celestes. Entre esa gran cantidad de datos se encuentran medidas astrométricas (como distancias, posiciones o movimientos propios) y también medidas fotométricas (como brillos aparentes y espectros). Estas medidas fotométricas forman parte del conjunto de datos que periódicamente la sonda envía a la base en la tierra y sobre las que se centra este trabajo. En concreto, se analizará los espectros RP (longitudes de onda características de la luz roja 640-1050 nm) de un subconjunto de estrellas llamadas enanas ultrafrías y se aplicarán diversas técnicas de creación de espacios latentes de menor dimensión, para detectar indicios de juventud en dichos espectros.
Bayesian Inference on the Pleiades Open Cluster
(Universidad de Educación a Distancia (UNED), 2023-09) Palmero Moya, Francisco José; Olivares Romero, Javier; Sarro Baro, Luis Manuel
Context: Age is one of the fundamental parameters of any astrophysical object, being it a galaxy, a star, or a planet. The main three stellar dating techniques in astrophysics are dynamical ages, isochrone ages, and the chemical abundance of the Lithium isotopes. However, these methods produce ages that differ by up to 50 % for stars younger than the Sun. The main culprit for these differences is the lack of a consistent and robust age calibration due to the fact that the only sufficiently precise age available is that of the Sun. Aims: Our aim is to define and implement a Bayesian hierarchical model able to determine the ages of star clusters and associations through two age dating techniques: isochrones and Lithium abundance. Methods: The resulting model combines existent photometric, parallax, and chemical abundance of Lithium data sets of stars belonging to stellar open clusters to infer its age distribution through modern and robust artificial intelligence methods. A Neural Network is trained given a grid of pre-calculated BT-Settl models to interpolate the spectral energy distributions of stars, working as a black-box interpolator in the model. The Bayesian hierarchical model not only facilitates simultaneous inference of star-level parameters but also offers an elegant framework for effectively pooling open cluster information and propagating uncertainty. Markov Chain Monte Carlo techniques allow us to sample the posterior distribution using the Hamiltonian Monte Carlo algorithm. Results: Our model’s robust performance on a synthetic dataset with known parameters, coupled with its successful age estimation of the Pleiades Open Cluster (116.8 ± 1.9 Myr), represents a significant advancement in the field by overcoming key challenges that have hindered previous attempts mixing artifical intelligence paradigms. The resulting model signifies a new methodology for age estimation that can be applied to a wide range of open clusters, with the Pleiades serving as the initial test benchmark.
Big Data Clustering
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial, 2017-07-07) Tizón Galisteo, Daniel; Sarro Baro, Luis Manuel
En este trabajo he realizado una investigación sobre algoritmos de clusterización que tienen órdenes de complejidad lineales o logarítmicos respecto al tiempo de ejecución, y que pueden ser paralelizables, y por tanto nos permitan trabajar con grandes cantidades de datos. Además, hay que tener en cuenta que puesto que utilizaré un cluster de Spark, los algoritmos que podremos utilizar estarán limitados por aquellos que se encuentran implementados en la librería MLlib de Apache Spark. También he llevado a cabo un estudio de distintos índices de validación interna y externa que podemos emplear para evaluar la calidad de los grupos o clusters creados por dichos algoritmos. Como caso de uso, he utilizado los datos astrométricos procedentes de millones de estrellas de nuestra galaxia proporcionados por la misión Gaia de la Agencia Espacial Europea para realizar una clusterización de dichas estrellas, con el objetivo de tratar de encontrar cúmulos estelares nuevos o recabar más información sobre los ya existentes. Para llevar a cabo el caso de estudio, dada la gran cantidad de datos a tratar, he utilizado la infraestructura facilitada por la DPAC (Data Processing and Analysis Consortium), consistente en un cluster de Apache Spark formado por 6 nodos con 16 cores y 64Gb de RAM cada uno.
