Search

We characterize the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one and we also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (rmag ≤ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength r0 and slope γ by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterized and validated with the spectroscopic data of Survey Validation. © 2021 The Author(s)., PZ, OR-M, SC, PN, and CB acknowledge support from the Science Technology Facilities Council through ST/P000541/1 andST/T000244/1. OR-M is supported by the Mexican National Council of Science and Technology (CONACyT) through grant No. 297228/440775 and funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374. JM gratefully acknowledges support from the U.S. Department of Energy, Office of Science, Office of High Energy Physics under Award Number DESC0020086 and from the National Science Foundation under grant AST-1616414. Authors want to thank the GAMA collaboration for early access to GAMA DR4 data for this work. Some of the results in this paper have been derived using the healpy and HEALPIX package. We acknowledge the usage of the HyperLeda database (http://leda.univ-lyon1.fr).This work also made extensive use of the NASA Astrophysics Data System and of the astro-ph preprint archive at arXiv.org. This work used the DiRAC@Durham facility managed by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). The equipment was funded by BEIS capital funding via STFC capital grants ST/K00042X/1, ST/P002293/1, and ST/R002371/1, Durham University and STFC operations grant ST/R000832/1. DiRAC is part of the National e-Infrastructure. This research used resources of the National Energy Research Scientific Computing Center (NERSC). NERSC is a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. This research is supported by the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy under Contract No. DE-AC02-05CH1123, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract; additional support for DESI is provided by the U.S. National Science Foundation, Division of Astronomical Sciences under Contract No. AST-0950945 to the NSF’s National Optical-Infrared Astronomy Research Laboratory; the Science and Technologies Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico; the Ministry of Economy of Spain, and by the DESI Member Institutions. The authors are honored to be permitted to conduct astronomical research on Iolkam Du’ag (Kitt Peak), a mountain with particular significance to the Tohono O’odham Nation., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

This paper presents the results of the photometric CCD observations of the NEA (2100) Ra-Shalom carried out on August 24–29, 2019, at the 1-m telescope of the Sanglokh Observatory of the Institute of Astrophysics, National Academy of Sciences of the Republic of Tajikistan. The rotation period P = 19.8 ± 0.1 h was determined. Composite light curves were plotted in the photometric BVR bands; the brightness amplitude ΔV = 0.61m ± 0.05m and the average values of the color indices B–V = 0.75m ± 0.05m, V–R = 0.40m ± 0.02m were determined. Variations in the color indices with rotation period are within the measurement errors, which indicates that the reflectivity of Ra-Shalom’s surface is uniform. The absolute stellar magnitude of the asteroid is 15.91m ± 0.10m. The ratio of the asteroid’s axes a/b = 1.75.

In order to meet the ground test requirements of star sensors and solve the problem of the non-linearity between the apparent magnitude and the total grey value of the stars encountered in actual m...

We present a deep learning model to predict the r-band bulge-to-total light ratio (B/T) of nearby galaxies using their multi-band JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample of galaxies with reliable decomposition into the bulge and disk components. The existing approaches to estimate the B/T use galaxy light-profile modelling to find the best fit. This method is computationally expensive, prohibitively so for large samples of galaxies, and requires a significant amount of human intervention. Machine learning models have the potential to overcome these shortcomings. In our CNN model, for a test set of 20000 galaxies, 85.7 per cent of the predicted B/T values have absolute error (AE) less than 0.1. We see further improvement to 87.5 per cent if, while testing, we only consider brighter galaxies (with r-band apparent magnitude < 17) with no bright neighbours. Our model estimates B/T for the 20000 test galaxies in less than a minute. This is a significant improvement in inference time from the conventional fitting pipelines, which manage around 2-3 estimates per minute. Thus, the proposed machine learning approach could potentially save a tremendous amount of time, effort and computational resources while predicting B/T reliably, particularly in the era of next-generation sky surveys such as the Legacy Survey of Space and Time (LSST) and the Euclid sky survey which will produce extremely large samples of galaxies., 11 pages, 3 tables, 8 figures, accepted for publication in MNRAS

