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Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5$\sigma$ point-source depth of $g$ = 24.3, $r$ = 23.9, $i$ = 23.5, and $z$ = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of $-0.0013$, a scatter of $0.0293$, and an outlier fraction of $5.1\%$. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters. We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes., Comment: 22 pages, 14 figures

We present a new constraint on the Hubble constant ($H_0$) from the standard dark siren method using a sample of $5$ well-covered gravitational waves (GW) alerts reported during the first part of the fourth LIGO/Virgo/KAGRA observing run and with $3$ updated standard dark sirens from third observation run in combination the previous constraints from the first three runs. Our methodology relies on the galaxy catalogue method alone. We use a Deep Learning method to derive the full probability density estimation of photometric redshifts using the Legacy Survey catalogues. We add the constraints from well localized Binary Black Hole mergers to the sample of standard dark sirens analysed in our previous work. We combine the $H_0$ posterior for $5$ new standard sirens with other $10$ previous events (using the most recent available data for the 5 novel events and updated 3 previous posteriors from O3), finding $H_0 = 70.4^{+13.6}_{-11.7}~{\rm km~s^{-1}~Mpc^{-1}}$ (68\% Confidence interval) with the catalogue method only. This result represents an improvement of $\sim 23\%$ comparing the new $15$ dark siren constrain with the previous $10$ dark siren constraint and a reduction in uncertainty of $\sim 40\%$ from the combination of $15$ dark and bright sirens compared with the GW170817 bright siren alone. The combination of dark and bright siren GW170817 with recent jet constraints yields $H_0$ of $68.0^{+4.4}_{-3.8}~{\rm km~s^{-1}~Mpc^{-1}}$, a $\sim 6\%$ precision from Standard Sirens, reducing the previous constraint uncertainty by $\sim 10\%$ ., Comment: 18 pages, 11 figures and 2 tables. Article accepted for publication in MNRAS

The current and next observation seasons will detect hundreds of gravitational waves (GWs) from compact binary systems coalescence at cosmological distances. When combined with independent electromagnetic measurements, the source redshift will be known, and we will be able to obtain precise measurements of the Hubble constant $H_0$ via the distance-redshift relation. However, most observed mergers are not expected to have electromagnetic counterparts, which prevents a direct redshift measurement. In this scenario, one of the possibilities is to use the dark sirens method that statistically marginalizes over all the potential host galaxies within the GW location volume to provide a probabilistic redshift to the source. Here we presented $H_{0}$ measurements using two new dark sirens compared to previous analyses using DECam data, GW190924$\_$021846 and GW200202$\_$154313. The photometric redshifts of the possible host galaxies of these two events are acquired from the DECam Local Volume Exploration Survey (DELVE) carried out on the Blanco telescope at Cerro Tololo in Chile. The combination of the $H_0$ posterior from GW190924$\_$021846 and GW200202$\_$154313 together with the bright siren GW170817 leads to $H_{0} = 68.84^{+15.51}_{-7.74}\, \rm{km/s/Mpc}$. Including these two dark sirens improves the 68% confidence interval (CI) by 7% over GW170817 alone. This demonstrates that the inclusion of well-localized dark sirens in such analysis improves the precision with which cosmological measurements can be made. Using a sample containing 10 well-localized dark sirens observed during the third LIGO/Virgo observation run, we determine a measurement of $H_{0} = 76.00^{+17.64}_{-13.45}\, \rm{km /s/Mpc}$., Comment: v2: minor corrections and references added

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. It achieves single-point photometric redshifts with scatter ($\sigma_\text{NMAD}$) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r-auto magnitudes between 16 and 21., Comment: 49 pages, 9 figures. Accepted for publication in Astronomy and Computing. Data products are available in https://splus.cloud/ website

The Southern Photometric Local Universe Survey (S-PLUS) is an ongoing survey of $\sim$9300 deg$^2$ in the southern sky in a 12-band photometric system. This paper presents the second data release (DR2) of S-PLUS, consisting of 514 tiles covering an area of 950 deg$^2$. The data has been fully calibrated using a new photometric calibration technique suitable for the new generation of wide-field multi-filter surveys. This technique consists of a $\chi^2$ minimisation to fit synthetic stellar templates to already calibrated data from other surveys, eliminating the need for standard stars and reducing the survey duration by $\sim$15\%. We compare the template-predicted and S-PLUS instrumental magnitudes to derive the photometric zero-points (ZPs). We show that these ZPs can be further refined by fitting the stellar templates to the 12 S-PLUS magnitudes, which better constrain the models by adding the narrow-band information. We use the STRIPE82 region to estimate ZP errors, which are $\lesssim10$ mmags for filters J0410, J0430, $g$, J0515, $r$, J0660, $i$, J0861 and $z$; $\lesssim 15$ mmags for filter J0378; and $\lesssim 25$ mmags for filters $u$ and J0395. We describe the complete data flow of the S-PLUS/DR2 from observations to the final catalogues and present a brief characterisation of the data. We show that, for a minimum signal-to-noise threshold of 3, the photometric depths of the DR2 range from 19.9 mag to 21.3 mag (measured in Petrosian apertures), depending on the filter. The S-PLUS DR2 can be accessed from the website: https://splus.cloud}{https://splus.cloud., Comment: 29 pages, 26 figures, 7 tables