Computational Framework for the Assesment of New Forms of Political Organization in Social Media
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2016-07-07) Aragón Asenjo, Pablo; Kaltenbrunner, Andreas; Sarro Baro, Luis Manuel
Social media has become a key mechanism for the organization of grassroots movements. In the 2015 Barcelona City Council election, Barcelona en Comú, an emerging grassroots party, was the most voted one. This candidacy was devised by activists involved in the Spanish 15M movement in order to turn citizen outrage into political change. On the one hand, the 15M movement is based on a decentralized structure. On the other hand, political science literature postulates that parties historically develop oligarchical leadership structures. This tension motivates to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. This thesis proposes a computational framework to (1) better identify the Twitter networks of political parties by setting a confidence parameter in a popular community detection algorithm of the state of the art, and (2) analyze each party network by measuring the hierarchical structure, small-world phenomenon and coreness. The evaluation of the framework on the Twitter networks of the parties that ran for this election shows that the extended community detection algorithm effectively set boundaries between party networks. Although most parties consist of one single cluster, in Barcelona en Comú two well-defined groups co-exist: a cluster dominated by the party leader and the collective accounts, and another cluster formed by the movement activists. While the former group is highly centralized like traditional parties, the latter one stands out for its decentralized, cohesive and resilient structure.
The cosmic DANCe of Perseus - I. Membership, phase-space structure, mass, and energy distributions
(EDP Sciences, 2023-02-27) Olivares Romero, Javier; Bouy, Hervé; Miret Roig, Nuria; Galli, P. A. B.; Sarro Baro, Luis Manuel; Moraux, Estelle; Berihuete, Ángel; https://orcid.org/0000-0002-7084-487X; https://orcid.org/0000-0001-5292-0421; https://orcid.org/0000-0003-2271-9297; https://orcid.org/0000-0003-4127-7295; https://orcid.org/0000-0002-8589-4423
Context. Star-forming regions are excellent benchmarks for testing and validating theories of star formation and stellar evolution. The Perseus star-forming region, being one of the youngest (< 10 Myr), closest (280−320 pc), and most studied in the literature, is a fundamental benchmark. Aims. We aim to study the membership, phase-space structure, mass, and energy (kinetic plus potential) distribution of the Perseus star-forming region using public catalogues (Gaia, APOGEE, 2MASS, and Pan-STARRS). Methods. We used Bayesian methodologies that account for extinction to identify the Perseus physical groups in the phase-space, retrieve their candidate members, derive their properties (age, mass, 3D positions, 3D velocities, and energy), and attempt to reconstruct their origin. Results. We identify 1052 candidate members in seven physical groups (one of them new) with ages between 3 and 10 Myr, dynamical super-virial states, and large fractions of energetically unbounded stars. Their mass distributions are broadly compatible with that of Chabrier for masses ≳0.1 M⊙ and do not show hints of over-abundance of low-mass stars in NGC 1333 with respect to IC 348. These groups’ ages, spatial structure, and kinematics are compatible with at least three generations of stars. Future work is still needed to clarify if the formation of the youngest was triggered by the oldest. Conclusions. The exquisite Gaia data complemented with public archives and mined with comprehensive Bayesian methodologies allow us to identify 31% more members than previous studies, discover a new physical group (Gorgophone: 7 Myr, 191 members, and 145 M⊙), and confirm that the spatial, kinematic, and energy distributions of these groups support the hierarchical star formation scenario.
Diseño de un Prototipo de Sistema Experto para la generación de los Informes de Calidad relativos a los Objetos Variables detectados por la Misión Espacial GAIA
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2012-09) Garcia Sedano, Fernando; Sarro Baro, Luis Manuel
El objetivo de este Trabajo Fin de Máster es el diseño de un SE diseñado para la tarea de evaluar la calidad de los muestreos o “surveys” de variabilidad obtenidos por la misión espacial GAIA. GAIA es una misión de la AGENCIA espacial Europea (ESA) con fecha prevista de lanzamiento en el año 2.013, con el objetivo de recoger datos para entender el origen y evolución de nuestra Galaxia. Esto implica la observación de unos 109 objetos celestes (el mayor y más preciso mapa galáctico realizado hasta la fecha) con posiciones, distancias y características espectrales básicas, convirtiéndose de este modo en la sucesora de la misión Hipparcos, aunque a una escala mucho mayor.