Red supergiants are the most common final evolutionary stage of stars that have initial masses between 8 and 35 times that of the Sun1. During this stage, which lasts roughly 100,000 years1, red supergiants experience substantial mass loss. However, the mechanism for this mass loss is unknown2. Mass loss may affect the evolutionary path, collapse and future supernova light curve3 of a red supergiant, and its ultimate fate as either a neutron star or a black hole4. From November 2019 to March 2020, Betelgeuse—the second-closest red supergiant to Earth (roughly 220 parsecs, or 724 light years, away)5,6—experienced a historic dimming of its visible brightness. Usually having an apparent magnitude between 0.1 and 1.0, its visual brightness decreased to 1.614 ± 0.008 magnitudes around 7–13 February 20207—an event referred to as Betelgeuse’s Great Dimming. Here we report high-angular-resolution observations showing that the southern hemisphere of Betelgeuse was ten times darker than usual in the visible spectrum during its Great Dimming. Observations and modelling support a scenario in which a dust clump formed recently in the vicinity of the star, owing to a local temperature decrease in a cool patch that appeared on the photosphere. The directly imaged brightness variations of Betelgeuse evolved on a timescale of weeks. Our findings suggest that a component of mass loss from red supergiants8 is inhomogeneous, linked to a very contrasted and rapidly changing photosphere. The southern hemisphere of Betelgeuse during its Great Dimming was an order of magnitude darker than usual, owing to a cool patch on the photosphere and associated dust formation.

By computer simulations, the behavior of meteoroids when entering the Earth's atmosphere is studied. Given the initial mass and velocity parameters, the Modified Euler Integration numerical method is applied to solve the equations that describe the behavior of falling meteoroids. The numerical results obtained through arbitrary values inserted in the simulation showed good agreement when compared with the observables selected from the International Astronomical Union (IAU) database, but they show that improvements in accuracy can be made in future versions of the algorithm. Mediante simulaciones por ordenador se estudia el comportamiento de los meteoroides al entrar en la atmósfera terrestre. Dados los parámetros iniciales de masa y velocidad, se aplica el método numérico de Integración de Euler Modificada para resolver las ecuaciones que describen el comportamiento de la caída de meteoroides. Los resultados numéricos obtenidos a través de valores arbitrarios insertados en la simulación mostraron una buena concordancia cuando se compararon con los observables seleccionados de la base de datos de la International Astronomical Union (IAU), pero muestran que se pueden realizar mejoras en la precisión en futuras versiones del algoritmo. Através de simulações computacionais estuda-se o comportamento de meteoroides ao adentrar a atmosfera terrestre. Dados os parâmetros massa e velocidade iniciais aplica-se o método numérico de Integração de Euler Modificado para resolver as equações que descrevem a o comportamento de meteoroides em queda. Os resultados numéricos obtidos através de valores arbitrários inseridos na simulação mostraram boa concordância quando comparados com os observáveis selecionados da base de dados da International Astronomical Union (IAU), porém evidenciam que aperfeiçoamentos na precisão podem ser realizados em versões futuras do algoritmo.

We present optical and ultraviolet photometry, as well as optical spectra, for the type II supernova (SN) 2015bf. Our observations cover the phases from ∼2 to ∼200 d after explosion. The first spectrum is characterized by a blue continuum with a blackbody temperature of ∼24 000 K and flash-ionized emission lines. After about 1 week, the spectra of SN 2015bf evolve like those of a regular SN II. From the luminosity of the narrow emission component of H α, we deduce that the mass-loss rate is larger than ${\sim}3.7\times 10^{-3}\, {\rm M_\odot \, yr^{-1}}$. The disappearance of the flash features in the first week after explosion indicates that the circumstellar material is confined within ∼6 × 1014 cm. Thus, we suggest that the progenitor of SN 2015bf experienced violent mass loss shortly before the supernova explosion. The multiband light curves show that SN 2015bf has a high peak luminosity with an absolute visual magnitude MV = −18.11 ± 0.08 mag and a fast post-peak decline with a V-band decay of 1.22 ± 0.09 mag within ∼50 d after maximum light. Moreover, the R-band tail luminosity of SN 2015bf is fainter than that of SNe II with similar peak by 1–2 mag, suggesting a small amount of 56Ni (${\sim}0.009\, {\rm M_\odot }$) synthesized during the explosion. Such a low nickel mass indicates that the progenitor of SN 2015bf could be a super-asymptotic-giant-branch star that collapsed owing to electron capture.