Aims. The derivation of spectroscopic parameters for M dwarf stars is very important in the fields of stellar and exoplanet characterization. The goal of this work is the creation of an automatic computational tool, able to derive quickly and reliably the T$_{\mathrm{eff}}$ and [Fe/H] of M dwarfs by using their optical spectra, that can be obtained by different spectrographs with different resolutions. Methods. ODUSSEAS (Observing Dwarfs Using Stellar Spectroscopic Energy-Absorption Shapes) is based on the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and on the use of the machine learning Python package "scikit-learn" for predicting the stellar parameters. Results. We show that our tool is able to derive parameters accurately and with high precision, having precision errors of ~30 K for T$_{\mathrm{eff}}$ and ~0.04 dex for [Fe/H]. The results are consistent for spectra with resolutions between 48000 and 115000 and SNR above 20., Comment: 16 pages, 14 figures, Accepted by A&A

Context. Being the most numerous and oldest stars in the galaxy, M dwarfs are objects of great interest for exoplanet searches. The presence of molecules in their atmosphere complicates our understanding of their atmospheric properties. But great advances have recently been made in the modeling of M dwarfs due to the revision of solar abundances. Aims. We aim to determine stellar parameters of M dwarfs using high resolution spectra (R = 90 000) simultaneously in the visible and the near-infrared. The high resolution spectra and broad wavelength coverage provide an unique opportunity to understand the onset of dust and cloud formation at cool temperatures. Furthermore, this study will help in understanding the physical processes which occur in a cool atmospheres, particularly, the redistribution of energy from the optical to the near-infrared. Methods. The stellar parameters of M dwarfs in our sample have been determined by comparing the high resolution spectra both in the optical and in the near-infrared simultaneously observed by CARMENES with the synthetic spectra obtained from the BT-Settl model atmosphere. The detailed spectral synthesis of these observed spectra both in the optical and in the near-infrared helps to understand the missing continuum opacity. Results. For the first time, we derive fundamental stellar parameters of M dwarfs using the high resolution optical and near-infrared spectra simultaneously. We determine Teff , log g and [M/H] for 292 M dwarfs of spectral type M0 to M9, where the formation of dust and clouds are important. The derived Teff for the sample ranges from 2300 to 4000 K, values of log g ranges from 4.5 geq log g leq 5.5 and the resulting metallicity ranges from -0.5 geq [M/H] leq +0.5. We have also explored the possible differences in Teff , log g and [M/H] by comparing them with other studies of the same sample of M dwarfs., Comment: 13 pages, 6 figures, 2 tables, accepted for publication in A&A

The VVV survey has allowed for an unprecedented number of multi-epoch observations of the southern Galactic plane. In a recent paper,13 massive young stellar objects(MYSOs) have already been identified within the highly variable(\Delta Ks > 1 mag) YSO sample of another published work.This study aims to understand the general nature of variability in MYSOs.We present the first systematic study of variability in a large sample of candidate MYSOs.We examined the data for variability of the putative driving sources of all known Spitzer EGOs and bright 24 \mu m sources coinciding with the peak of 870 \mu m detected ATLASGAL clumps, a total of 718 targets. Of these, 190 point sources (139 EGOs and 51 non-EGOs) displayed variability (IQR > 0.05, \Delta Ks > 0.15 mag). Light-curves(LCs) have been sub-classified into eruptive, dipper, fader, short-term-variable and long-period variable-YSO categories.Lomb-Scargle periodogram analysis of periodic LCs was carried out. 1 - 870 \mu m spectral energy distributions of the variable sources were fitted with YSO models to obtain representative properties. 41% of the variable sources are represented by > 4Msun objects, and only 6% by > 8Msun objects.The highest-mass objects are mostly non-EGOs,deeply embedded.By placing them on the HR diagram we show that most lower mass,EGO type objects are concentrated on the putative birth-line position, while the luminous non-EGO type objects group around the ZAMS track.Some of the most luminous far infrared sources in the massive clumps and infrared quiet driving sources of EGOs have been missed out by this study owing to an uniform sample selection method.A high rate of detectable variability in EGO targets (139 out of 153 searched) implies that near-infrared variability in MYSOs is closely linked to the accretion phenomenon and outflow activity., Comment: 60 pages, 47 figures. Accepted for publication in Astronomy and Astrophysics