Estimación de la función de luminosidad de UCDs mediante técnicas de aprendizaje automático
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial, 2021-09-01) Arroyo Galende, Borja; Sarro Baro, Luis Manuel
Gaia es una misión espacial cuyo objetivo es medir una muestra de estrellas de nuestra Galaxia devolviendo tanto medidas astrométricas como fotométricas. El procesamiento de datos surge entonces de forma natural para poder responder a cuestiones planteadas por el ámbito científico. En este trabajo se crea un flujo de datos que comienza con la misión Gaia (junto con observaciones de otras misiones) y termina con la construcción de un modelo jerárquico multinivel encargado de estimar las probabilidades a posteriori de distintas variables astrofísicas junto con algunos parámetros. Para ello, primero se eliminan las observaciones ruidosas mediante un bosque aleatorio entrenado sobre los conjuntos de entrenamiento positivo, o de buenas soluciones astrométricas; y negativo, o de malas soluciones astrométricas. El resultado es una lista curada de estrellas, en cuanto a que poseen una buena solución astrométrica, que se introducen como entrada al modelo jerárquico bayesiano multinivel. Dicho modelo infiere las relaciones entre las distintas variables que intervienen en el proceso y da como resultado la estimación de la secuencia principal. La función de luminosidad se representa, a priori, según una exponencial. Esta suposición, junto con la mala escalabilidad del modelo jerárquico, debido a que posee un proceso gaussiano embebido, causan la imposibilidad de realizar una inferencia completa con todas las observaciones. La excedencia con creces del tiempo teórico de dedicación a este trabajo es el mayor impedimento de cara a finalizar lo que ha sido, y es, un estudio muy completo que aborda diferentes métodos del mundo de la ciencia de datos.
Estimación de la temperatura y gravedad de estrellas del archivo de COROT a partir de espectros FLAMES
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2011-09) León Manzano, Gonzalo; Sarro Baro, Luis Manuel
El área de conocimiento en el que la investigación se halla enmarcada es la Minería de Datos, cuyo objetivo es el descubrimiento de patrones en grandes volúmenes de datos. El conjunto de datos del que se quiere extraer conocimiento procede de la Astronomía, en concreto, son los espectros de un conjunto de estrellas de los que se pretende estimar diversos parámetros físicos.
Estudio y análisis de las técnicas del pipeline de OCA aplicadas a datos simulados de la misión GAIA
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2012-09-27) Pérez Liñana, Juan Gabriel; Sarro Baro, Luis Manuel; García Torres, Miguel
Este Trabajo de Fin de Master se enmarca dentro de la mision GAIA de la Agencia Europea del Espacio, cuyo lanzamiento esta previsto para nales de 2013. Debido al elevado volumen de datos que se generara, se ha decidido crear un consorcio para el procesamiento y analisis de datos, llamado Gaia Data Processing and Analysis Consortium (DPAC). Dicho consorcio se encuentra dividido en 10 unidades de coordinacion de las cuales, la octava (CU8), esta enfocada en la estimacion de parametros astrofsicos a partir de las observaciones. El presente trabajo pertenece a los estudios preliminares llevados a cabo dentro del bloque de trabajo Object Clustering Algorithm (OCA) de CU8. El objetivo principal de OCA es desarrollar las herramientas adecuadas para el analisis de los datos recibidos desde la perspectiva del agrupamiento. Los principales retos de OCA son estudiar la tecnicas mas adecuadas de agrupamiento para la naturaleza de los datos de GAIA y ser capaz de escalar dichas tecnicas para poder tratar el gran volumen de datos que se recibira a lo largo de la mision. A lo largo de este trabajo se presentaran las metodologas propuestas en la literatura para poder escalar algoritmos de agrupamiento as como la descripcion de las tecnicas elegidas debido a sus propiedades.
