arXiv subjects

Padmavathi Venkatraman

Publications and source records attributed to Padmavathi Venkatraman.

7 recordsLinked to original sources

arXiv2026

Lens Modeling and Cosmological Inference from an Impure Sample of Galaxy-Galaxy Strong Lenses

The start of the Legacy Survey of Space and Time marks a new era for strong lensing science, where the number of strong lenses identified is expected to increase to $\mathcal{O}(10^5)$. In this paper we use a neural network to determine the precision with which lens parameters can be determined, using realistic simulated LSST lensed systems. We find that the Einstein radius can be measured with a mean precision of $3.7\%$ with calibrated uncertainties accurately reflecting the corresponding measurement error. Based on the performance of current strong lens classifiers, the $\sim 100,000$ detectable strong lenses are expected to be accompanied by a similar or larger number of false positives (non-lenses). In readiness for this we introduce a formalism, termed `COSMIC-BEAMS', to infer cosmological parameters while accounting for contamination by false positives. As a proof-of-concept, using simulated LSST measurements of the Einstein radii of a realistic and impure sample of photometric lens systems, i.e. those without spectroscopic confirmation, we find that the cosmological parameters $Ω_m$, $Ω_Λ$, and $w$ can be measured to a precision of $0.1$, $0.03$ and $0.15$ respectively for a $w$CDM cosmology. We demonstrate that unbiased cosmological parameters can be inferred even in strong lens samples contaminated by $50\%$ false positives, and that the photometric dataset of $100\,000$ strong lenses will provide equivalent $w$-precision to $2500-3500$ spectroscopic systems.

astro-ph.CO↗

arXiv2026

NEXUS: A Search for Nuclear Variability with the First Two JWST NIRCam Epochs

The multi-cycle JWST Treasury program NEXUS will obtain cadenced imaging and spectroscopic observations around the North Ecliptic Pole during 2024-2028. Here we report a systematic search for nuclear variability among $\sim 25\,$k sources covered by NIRCam (F200W+F444W) imaging using the first two NEXUS epochs separated by 9 months in the observed frame. Difference imaging techniques reach $1σ$ variability sensitivity of 0.18~mag (F200W) and 0.15~mag (F444W) at 28th magnitude (within 0".2 diameter aperture), improved to $0.01$~mag and $0.02$~mag at $<25$th magnitude, demonstrating the superb performance of NIRCam photometry. The difference imaging results represent significant improvement over aperture photometry on individual epochs (by $>30\%$). We identify 465 high-confidence variable sources among the parent sample, with 2-epoch flux difference at $>3σ$ from the fiducial variability sensitivity. Essentially all these variable sources are of extragalactic origin based on preliminary photometric classifications, and follow a similar photometric redshift distribution as the parent sample up to $z_{\rm phot}>10$. While the majority of these variability candidates are likely normal unobscured AGNs, some of them may be rare nuclear stellar transients and tidal disruption events that await confirmation with spectroscopy and continued photometric monitoring. We also constrain the photometric variability of ten spectroscopically confirmed broad-line Little Red Dots (LRDs) at $3\lesssim z \lesssim 7$, and find none of them show detectable variability in either band. We derive stringent $3σ$ upper limits on the F444W variability of $\sim 3-10\%$ for these LRDs, with a median value of $\sim 5\%$. These constraints imply weak variability in the rest-frame optical continuum of LRDs.

astro-ph.GA↗

arXiv2026

Investigating the Dark Energy Constraint from Strongly Lensed AGN at LSST-Scale

Strongly lensed Active Galactic Nuclei (AGN) with an observable time delay can be used to constrain the expansion history of the Universe through time-delay cosmography (TDC). As the sample of time-delay lenses grows to statistical size, with $\mathcal{O}$(1000) lensed AGN forecast to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), there is an emerging opportunity to use TDC as an independent probe of dark energy. To take advantage of this statistical sample, we implement a scalable hierarchical inference tool which computes the cosmological likelihood for hundreds of strong lenses simultaneously. With this new technique, we investigate the cosmological constraining power from a simulation of the full LSST sample. We start from individual lenses, and emulate the full joint hierarchical TDC analysis, including image-based modeling, time-delay measurement, velocity dispersion measurement, and external convergence prediction. We fully account for the mass-sheet and mass-anisotropy degeneracies. We assume a sample of 800 lenses, with varying levels of follow-up fidelity based on existing campaigns. With our baseline assumptions, within a flexible $w_0w_a$CDM cosmology, we simultaneously forecast a $\sim$2.5% constraint on H0 and a dark energy figure of merit (DE FOM) of 6.7. We show that by expanding the sample from 50 lenses with IFU kinematics to include 750 lenses with plausible LSST time-delay measurements, we improve the forecasted DE FOM by nearly a factor of 3, demonstrating the value of incorporating this portion of the sample. We also investigate different follow-up campaign strategies, and find significant improvements in the DE FOM with additional stellar kinematics measurements and higher-precision time-delay measurements. We also demonstrate how the redshift configuration of time-delay lenses impacts constraining power in $w_0w_a$CDM.