In the era of vast spectroscopic surveys focusing on Galactic stellar populations, astronomers want to exploit the large quantity and good quality of data to derive their atmospheric parameters without losing precision from automatic procedures. In this work, we developed a new spectral package, FASMA, to estimate the stellar atmospheric parameters (namely effective temperature, surface gravity, and metallicity) in a fast and robust way. This method is suitable for spectra of FGK-type stars in medium and high resolution. The spectroscopic analysis is based on the spectral synthesis technique using the radiative transfer code, MOOG. The line list is comprised of mainly iron lines in the optical spectrum. The atomic data are calibrated after the Sun and Arcturus. We use two comparison samples to test our method, i) a sample of 451 FGK-type dwarfs from the high resolution HARPS spectrograph, and ii) the Gaia-ESO benchmark stars using both high and medium resolution spectra. We explore biases in our method from the analysis of synthetic spectra covering the parameter space of our interest. We show that our spectral package is able to provide reliable results for a wide range of stellar parameters, different rotational velocities, different instrumental resolutions, and for different spectral regions of the VLT-GIRAFFE spectrographs, used among others for the Gaia-ESO survey. FASMA estimates stellar parameters in less than 15 min for high resolution and 3 min for medium resolution spectra. The complete package is publicly available to the community., Comment: 35 pages, accepted in MNRAS

M dwarfs are an important source of information when studying and probing the lower end of the Hertzsprung-Russell (HR) diagram, down to the hydrogen-burning limit. Being the most numerous and oldest stars in the galaxy, they carry fundamental information on its chemical history. The presence of molecules in their atmospheres, along with various condensed species, complicates our understanding of their physical properties and thus makes the determination of their fundamental stellar parameters more challenging and difficult. The aim of this study is to perform a detailed spectroscopic analysis of the high-resolution H-band spectra of M dwarfs in order to determine their fundamental stellar parameters and to validate atmospheric models. The present study will also help us to understand various processes, including dust formation and depletion of metals onto dust grains in M dwarf atmospheres. The high spectral resolution also provides a unique opportunity to constrain other chemical and physical processes that occur in a cool atmosphere The high-resolution APOGEE spectra of M dwarfs, covering the entire H-band, provide a unique opportunity to measure their fundamental parameters. We have performed a detailed spectral synthesis by comparing these high-resolution H-band spectra to that of the most recent BT-settl model and have obtained fundamental parameters such as effective temperature, surface gravity, and metallicity (Teff, log g and [Fe/H]) respectively., Comment: 15 pages, 10 figures, accepted for publication in A&A

Context: Thanks to the importance that the star-planet relation has to our understanding of the planet formation process, the precise determination of stellar parameters for the ever increasing number of discovered extrasolar planets is of great relevance. Furthermore, precise stellar parameters are needed to fully characterize the planet properties. It is thus important to continue the efforts to determine, in the most uniform way possible, the parameters for stars with planets as new discoveries are announced. Aims: In this paper we present new precise atmospheric parameters for a sample of 50 stars with planets. The results are presented in the catalogue: SWEET-Cat. Methods: Stellar atmospheric parameters and masses for the 50 stars were derived assuming local thermodynamic equilibrium (LTE) and using high-resolution and high signal-to-noise spectra. The methodology used is based on the measurement of equivalent widths with ARES2 for a list of iron lines. The line abundances were derived using MOOG. We then used the curve of growth analysis to determine the parameters. We implemented a new minimization procedure which significantly improves the computational time. Results: The stellar parameters for the 50 stars are presented and compared with previously determined literature values. For SWEET-Cat, we compile values for the effective temperature, surface gravity, metallicity, and stellar mass for almost all the planet host stars listed in the Extrasolar Planets Encyclopedia. This data will be updated on a continuous basis. The data can be used for statistical studies of the star-planet correlation, and for the derivation of consistent properties for known planets., Comment: 12 pages, 7 figures, accepted A&A

The ever-growing number of large spectroscopic survey programs has increased the importance of fast and reliable methods with which to determine precise stellar parameters. Some of these methods are highly dependent on correct spectroscopic calibrations. The goal of this work is to obtain a new spectroscopic calibration for a fast estimate of Teff and [Fe/H] for a wide range of stellar spectral types. We used spectra from a joint sample of 708 stars, compiled from 451 FGK dwarfs and 257 GK-giant stars. We used homogeneously determined spectroscopic stellar parameters to derive temperature calibrations using a set of selected EW line-ratios, and [Fe/H] calibrations using a set of selected FeI lines. We have derived 322 EW line-ratios and 100 FeI lines that can be used to compute Teff and [Fe/H], respectively. We show that these calibrations are effective for FGK dwarfs and GK-giant stars in the following ranges: 4500 K < Teff < 6500 K , 2.5 < logg < 4.9 dex, and -0.8 < [Fe/H] < 0.5 dex. The new calibration has a standard deviation of 74 K for Teff and 0.07 dex for [Fe/H]. We use four independent samples of stars to test and verify the new calibration, a sample of 56 giant stars, a sample composed of Gaia FGK benchmark stars, a sample of 36 GK-giant stars of the DR1 of the Gaia-ESO survey, and a sample of 582 FGK-dwarf stars. We also provide a new computer code, GeTCal, for automatically producing new calibration files based on any new sample of stars., Comment: Accepted by A&A for publication, 8 pages, 9 figures