arXiv subjects

Jayashree Behera

Publications and source records attributed to Jayashree Behera.

5 recordsLinked to original sources

arXiv2026

Joint Multiband Photometry with crowdsource

We present a new multiband extension to the crowdsource photometric pipeline, enabling simultaneous fitting across multiple imaging bands in crowded fields. The core idea is that multiple images of the same part of the sky should have the same sources at the same locations; only the fluxes in the different images should be allowed to vary in fitting. The framework also allows us to use all images of a given region to detect faint sources, with configurable weighting among the different bandpasses as appropriate for different source spectra. Similar concepts are already present in other crowded field packages like DAOPHOT and DOLPHOT; we now include it in the crowdsource fitting approach. We describe the mathematical formulation of the multiband fit and demonstrate its performance using the Wide-field Infrared Survey Explorer (WISE) W1 and W2 imaging as a concrete application. The multiband algorithm improves flux consistency and reduces band-to-band positional scatter relative to independent-band fitting. We test the method on unWISE coadded tiles spanning both sparse and crowded regions and quantify improvements in photometric agreement and astrometric stability. This framework provides a general foundation for future multiband crowded-field catalogs.

astro-ph.IM↗

arXiv2024

Optimised neural network predictions of galaxy formation histories using semi-stochastic corrections

We present a novel methodology to improve predictions of galaxy formation histories by incorporating semi-stochastic corrections to account for short-timescale variability. Our paper addresses limitations in existing models that capture broad trends in galaxy evolution, but fail to reproduce the bursty nature of star formation and chemical enrichment, resulting in inaccurate predictions of key observables such as stellar masses, optical spectra, and colour distributions. We introduce a simple technique to add a stochastic components by utilizing the power spectra of galaxy formation histories. We justify our stochastic approach by studying the correlation between the phases of the halo mass assembly and star-formation histories in the IllustrisTNG simulation, and we find that they are correlated only on timescales longer than 6 Gyr, with a strong dependence on galaxy type. We demonstrate our approach by applying our methodology to the predictions on a neural network trained on hydrodynamical simulations, which failed to recover the high-frequency components of star-formation and chemical enrichment histories. Our methodology successfully recovers realistic variability in galaxy properties at short timescales. It significantly improves the accuracy of predicted stellar masses, metallicities, spectra, and colour distributions and provides a practical framework for generating large, realistic mock galaxy catalogs, while also enhancing our understanding of the complex interplay between galaxy evolution and dark matter halo assembly.

astro-ph.GA↗

arXiv2024

Evaluating the galaxy formation histories predicted by a neural network in pure dark matter simulations

We investigate a series of galaxy properties computed using the merger trees and environmental histories from dark matter only cosmological simulations, using a semi-recurrent neural network producing self-consistent predictions of galaxy evolution, and using stochastic improvements to this model based on similarly predicted Fourier Transforms. We apply these methods to the dark matter only runs of the IllustrisTNG simulations to understand the effects of baryon removal, and to the gigaparsec-volume pure dark matter simulation Uchuu, to understand the effects of the lower resolution or alternative metrics for halo properties. We find that the machine learning model recovers accurate summary statistics derived from the predicted star formation and stellar metallicity histories, and correspondent spectroscopy and photometry. However, the inaccuracies of the model's application to dark simulations are substantial for low mass and slowly growing haloes. For these objects, the halo mass accretion rate is exaggerated due to the lack of stellar feedback, yet the formation of the halo can be severely limited by the absence of low mass progenitors in a low resolution simulation. Furthermore, differences in the structure and environment of higher mass haloes results in an overabundance of red, quenched galaxies. These results signify progress towards a machine learning model which builds high fidelity mocks based on a physical interpretation of the galaxy-halo connection, yet they illustrate the need to account for differences in halo properties and the resolution of the simulation.

astro-ph.CO↗

arXiv2023

Modeling the BAO feature in Bispectrum

We investigate how well a simple leading order perturbation theory model of the bispectrum can fit the BAO feature in the measured bispectrum monopole of galaxies. Previous works showed that perturbative models of galaxy bispectrum start failing at the wavenumbers of k ~ 0.1 Mpc/h. We show that when the BAO feature in the bispectrum is separated it can be successfully modeled up to much higher wavenumbers. We validate our modeling on GLAM simulations that were run with and without the BAO feature in the initial conditions. We also quantify the amount of systematic error due to BAO template being offset from the true cosmology. We find that the systematic errors do not exceed 0.3 per cent for reasonable deviations from the true cosmology.

astro-ph.CO↗

arXiv2023

NANCY: Next-generation All-sky Near-infrared Community surveY

The Nancy Grace Roman Space Telescope is capable of delivering an unprecedented all-sky, high-spatial resolution, multi-epoch infrared map to the astronomical community. This opportunity arises in the midst of numerous ground- and space-based surveys that will provide extensive spectroscopy and imaging together covering the entire sky (such as Rubin/LSST, Euclid, UNIONS, SPHEREx, DESI, SDSS-V, GALAH, 4MOST, WEAVE, MOONS, PFS, UVEX, NEO Surveyor, etc.). Roman can uniquely provide uniform high-spatial-resolution (~0.1 arcsec) imaging over the entire sky, vastly expanding the science reach and precision of all of these near-term and future surveys. This imaging will not only enhance other surveys, but also facilitate completely new science. By imaging the full sky over two epochs, Roman can measure the proper motions for stars across the entire Milky Way, probing 100 times fainter than Gaia out to the very edge of the Galaxy. Here, we propose NANCY: a completely public, all-sky survey that will create a high-value legacy dataset benefiting innumerable ongoing and forthcoming studies of the universe. NANCY is a pure expression of Roman's potential: it images the entire sky, at high spatial resolution, in a broad infrared bandpass that collects as many photons as possible. The majority of all ongoing astronomical surveys would benefit from incorporating observations of NANCY into their analyses, whether these surveys focus on nearby stars, the Milky Way, near-field cosmology, or the broader universe.

astro-ph.IM↗