astro-ph.CO↗

arXiv2026

NEXUS: Abundance, Environments, and Spectral Diversity of Little Red Dots from the NIRSpec MSA Sample

We present a comprehensive study of Little Red Dots (LRDs) at 2.3 < z < 7.4 using NIRCam photometry and NIRSpec MSA/PRISM spectra from the ongoing NEXUS program. Photometric selection combining several commonly adopted methods yields a high completeness of about 85% for LRD selection over this redshift range and for a flux limit of F444W < 26. The overall purity is about 60%, with contamination from emission-line galaxies and normal active galactic nuclei (AGNs), as well as dwarf stars. Most (>90%) of the spectroscopically confirmed LRDs have robust broad-line detection. Our spectroscopic sample of 36 LRDs displays the full range of spectral diversity of LRDs. It includes objects with extreme Balmer breaks similar to the LRD "Cliff", as well as objects with moderately reddened rest-optical continua that can be fit with low-temperature blackbody components in the recent BH* model framework. The broad H$α$ emission is correlated with the continuum emission at 5100 Angstrom, suggesting common origins for these emission components; the narrow [O III] emission, however, is poorly correlated with the optical continuum. We do not find evidence of redshift evolution in these spectral properties. The space density of LRDs declines toward z about 2, opposite to the trend for normal AGNs, although low-luminosity LRDs at z about 2-4 may be more abundant than currently probed by ground-based searches. The clustering of LRDs suggests that they live in dark matter halos of several times $10^{11}\ h^{-1}$ solar masses, albeit with large uncertainties. Overall, these results are consistent with recent observations of LRDs and with the emerging picture of accreting SMBHs enshrouded in dense gas envelopes as the origin of LRDs.

astro-ph.GA↗

arXiv2025

Picture an Astronomer: Best Practices for Retaining Talent in Astrophysics

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career outcome was the primary motivation for the Picture an Astronomer series, which included both targeted public outreach to increase representation of women in astrophysics and high-level, solution-oriented discussions among professional astronomers. In March 2025, more than 200 astronomers came together in a hybrid-format symposium focused on the state of the field for female scientists, combining scientific exchange with discussions of policies and practices to strengthen retention of talent in the field. This white paper is the result of those discussions, offering a wide range of recommendations developed in the context of gendered attrition in astrophysics but which ultimately support a healthier climate for all scientists alike.

astro-ph.IM↗

arXiv2025

Lens Model Accuracy in the Expected LSST Lensed AGN Sample

Strong gravitational lensing of active galactic nuclei (AGN) enables measurements of cosmological parameters through time-delay cosmography (TDC). With data from the upcoming LSST survey, we anticipate using a sample of O(1000) lensed AGN for TDC. To prepare for this dataset and enable this measurement, we construct and analyze a realistic mock sample of 1300 systems drawn from the OM10 (Oguri & Marshall 2010) catalog of simulated lenses with AGN sources at $z<3.1$ in order to test a key aspect of the analysis pipeline, that of the lens modeling. We realize the lenses as power law elliptical mass distributions and simulate 5-year LSST i-band coadd images. From every image, we infer the lens mass model parameters using neural posterior estimation (NPE). Focusing on the key model parameters, $θ_E$ (the Einstein Radius) and $γ_{lens}$ (the projected mass density profile slope), with consistent mass-light ellipticity correlations in test and training data, we recover $θ_E$ with less than 1% bias per lens, 6.5% precision per lens and $γ_{lens}$ with less than 3% bias per lens, 8% precision per lens. We find that lens light subtraction prior to modeling is only useful when applied to data sampled from the training prior. If emulated deconvolution is applied to the data prior to modeling, precision improves across all parameters by a factor of 2. Finally, we combine the inferred lens mass models using Bayesian Hierarchical Inference to recover the global properties of the lens sample with less than 1% bias.

astro-ph.CO↗

arXiv2024

shock_cooling_curve: A Python-Based Package for Extensive and Efficient Modeling of Shock Cooling Emission in Supernovae

The light-curve evolution of a supernova contains information of the exploding star. Early-time photometry of a variety of explosive transients, including Calcium-rich transients and type IIb/Ibc and IIP supernovae shows evidence for an early light curve peak as a result of the explosion's shock wave passing through extended material (i.e., shock cooling emission (SCE)). Analytic modeling of the shock cooling emission allows us to estimate progenitor properties such as the radius and mass of extended material (e.g., the stellar envelope) as well as the shock velocity. In this work, we present a Python-based modular package that implements four analytic models originally developed in Piro 2015, Piro 2020 and Sapir & Waxman (2017) applied to photometric data to obtain progenitor parameter properties via different modeling techniques (including non-linear optimization, MCMC sampling). Our software is easily extendable to other analytic models for SCE and different methods of parameter estimation.

astro-ph.HE↗