arXiv subjects

Kaylee de Soto

Publications and source records attributed to Kaylee de Soto.

8 recordsLinked to original sources

arXiv2026

AT 2024ahzi: A Type IIP Supernova Discovered by the LSST Commissioning Camera

As part of its commissioning, the Vera C. Rubin Observatory observed several fields repeatedly for a month with ComCam, an instrument that uses the same hardware as the LSST camera but covers a smaller field of view. We photometrically classify AT 2024ahzi, a transient discovered by ComCam, as a Type IIP supernova (SN IIP) using both ComCam and DECam photometry. We find that the duration, luminosity, and color of AT 2024ahzi's photometric plateau are all consistent with those from a large sample of SNe II. By comparing its multi-band light curves to SN II models and analytic relations, we place constraints on the SN progenitor, explosion dynamics, and circumstellar environment. We argue that the progenitor has an extended density profile indistinguishable from a slowly accelerating CSM. We discuss how a similar workflow can identify and characterize future Rubin SNe II.

astro-ph.HE↗

arXiv2025

Characterizing Supernova Host Galaxies with FrankenBlast: A Scalable Tool for Transient Host Galaxy Association, Photometry, and Stellar Population Modeling

We present FrankenBlast, a customized and improved version of the Blast web application. FrankenBlast associates transients to their host galaxies, performs host photometry, and runs a innovative SED fitting code to constrain host stellar population properties--all within minutes per object. We test FrankenBlast on 14,432 supernovae (SNe), ~half of which are spectroscopically-classified, and are able to constrain host properties for 9262 events. When contrasting the host stellar masses ($M_*$), specific star formation rates (sSFR), and host dust extinction ($A_V$) between spectroscopically and photometrically-classified SNe Ia, Ib/c, II, and IIn, we determine that deviations in these distributions are primarily due to misclassified events contaminating the photometrically-classified sample. We further show that the higher redshifts of the photometrically-classified sample also force their $M_*$ and sSFR distributions to deviate from those of the spectroscopically-classified sample, as these properties are redshift-dependent. We compare host properties between spectroscopically-classified SN populations and determine if they primarily trace $M_*$ or SFR. We find that all SN populations seem to both depend on $M_*$ and SFR, with SNe II and IIn somewhat more SFR-dependent than SNe Ia and Ib/c, and SNe Ia more $M_*$-dependent than all other classes. We find the difference in the SNe Ib/c and II hosts the most intriguing and speculate that SNe Ib/c must be more dependent on higher $M_*$ and more evolved environments for the right conditions for progenitor formation. All data products and FrankenBlast are publicly available, along with a developing FrankenBlast version intended for Rubin Observatory science products.

astro-ph.HE↗

arXiv2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera (DECam) as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

astro-ph.HE↗

arXiv2025

Spectral Diversity in Type Ibn Supernovae and the Large Host Offset of SN2024acyl

In this paper, we first present observations of SN~2024acyl, a normal Type Ibn supernova with a large projected offset ($\sim$35~kpc) from its host galaxy. The low star-formation rate measured at the explosion site raises the possibility that the progenitor of SN~2024acyl may not have been a massive star. We then examine, more broadly, the spectral diversity of Type Ibn supernovae around 20--35 days after peak brightness and identify two distinct groups: Group I, which shows bluer rest-frame optical color and narrower He~I emission lines; and Group II, which shows redder rest-frame optical color and broader He~I lines. Group~I also tends to show higher peak luminosities. The diversity we identify appears to be closely connected to the diversity observed around peak and to persist into late phases ($>80$ days after peak). Given its redder color and broader He~I lines, we classify SN~2024acyl as belonging to Group II. Based on the current dataset, we find no clear connection between this spectral diversity and either the host environments of Type Ibn SNe or their pre-explosion activity. The observed diversity in Type Ibn SNe likely reflects differences in circumstellar material properties and/or explosion energetics. These differences could result from a range of progenitor properties, such as different helium star mass, orbital period and companion type if they are in binary systems, and may indicate fundamentally diverse progenitors. Whether a continuous distribution exists between the two groups remains to be determined and will require further data to explore.

astro-ph.HE↗

arXiv2025

Million Points of Light (MPoL): a PyTorch library for radio interferometric imaging and inference

