arXiv subjects

Sean Xu

Publications and source records attributed to Sean Xu.

5 recordsLinked to original sources

arXiv2026

The Carousel Lens III: Joint lens convergence and source kinematic modeling

We introduce a new, independent modeling component to the Carousel Lens series by exploiting the spatially-resolved kinematics contained within the lensed arcs, which so far has remained rather underexplored in strong-lensing analyses. We present an end-to-end forward-modeling framework that reconstructs an integral-field spectroscopic datacube from a parameterization of the lens convergence profile together with the line-of-sight velocity, velocity dispersion, and surface brightness profiles of the unlensed source. The kinematic structure of the source acts as an additional set of ray-traceable markers distributed across every lensed image, inaccessible from imaging data alone. Furthermore, by generating an [OII] emission-line datacube, we isolate a single source redshift and remove lens and line-of-sight light contamination. We apply this framework to deep VLT/MUSE observations of the Carousel Lens, modeling the [OII] emission of the quadruply-imaged star-forming galaxy at $z_{\rm s} = 1.432$ that anchors the system's cosmography constraints. We measure an Einstein radius $θ_{\rm E} = 12.816''^{+0.005}_{-0.007}$ and a logarithmic slope $γ= 1.412^{+0.002}_{-0.002}$, tightening the statistical uncertainties on both by roughly a factor of $2-2.5$ relative to the corresponding flat emission-line map model. We find that the source galaxy exhibits a strong rotation, lies confidently along the star-forming main sequence, and has an inferred central black hole mass of $\log M_{\rm BH}/M_{\odot} = 7.89 \pm 0.51$. These results establish datacube-level forward modeling as a practical and independent route to traditional image-based lens models in the current systematics-limited regime, and one that extends naturally to this system's other lensed sources and to other lens systems.

astro-ph.GA↗

arXiv2026

GIGA-Lens 2.0: Strong-Lens Modeling on Multiple GPU Nodes

We present GIGA-Lens 2.0: a major upgrade to the GPU-accelerated Bayesian framework for modeling strong lensing systems that allows it to be run across multiple GPU nodes. We have succeeded in running GIGA-Lens 2.0 on 128 nodes or 512 A100 GPUs. We demonstrate the speed benefits of this new version, and apply them to modeling 100 simulated systems and a real system, DESI J238.5690+04.7276. We also present other changes to the framework that have yielded further improvement on performance.

astro-ph.CO↗

arXiv2026

The Carousel Lens II: Cosmological Constraints with GIGA-Lens

The nature of dark matter and dark energy are among the central questions in cosmology. Strong gravitational lenses with multiple source planes provide a geometric probe of cosmology: the ratio of deflection angles at different redshifts depends only on angular-diameter distances, constraining the matter density $Ω_m$ and the dark energy equation of state $w$. However, constraints from this technique have historically lagged behind those from the CMB, SNe Ia, and BAO. In this work, we present new cosmological constraints from the Carousel Lens, a cluster-scale lens with more than 40 extended images from 11 spectroscopically confirmed sources. Its relaxed core and rich set of extended images behind the main halo make it particularly suitable for cosmological inference. Using the GIGA-Lens pipeline, we construct a pixel-level lens model including six HST-detected sources and four mass components. From this model, we obtain $w$CDM constraints of $Ω_m = 0.34^{+0.16}_{-0.13}$ and $w = -1.31^{+0.35}_{-0.32}$ from the Carousel Lens alone, accounting for both statistical and systematic uncertainties. We further project that including four additional known higher-redshift sources, assuming similar fractional uncertainties, could improve the constraining power by ~80%, bringing the precision close to that of the CMB and SNe Ia. For an evolving dark energy model ($w_0w_a$CDM), the Carousel Lens alone yields constraints comparable to the CMB, providing an independent and complementary probe alongside SN Ia and BAO. While currently systematic uncertainties dominate, which we quantify through simulations, our results demonstrate that relaxed multi-source-plane cluster lenses can deliver competitive cosmological constraints. Further improvements are expected from reductions in systematics and from incorporating higher-redshift sources (known and new) with high-resolution imaging.

astro-ph.CO↗

arXiv2026

A Novel Lensed Point Source Modeling Pipeline using GIGA-Lens with Application to SN Zwicky and SN iPTF16geu

We introduce a novel modeling pipeline for strongly lensed point sources, using the GIGA-Lens framework, running on four A100 GPUs via the JAX platform. Using simulations, we demonstrate accurate and precise recovery of image positions, fluxes, and time delays, together with inference of complex lens mass distributions -- including the mass density slope, $γ$ -- from images of lensed point sources alone. We further show that we can achieve statistical uncertainty of $\sim 3.6\%$ ($\sim 2.5\, \mathrm{km\, s^{-1}/Mpc}$) on $H_0$ from a single system, with full forward modeling, i.e., simultaneous inference of all lens model parameters together with $H_0$. We apply our pipeline to two well-studied lensed SNe Ia, Zwicky and iPTF16geu. For SN iPTF16geu, unlike previous modeling efforts, we model only the images of the lensed point source (the SN) and do not use the lensed images of the extended host-galaxy. Nevertheless, we are able to infer all of the mass parameters modeled in earlier studies, and our best-fit values, including $γ$, are fully consistent with published results. In the case of SN Zwicky, taking the same approach, however, we obtain an alternative best-fit model compared to published results, underscoring the importance of fully exploring the model parameter space.

astro-ph.CO↗

arXiv2025

DESI Strong Lens Foundry V: A Sample of HST-Observed Strong Lenses Modeled with GIGA-Lens

We present six galaxy-scale strong lenses with HST imaging modeled using GIGA-Lens. This is Paper V of the DESI Strong Lens Foundry series. These systems were discovered in the DESI Legacy Imaging Surveys using ML/AI methods and confirmed with DESI, Keck/NIRES, and VLT/MUSE spectroscopy. They span $z_d = 0.39 - 1.1$ and $z_s = 1.4 - 3.3$. This is the first HST strong lens sample modeled with full forward modeling -- all lens and source parameters sampled simultaneously in a single inference -- with explicit convergence validation using both $\widehat{R}$ and effective sample size (ESS) for each system. All inferred parameters satisfy $\widehat{R} < 1.1$ and ${\rm ESS} \gtrsim 10,000$, demonstrating that GIGA-Lens achieves statistically robust inference even for some of the most complex galaxy-scale lenses known. These results pave the way for scaling to much larger, high-resolution strong lens samples from HST, Euclid, JWST, and Roman. Convergence-validated modeling will be critical for key science goals, including constraining the mass-density profile of galaxies, detecting low-mass dark matter (sub)halos, and delivering precise and accurate cosmological constraints.

astro-ph.CO↗