Evaluation of unsupervised clustering algorithms for variable stars data
(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2008-09) Herrera Plaza, Pilar; Sarro Baro, Luis Manuel
The aim of this master thesis is to assess the validity of unsupervised clustering algorithms to variable stars data classification for the Gaia mission. The use of these techniques allows to identify natural clustering without using any previous information about the classes and its distribution and, therefore, allows to discover new classes of objects. With this objective, we evaluate two probabilistic algorithms, one in which each cluster is characterized by a parametric distribution, and other, by a no-parametric distribution in a hierarchical clustering: Autoclass and HMAC (Hierarchical Mode Association Clustering). Both methods are evaluated against the same criteria, reproducibility, computation time, sensitivity to new classes and interpretability, in datasets that can grow up to 108 instances. These criteria are the first step to assess the feasibility of application of the algorithm but they are not enough to evaluate the goodness of clustering results. Despite the popular use of the unsupervised clustering techniques, the performance evaluation of clustering is an open question. It includes knowing how many clusters are actually present and how real is the clustering itself. Our clustering evaluation starts applying the expert knowledge and using a labeled dataset what allows to match some clusters with some variable stars types, but this is not enough to reach the objective of identifying each cluster. A review of the existing indices to evaluate clustering with objective criteria is included. Clusters and data are then analyzed to understand the results obtained with both methods biased by the method itself. A clustering combination method of these two algorithms is also tested as a technique that optimizes according multiple objective functions and trying to avoid some limitations of both algorithms.
Gaia Data Release 3 Chemical cartography of the Milky Way
(EDP Sciences, 2023-06-16) Recio Blanco, Alejandra; Kordopatis, G.; Laverny, P. de; Alonso Palicio, Pedro; Sarro Baro, Luis Manuel
Context. The motion of stars has been used to reveal details of the complex history of the Milky Way, in constant interaction with its environment. Nevertheless, to reconstruct the Galactic history puzzle in its entirety, the chemo-physical characterisation of stars is essential. Previous Gaia data releases were supported by a smaller, heterogeneous, and spatially biased mixture of chemical data from ground-based observations. Aims. Gaia Data Release 3 opens a new era of all-sky spectral analysis of stellar populations thanks to the nearly 5.6 million stars observed by the Radial Velocity Spectrometer (RVS) and parametrised by the GSP-Spec module. In this work, we aim to demonstrate the scientific quality of Gaia’s Milky Way chemical cartography through a chemo-dynamical analysis of disc and halo populations. Methods. Stellar atmospheric parameters and chemical abundances provided by Gaia DR3 spectroscopy are combined with DR3 radial velocities and EDR3 astrometry to analyse the relationships between chemistry and Milky Way structure, stellar kinematics, and orbital parameters. Results. The all-sky Gaia chemical cartography allows a powerful and precise chemo-dynamical view of the Milky Way with unprecedented spatial coverage and statistical robustness. First, it reveals the strong vertical symmetry of the Galaxy and the flared structure of the disc. Second, the observed kinematic disturbances of the disc – seen as phase space correlations – and kinematic or orbital substructures are associated with chemical patterns that favour stars with enhanced metallicities and lower [α/Fe] abundance ratios compared to the median values in the radial distributions. This is detected both for young objects that trace the spiral arms and older populations. Several α, iron-peak elements and at least one heavy element trace the thin and thick disc properties in the solar cylinder. Third, young disc stars show a recent chemical impoverishment in several elements. Fourth, the largest chemo-dynamical sample of open clusters analysed so far shows a steepening of the radial metallicity gradient with age, which is also observed in the young field population. Finally, the Gaia chemical data have the required coverage and precision to unveil galaxy accretion debris and heated disc stars on halo orbits through their [α/Fe] ratio, and to allow the study of the chemo-dynamical properties of globular clusters. Conclusions. Gaia DR3 chemo-dynamical diagnostics open new horizons before the era of ground-based wide-field spectroscopic surveys. They unveil a complex Milky Way that is the outcome of an eventful evolution, shaping it to the present day.