Astronomical radio interferometers achieve exquisite angular resolution by cross-correlating signal from a cosmic source simultaneously observed by distant pairs of radio telescopes to produce a Fourier-type measurement called a visibility. Million Points of Light (MPoL) is a Python library supporting feed-forward modeling of interferometric visibility datasets for synthesis imaging and parametric Bayesian inference, built using the autodifferentiable machine learning framework PyTorch. Neural network components provide a rich set of modular and composable building blocks that can be used to express the physical relationships between latent model parameters and observed data following the radio interferometric measurement equation. Industry-grade optimizers make it straightforward to simultaneously solve for the synthesized image and calibration parameters using stochastic gradient descent.

astro-ph.IM↗

arXiv2023

Hierarchical Cross-entropy Loss for Classification of Astrophysical Transients

Astrophysical transient phenomena are traditionally classified spectroscopically in a hierarchical taxonomy; however, this graph structure is currently not utilized in neural net-based photometric classifiers for time-domain astrophysics. Instead, independent classifiers are trained for different tiers of classified data, and events are excluded if they fall outside of these well-defined but flat classification schemes. Here, we introduce a weighted hierarchical cross-entropy objective function for classification of astrophysical transients. Our method allows users to directly build and use physics- or observationally-motivated tree-based taxonomies. Our weighted hierarchical cross-entropy loss directly uses this graph to accurately classify all targets into any node of the tree, re-weighting imbalanced classes. We test our novel loss on a set of variable stars and extragalactic transients from the Zwicky Transient Facility, showing that we can achieve similar performance to fine-tuned classifiers with the advantage of notably more flexibility in downstream classification tasks.

astro-ph.IM↗

arXiv2023

Relative intrinsic scatter in hierarchical Type Ia supernova siblings analyses: Application to SNe 2021hpr, 1997bq & 2008fv in NGC 3147

We present Young Supernova Experiment $grizy$ photometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates, and investigating the contributions towards the SN Ia intrinsic scatter (post-standardisation residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter, $σ_{Rel}$: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution towards the total intrinsic scatter, $σ_0$, from within-galaxy variations about the siblings' common properties. It also affects the combined-distance uncertainty. We present analytic formulae for computing a $σ_{Rel}$-posterior from individual siblings distances (estimated using any SN-model). Applying a newly trained BayeSN model, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wide $σ_{Rel}$-posterior means $σ_{Rel}\approxσ_0$ is not ruled out. We thus combine the distances by marginalizing over $σ_{Rel}$ with an informative prior: $σ_{Rel}\sim U(0,σ_0)$. Simultaneously fitting the trio's light curves improves constraints on distance, and each sibling's individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore, $σ_{Rel}$-marginalization yields robust estimates of siblings distances for cosmology, and dust parameters for siblings-host correlation studies. Incorporating NGC 3147's Cepheid-distance yields $H_0=78.4\pm 6.5\,$km/s/Mpc. Our work motivates analyses of homogeneous siblings samples, to constrain $σ_{Rel}$, and its SN-model dependence.

astro-ph.CO↗

arXiv2022

Tracing Milky Way substructure with an RR Lyrae hierarchical clustering forest

RR Lyrae variable stars have long been reliable standard candles used to discern structure in the Local Group. With this in mind, we present a routine to identify groupings containing a statistically significant number of RR Lyrae variables in the Milky Way environment. RR Lyrae variable groupings, or substructures, with potential Galactic archaeology applications are found using a forest of agglomerative, hierarchical clustering trees, whose leaves are Milky Way RR Lyrae variables. Each grouping is validated by ensuring that the internal RR Lyrae variable proper motions are sufficiently correlated. Photometric information was collected from the Gaia second data release and proper motions from the (early) third data release. After applying this routine to the catalogue of 91234 variables, we are able to report sixteen unique RR Lyrae substructures with physical sizes of less than 1 kpc. Five of these substructures are in close proximity to Milky Way globular clusters with previously known tidal tails and/or a potential connection to Galactic merger events. One candidate substructure is in the neighbourhood of the Large Magellanic Cloud but is more distant (and older) than known satellites of the dwarf galaxy. Our study ends with a discussion of ways in which future surveys could be applied to the discovery of Milky Way stellar streams.

astro-ph.GA↗