Sanjib Sharma

Mapping the local and distant Universe is key to our understanding of it. For decades, the Sloan Digital Sky Survey (SDSS) has made a concerted effort to map millions of celestial objects to constrain the physical processes that govern our Universe. The most recent and fifth generation of SDSS (SDSS-V) is organized into three scientific “mappers”: the Milky Way Mapper, which aims to chart the various components of the Milky Way and constrain its formation and assembly; the Black Hole Mapper, which focuses on understanding supermassive black holes in distant galaxies across the Universe; and the Local Volume Mapper, which uses integral field spectroscopy to map the ionized interstellar medium in the Local Group. This paper describes the scope and content for the nineteenth data release (DR19) of SDSS, which is the most substantial to date in SDSS-V. DR19 is the first to contain data from all three mappers. Additionally, we also describe nine value-added catalogs that enhance the science that can be conducted with the SDSS-V data. Finally, we discuss how to access SDSS DR19 and provide illustrative examples and tutorials.

After carbon and oxygen, ²²Ne is the most abundant element in white dwarf (WD) interiors. As C/O WDs crystallize, they are predicted to go through a distillation process in the central layers if they have a sufficiently high ²²Ne mass fraction of ≳2.5%. Observational evidence for distillation comes from an overdensity of WDs on the Q-branch in Gaia color–magnitude diagrams, which indicates that ∼6% of massive WDs are delayed in their cooling by as much as ∼10 Gyr. However, it is unclear how these stars end up with such a high concentration of ²²Ne and if a significant fraction of the more common average-mass WDs go through distillation. We argue that a significant metal-rich stellar population in the solar neighborhood should lead to distilled WDs, without requiring a binary merger. We use MESA along with the carbon, nitrogen, and oxygen abundances derived from high-resolution spectroscopy of stars included in the Hypatia catalog to predict the ²²Ne mass fraction in their descendant WDs. We find that 0.6%–2.5% of the WDs in the solar neighborhood have sufficient ²²Ne in their interiors to go through multi-Gyr cooling delays, which could significantly inflate their numbers in the observed samples. Hence, ²²Ne distillation and long-lived habitable zones around WDs should be relatively common in the solar neighborhood. We also use a Galactic model to predict the fraction of WDs that go through distillation as a function of Galactocentric distance. The fraction of distilled WDs is ∼2%–8% near the Galactic center and declines steadily toward the outer disk.

The Galactic Bulge Time-Domain Survey (GBTDS) of the Roman Space Telescope will take high-cadence data of the Galactic bulge. We investigate the asteroseismic potential of this survey for red giants. We simulate the detectability of global asteroseismic frequencies, ν max and Δν, by modifying Kepler data to match nominal GBTDS observing strategies, considering different noise models, observing cadences, and detection algorithms. Our baseline case, using conservative assumptions, consistently leads to asteroseismic ν max detection probabilities above 80% for red clump and red giant branch (RGB) stars brighter than the 16th magnitude in Roman’s F146 filter. We then inject these detection probabilities into a Galaxia model of the bulge to estimate asteroseismic yields. For our nominal case, we detect 290,000 stars in total, with 185,000 detections in the bulge. Different assumptions give bulge yields from 135,000 to 349,000 stars. For stars with measured ν max , we find that we can recover Δν in 21%–42% of red clump stars, and 69%–92% of RGB stars. The expected yield and stellar parameter precision we predict for Roman asteroseismology promise to characterize planet-hosting stellar populations and to resolve questions regarding the formation history of the bulge.