Gaia Data Release 3. A golden sample of astrophysical parameters
(EDP Sciences, 2023-06-16) Creevey, O. L.; Lobel, A.; Pancino, Elena; Sarro Baro, Luis Manuel
Context. Gaia Data Release 3 (DR3) provides a wealth of new data products for the astronomical community to exploit, including astrophysical parameters for half a billion stars. In this work, we demonstrate the high quality of these data products and illustrate their use in different astrophysical contexts. Aims. We produce homogeneous samples of stars with high-quality astrophysical parameters by exploiting Gaia DR3, while focusing on many regimes across the Hertzsprung-Russell (HR) diagram; spectral types OBA, FGKM, and ultracool dwarfs (UCDs). We also focus on specific subsamples of particular interest to the community: solar analogues, carbon stars, and the Gaia spectrophotometric standard stars (SPSS). Methods. We query the astrophysical parameter tables along with other tables in Gaia DR3 to derive the samples of the stars of interest. We validate our results using the Gaia catalogue itself and by comparison with external data. Results. We produced six homogeneous samples of stars with high-quality astrophysical parameters across the HR diagram for the community to exploit. We first focus on three samples that span a large parameter space: young massive disc stars (OBA; about 3 Million), FGKM spectral type stars (about 3 Million), and UCDs (about 20 000). We provide these sources along with additional information (either a flag or complementary parameters) as tables that are made available in the Gaia archive. We also identify 15 740 bone fide carbon stars and 5863 solar analogues, and provide the first homogeneous set of stellar parameters of the SPSS sample. We demonstrate some applications of these samples in different astrophysical contexts. We use a subset of the OBA sample to illustrate its usefulness in analysing the Milky Way rotation curve. We then use the properties of the FGKM stars to analyse known exoplanet systems. We also analyse the ages of some unseen UCD-companions to the FGKM stars. We additionally predict the colours of the Sun in various passbands (Gaia, 2MASS, WISE) using the solar-analogue sample. Conclusions. Gaia DR3 contains a wealth of new high-quality astrophysical parameters for the community to exploit.
Gaia Data Release 3. Apsis. III. Non-stellar content and source classification
(EDP Sciences, 2023-06-16) Delchambre, L.; Bailer Jones, C. A. L.; Bellas Velidis, I.; Drimmel, R.; Garabato, D.; Sarro Baro, Luis Manuel; https://orcid.org/0000-0003-2559-408X; https://orcid.org/0009-0004-7385-9198; https://orcid.org/0000-0002-1777-5502; https://orcid.org/0000-0002-7133-6623
Context. As part of the third Gaia Data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b|> 5°. Results.Gaia DR3 includes 1591 million sources with DSC classifications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 deg2 where the extinction is evaluated by TGE. Conclusions. Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while UGC redshifts have a mean error of 0.008 ± 0.037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
Gaia Data Release 3. Exploring and mapping the diffuse interstellar band at 862 nm
(EDP Sciences, 2023-06-16) Schultheis, M.; Zhao, He; Marshall, D. J.; Zhao, He; Sarro Baro, Luis Manuel
Context. Diffuse interstellar bands (DIBs) are common interstellar absorption features in spectroscopic observations but their origins remain unclear. DIBs play an important role in the life cycle of the interstellar medium (ISM) and can also be used to trace Galactic structure. Aims. Here, we demonstrate the capacity of the Gaia-Radial Velocity Spectrometer (RVS) in Gaia DR3 to reveal the spatial distribution of the unknown molecular species responsible for the most prominent DIB at 862 nm in the RVS passband, exploring the Galactic ISM within a few kiloparsecs from the Sun. Methods. The DIBs are measured within the GSP-Spec module using a Gaussian profile fit for cool stars and a Gaussian process for hot stars. In addition to the equivalent widths and their uncertainties, Gaia DR3 provides their characteristic central wavelength, width, and quality flags. Results. We present an extensive sample of 476 117 individual DIB measurements obtained in a homogeneous way covering the entire sky. We compare spatial distributions of the DIB carrier with interstellar reddening and find evidence that DIB carriers are present in a local bubble around the Sun which contains nearly no dust. We characterised the DIB equivalent width with a local density of 0.19 ± 0.04 Å kpc−1 and a scale height of 98.60+11.10 −8.46 pc. The latter is smaller than the dust scale height, indicating that DIBs are more concentrated towards the Galactic plane. We determine the rest-frame wavelength with unprecedented precision (λ0 = 8620.86 ±0.019 Å in air) and reveal a remarkable correspondence between the DIB velocities and the CO gas velocities, suggesting that the 862 nm DIB carrier is related to macro-molecules. Conclusions. We demonstrate the unique capacity of Gaia to trace the spatial structure of the Galactic ISM using the 862 nm DIB.
Gaia Data Release 3. External calibration of BP/RP low-resolution spectroscopic data
(EDP Sciences, 2023-06-16) Montegriffo, P.; Angeli, Francesca De; Andrae, Rene; Riello, Marco; Pancino, Elena; Sarro Baro, Luis Manuel; https://orcid.org/0000-0001-5013-5948; https://orcid.org/0000-0003-1879-0488; https://orcid.org/0000-0001-8006-6365; https://orcid.org/0000-0002-3134-0935; https://orcid.org/0000-0003-0788-5879
Context.Gaia Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the European Space Agency (ESA) Gaia satellite during the first 34 months of its operational phase (the same period covered by Gaia early Data Release 3; Gaia EDR3). Low-resolution spectra for 220 million sources are one of the important new data products included in this release. Aims. In this paper, we focus on the external calibration of low-resolution spectroscopic content, describing the input data, algorithms, data processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the catalogue. Methods. We calibrated an instrument model to relate mean Gaia spectra to the corresponding spectral energy distributions (SEDs) using an extended set of calibrators: this includes modelling of the instrument dispersion relation, transmission, and line spread functions. Optimisation of the model is achieved through total least-squares regression, accounting for errors in Gaia and external spectra. Results. The resulting instrument model can be used for forward modelling of Gaia spectra or for inverse modelling of externally calibrated spectra in absolute flux units. Conclusions. The absolute calibration derived in this paper provides an essential ingredient for users of BP/RP spectra. It allows users to connect BP/RP spectra to absolute fluxes and physical wavelengths.