We resolve the multiple images of the binary-lens microlensing event ASASSN-22av using the GRAVITY instrument of the Very Large Telescope Interferometer (VLTI). The light curves show weak binary-lens perturbations, complicating the analysis, but the joint modeling with the VLTI data breaks several degeneracies, arriving at a strongly favored solution. Thanks to precise measurements of the angular Einstein radius θ _E = 0.724 ± 0.002 mas and microlens parallax, we determine that the lens system consists of two M dwarfs with masses of M ₁ = 0.258 ± 0.008 M _⊙ and M ₂ = 0.130 ± 0.007 M _⊙, a projected separation of r _⊥ = 6.83 ± 0.31 au, and a distance of D _L = 2.29 ± 0.08 kpc. The successful VLTI observations of ASASSN-22av open up a new path for studying intermediate-separation (i.e., a few astronomical units) stellar-mass binaries, including those containing dark compact objects such as neutron stars and stellar-mass black holes.

The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with keywords. Utilizing state-of-the-art large language models (LLMs) and a corpus of 385,166 peer-reviewed papers from the Astrophysics Data System, pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use keywords or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool’s versatility through case studies, showcasing its application in various research scenarios. The system’s performance is evaluated using custom benchmarks, including single-paper and multipaper tasks. Beyond literature review, pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g., in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying artificial intelligence to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature.

We analyse the M31 halo and its substructure within a projected radius of 120 kpc using a combination of Subaru/HSC NB515 and CFHT/MegaCam g- & i-bands. We succeed in separating M31’s halo stars from foreground contamination with ∼ 90 % accuracy by using the surface gravity sensitive NB515 filter. Based on the selected M31 halo stars, we discover three new substructures, which associate with the Giant Southern Stream (GSS) based on their photometric metallicity estimates. We also produce the distance and photometric metallicity estimates for the known substructures. While these quantities for the GSS are reproduced in our study, we find that the North-Western stream shows a steeper distance gradient than found in an earlier study, suggesting that it is likely to have formed in an orbit closer to the Milky Way. For two streams in the eastern halo (Stream C and D), we identify distance gradients that had not been resolved. Finally, we investigate the global halo photometric metallicity distribution and surface brightness profile using the NB515-selected halo stars. We find that the surface brightness of the metal-poor and metal-rich halo populations, and the all population can be fitted to a power-law profile with an index of α = −1.65 ± 0.02, −2.82 ± 0.01, and −2.44 ± 0.01, respectively. In contrast to the relative smoothness of the halo profile, its photometric metallicity distribution appears to be spatially non-uniform with nonmonotonic trends with radius, suggesting that the halo population had insufficient time to dynamically homogenize the accreted populations.

We find ourselves on the brink of an exciting era in observational astrophysics, driven by groundbreaking facilities like JWST, Euclid, Rubin, Roman, SKA, or ELT. Simultaneously, computational astrophysics has shown significant strides, yielding highly realistic galaxy formation simulations, thanks to both hardware and software enhancements. Bridging the gap between simulations and observations has become paramount for meaningful comparisons.

Ongoing deep IFS observations of disk galaxies provide opportunities for comparison with the Milky Way (MW) to understand galaxy evolution. However, such comparisons are marred by many challenges such as selection effects, differences in observations and methodology, and proper validation of full-spectrum fitting methods. In this study, we present a novel code GalCraft to address these challenges by generating mock IFS data cubes of the MW using simple stellar population models and a mock MW stellar catalog derived from E-Galaxia. We use the widely adopted full-spectrum fitting code pPXF to investigate the ability to recover kinematics and stellar populations for an edge-on mock MW IFS observation. We confirm that differences in kinematics, mean age, [M/H], and [α/Fe] between thin and thick disks can be distinguished. However, the age distribution is overestimated in the ranges between 2 − 4 and 12 − 14 Gyr compared to the expected values. This is likely due to the age spacing and degeneracy of SSP templates. We find systematic offsets in the recovered kinematics due to insufficient spectral resolution and the variation of line-of-sight velocity distribution with age and [M/H]. With future higher resolution and multi-[α/Fe] SSP templates, GalCraft will be useful to validate key signatures such as [α/Fe]-[M/H] distribution at different R and |z| and potentially infer radial migration and kinematic heating efficiency to study detailed chemodynamical evolution of MW-like galaxies.