Gaia Data Release 3. Mapping the asymmetric disc of the Milky Way
(EDP Sciences, 2023-06-16) Drimmel, R.; Romero Gómez, Mercé; Chemin, L.; Ramos, Pau; Sarro Baro, Luis Manuel
Context. With the most recent Gaia data release, the number of sources with complete 6D phase space information (position and velocity) has increased to well over 33 million stars, while stellar astrophysical parameters are provided for more than 470 million sources, and more than 11 million variable stars are identified. Aims. Using the astrophysical parameters and variability classifications provided in Gaia DR3, we selected various stellar populations to explore and identify non-axisymmetric features in the disc of the Milky Way in configuration and velocity space. Methods. Using more about 580 000 sources identified as hot OB stars, together with 988 known open clusters younger than 100 Myr, we mapped the spiral structure associated with star formation 4−5 kpc from the Sun. We selected over 2800 Classical Cepheids younger than 200 Myr that show spiral features extending as far as 10 kpc from the Sun in the outer disc. We also identified more than 8.7 million sources on the red giant branch (RGB), of which 5.7 million have line-of-sight velocities. This later sample allows the velocity field of the Milky Way to be mapped as far as 8 kpc from the Sun, including the inner disc. Results. The spiral structure revealed by the young populations is consistent with recent results using Gaia EDR3 astrometry and source lists based on near-infrared photometry, showing the Local (Orion) Arm to be at least 8 kpc long, and an outer arm consistent with what is seen in HI surveys, which seems to be a continuation of the Perseus arm into the third quadrant. The subset of RGB stars with velocities clearly reveals the large-scale kinematic signature of the bar in the inner disc, as well as evidence of streaming motions in the outer disc that might be associated with spiral arms or bar resonances. A local comparison of the velocity field of the OB stars reveals similarities and differences with the RGB sample. Conclusions. This cursory study of Gaia DR3 data shows there is a rich bounty of kinematic information to be explored more deeply, which will undoubtedly lead us to a clearer understanding of the dynamical nature of the non-axisymmetric structures of the Milky Way.
Gaia Data Release 3. Non-stellar content and source classification
(EDP Sciences, 2023-06-16) Delchambre, L.; Bailer Jones, C. A. L.; Bellas Velidis, I.; Sarro Baro, Luis Manuel
Context. As part of the third Gaia Data Release, we present the contributions of the non-stellar and classifcation modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsible for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their objectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A subset of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classfication. The Quasi Stellar Object Classifier (QSOC) and the Unresolved Galaxy Classfier (UGC) determine the redshifts of the sources classfied as quasar and galaxy by the DSC module. Finally, the Total Galactic Extinction (TGE) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b| > 5◦. Results. Gaia DR3 includes 1591 million sources with DSC classications; 56 million sources to which the OA clustering is applied; 1.4 million sources with redshift estimates from UGC; 6.4 million sources with QSOC redshift; and 3.1 million level 9 HEALPixes of size 0.013 deg2 where the extinction is evaluated by TGE. Conclusions. Validation shows that results are in good agreement with values from external catalogues; for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while UGC redshifts have a mean error of 0.008 ± 0.037 if evaluated on a clean set of spectra. An internal validation of the OA results further shows that 30 million sources are located in high confidence regions of the clustering map.
Gaia Data Release 3. Processing and validation of BP/RP low-resolution spectral data
(EDP Sciences, 2023-06-16) Angeli, Francesca De; Weiler, Michael; Montegriffo, P.; Evans, Dafydd Wyn; Sarro Baro, Luis Manuel; https://orcid.org/0000-0003-1879-0488; https://orcid.org/0000-0002-3007-3927; https://orcid.org/0000-0001-5013-5948; https://orcid.org/0000-0002-6685-5998
Context. Blue (BP) and Red (RP) Photometer low-resolution spectral data are one of the exciting new products in Gaia Data Release 3 (Gaia DR3). These data have also been used to derive astrometry and integrated photometry in Gaia Early Data Release 3 and astrophysical parameters and Solar System object reflectance spectra in Gaia DR3. Aims. In this paper, we give an overview of the processing techniques that allow raw satellite data of multiple transits per source to be converted into combined spectra calibrated to an internal reference system, resulting in low-resolution BP and RP mean spectra. We describe how we overcome challenges due to the complexity of the on-board instruments and to the various observation strategies. Furthermore, we show highlights from our scientific validation of the results. This work covers the internal calibration of BP/RP spectra to a self-consistent mean instrument, while the calibration of the BP/RP spectra to the absolute reference system of physical flux and wavelength is covered by one of the accompanying Gaia DR3 papers. Methods. We calibrate about 65 billion individual transit spectra onto the same mean BP/RP instrument through a series of calibration steps, including background subtraction, calibration of the CCD geometry, and an iterative procedure for the calibration of CCD efficiency as well as variations of the line-spread function and dispersion across the focal plane and in time. The calibrated transit spectra are then combined for each source in terms of an expansion into continuous basis functions. We discuss the configuration of these basis functions. Results. Time-averaged mean spectra covering the optical to near-infrared wavelength range [330, 1050] nm are published for approximately 220 million objects. Most of these are brighter than G = 17.65 but some BP/RP spectra are published for sources down to G = 21.43. Their signal-to-noise ratio (S/N) varies significantly over the wavelength range covered, and with magnitude and colour of the observed objects, with sources around G = 15 having a S/N above 100 in some wavelength ranges. The top-quality BP/RP spectra are achieved for sources with magnitudes 9 < G < 12, with S/N reaching 1000 in the central part of the RP wavelength range. Scientific validation suggests that the internal calibration was generally successful. However, there is some evidence for imperfect calibrations at the bright end G < 11, where calibrated BP/RP spectra can exhibit systematic flux variations that exceed their estimated flux uncertainties. We also report that, due to long-range noise correlations, BP/RP spectra can exhibit wiggles when sampled in pseudo-wavelength. Conclusions. The Gaia DR3 data products are the expansion coefficients and corresponding covariance matrices for BP and RP separately. Users are encouraged to work with the data in this format, with full covariance information showing that correlations between coefficients are typically very low. Documentation and instructions on how to access and use BP/RP spectral data from the archive are also provided.
Gaia Data Release 3. Pulsations in main sequence OBAF-type stars
(EDP Sciences, 2023-06-16) Ridder, Joris De; Ripepi, Vincenzo; Aerts, C.; Palaversa, Lovro; Sarro Baro, Luis Manuel
Context. The third Gaia data release provides photometric time series covering 34 months for about 10 million stars. For many of those stars, a characterisation in Fourier space and their variability classification are also provided. This paper focuses on intermediate- to high-mass (IHM) main sequence pulsators (M ≥ 1.3 M) of spectral types O, B, A, or F, known as βCep, slowly pulsating B (SPB), δ Sct, and γ Dor stars. These stars are often multi-periodic and display low amplitudes, making them challenging targets to analyse with sparse time series. Aims. We investigate the extent to which the sparse Gaia DR3 data can be used to detect OBAF-type pulsators and discriminate them from other types of variables. We aim to probe the empirical instability strips and compare them with theoretical predictions. The most populated variability class is that of the δ Sct variables. For these stars, we aim to confirm their empirical period-luminosity (PL) relation, and verify the relation between their oscillation amplitude and rotation. Methods. All datasets used in this analysis are part of the Gaia DR3 data release. The photometric time series were used to perform a Fourier analysis, while the global astrophysical parameters necessary for the empirical instability strips were taken from the Gaia DR3 gspphot tables, and the v sin i data were taken from the Gaia DR3 esphs tables. The δ Sct PL relation was derived using the same photometric parallax method as the one recently used to establish the PL relation for classical Cepheids using Gaia data. Results. We show that for nearby OBAF-type pulsators, the Gaia DR3 data are precise and accurate enough to pinpoint them in the Hertzsprung Russell (HR) diagram. We find empirical instability strips covering roader regions than theoretically predicted. In particular, our study reveals the presence of fast rotating gravity-mode pulsators outside the strips, as well as the co-existence of rotationally modulated variables inside the strips as reported before in the literature. We derive an extensive period–luminosity relation for δ Sct stars and provide evidence that the relation features different regimes depending on the oscillation period. We demonstrate how stellar rotation attenuates the amplitude of the dominant oscillation mode of δ Sct stars. Conclusions. The Gaia DR3 time-series photometry already allows for the detection of the dominant (non-)radial oscillation mode in about 100 000 intermediate- and high-mass dwarfs across the entire sky. This detection capability will increase as the time series becomes longer, allowing the additional delivery of frequencies and amplitudes of secondary pulsation modes.

Examinando por Autor "Sarro Baro, Luis Manuel"

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