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Anowar Shajib

Publications and source records attributed to Anowar Shajib.

6 recordsLinked to original sources

Can third- and fourth-order multipoles plus radial variation of iso-density ellipses explain the observed flux ratios in B1422$+$231? YES, and a lesson learned from a TNG100 lensing galaxy sample

Flux ratio anomalies in multiply-imaged quasar lenses are a long-standing issue. Using a classical system B1422+231 as a case study, we investigate how typical non-clumpy perturbations beyond elliptical shapes -- multipoles $m_3, m_4$ and radial variations in $q, \phi_q$ -- can account for the observed image positions and flux ratios under different observational precisions. We extract these perturbations from a pre-selected strong-lensing galaxy sample from the TNG100 simulation. Smooth macroscopic models (SIE+$\gamma$, EPL+$\gamma$) are then fitted to the observed image positions alone and to both positions and flux ratios, with and without including the extracted perturbations. With astrometric uncertainty of $\sigma_{p}=10$ mas, both macro-models alone can already successfully fit image positions within $3\sigma_{p}$. At $\sigma_{p}=2$ mas, however, 'astrometric anomalies' appear if smooth macro-models alone are adopted. In this case, adding the extracted perturbations can explain the anomalous image positions. When both positions and flux ratios are adopted, the SIE+$\gamma$ model family already shows 'flux ratio anomalies' at photometric uncertainty $\sigma_{f} \le 10\%$ (keeping $\sigma_{p}=10$ mas). When EPL+$\gamma$ is used, the smooth model alone can simultaneously fit both positions and flux ratios with $\sigma_{f}=10\%, 5\%$, but not with $\sigma_{f}=2\%$, where 'flux ratio anomalies' appear. Adding all four types of extracted perturbations can rescue the macro-models and explain the observed anomalous flux ratios. We present important lessons learned regarding model flexibility and degeneracy.

astro-ph.GA

SLSim: a strong lensing population simulation package

Gravitational lensing offers unique insights into cosmology by bending light around massive objects. Strong gravitational lensing, in particular, produces magnified and often multiple images of distant sources, crucial for precise cosmological measurements and understanding the distribution of dark matter in the universe. Current studies are limited by the number of strong gravitational lenses. From upcoming cosmological surveys, we anticipate observing a several orders of magnitude increase in the number of lenses, for both static and transient phenomena. However, detecting and analyzing these events from vast surveys like Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) presents significant challenges. To prepare for these challenges, we introduce SLSim, a versatile simulation tool tailored for the Vera C. Rubin Observatory. SLSim integrates advanced astrophysical models with computational efficiency to generate synthetic strong lens populations under realistic observational conditions. SLSim simulates static and variable lensing scenarios, essential for cosmological studies, training and testing lens search and data analysis pipelines. This paper details SLSim,'s design and implementation, emphasizing its modularity and capabilities across various astrophysical regimes. Validation against observational data and existing simulations confirms SLSim's accuracy in reproducing observed lensing phenomena. SLSim is publicly available at https://github.com/LSST-strong-lensing/slsim, and we anticipate continued development and expansion of its capabilities. Users are encouraged to check the repository for updates and to contribute to ongoing community efforts in strong lensing simulations.

astro-ph.CO

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

The AGEL Survey Data Release 2: A Gravitational Lens Sample for Galaxy Evolution and Cosmology

The ASTRO 3D Galaxy Evolution with Lenses (AGEL) Survey is an ongoing effort to spectroscopically confirm a diverse sample of gravitational lenses with high spatial resolution imaging, to facilitate a broad range of science outcomes. The AGEL systems span single galaxy-scale deflectors to groups and clusters, and include rare targets such as galaxy-scale lenses with multiple sources, lensed quiescent galaxies, and Einstein rings. We build on the 77 systems presented in Tran et al. 2022 (AGEL data release 1) to present a total 138 lenses, and high resolution F140W and F200LP Hubble Space Telescope images for 71 lenses from a completed HST SNAP program. Lens candidates were originally identified by convolutional neural networks in the DES and DECaLS imaging fields, and of the targets with follow-up spectroscopy we find a high (96%) success rate. Compared with other spectroscopic lens samples, AGEL lenses tend to have both higher redshift deflectors and sources. We briefly discuss the common causes of false-positive candidates, and strategies for mitigating false-positives in next generation lens searches. Lastly, we present 6 galaxy-scale double-source plane lenses useful for cosmological analyses. With next-generation telescopes and surveys such as Euclid, Vera Rubin's Legacy Survey of Space and Time, Keck Observatory's KAPA program, and 4MOST's 4SLSLS surveys on the horizon, the AGEL survey represents a pathfinder for refining automated candidate search methods and identifying and triaging candidates for followup based on scientific potential.

astro-ph.GA

Metallicity Scatter Originating from Sub-kiloparsec Starbursting Clumps in the Core of a Protocluster at z=7.88

We present new JWST NIRSpec integral field unit (IFU) G395H/F290LP observations of a merging galaxy system at $z=7.88$, part of A2744-z7p9, the most distant protocluster to date. The IFU cube reveals [OIII] emissions in two previously known galaxies (ZD3 and ZD6) and a newly identified galaxy, ZD12, at $z_{\rm spec}=7.8762$. One of the detected \oiii-emitting regions has a detection of the auroral [OIII]4363, line, allowing us to derive a direct metallicity of $\log$(O/H)$+12=7.4\pm0.2$, while metallicities in other regions are measured using strong line calibration methods. We find large deviations within the measured metallicity ($Δ\log {\rm (O/H)}\sim1$), which suggests a fast chemical enrichment from intense star formation and merger-driven growth, as expected in early galaxies. Our analysis shows that metal-poor regions could easily be outshone by more enriched regions, posing a challenge for spectroscopic analysis based on integrated light (i.e., NIRSpec MSA) against identifying metal-free star formation in the early universe. NIRCam imaging reveals seven UV-bright clumps in ZD12, in the range of stellar mass $\log M_*/M_\odot\sim7.6$--8.9. Four of them are unresolved ($< 100$pc) and intensely star-forming ($>30 M_\odot {\rm yr^{-1} kpc^{-2}}$), likely contributing to the scatter in metallicity by producing an ideal environment for rapid chemical cycles. Lastly, we revisit the nature of the host protocluster by including new member galaxies identified here and in the literature, and obtain local overdensity factor $δ=44_{-31}^{+89}$, total halo mass $M_{\rm h} = 5.8_{-0.3}^{+0.2}\times10^{11}\,M_\odot$, and a formal velocity dispersion of $1100\pm500$ km s$^{-1}$.

astro-ph.GA

Lens Modeling of STRIDES Strongly Lensed Quasars using Neural Posterior Estimation

Strongly lensed quasars can be used to constrain cosmological parameters through time-delay cosmography. Models of the lens masses are a necessary component of this analysis. To enable time-delay cosmography from a sample of $\mathcal{O}(10^3)$ lenses, which will soon become available from surveys like the Rubin Observatory's Legacy Survey of Space and Time (LSST) and the Euclid Wide Survey, we require fast and standardizable modeling techniques. To address this need, we apply neural posterior estimation (NPE) for modeling galaxy-scale strongly lensed quasars from the Strong Lensing Insights into the Dark Energy Survey (STRIDES) sample. NPE brings two advantages: speed and the ability to implicitly marginalize over nuisance parameters. We extend this method by employing sequential NPE to increase precision of mass model posteriors. We then fold individual lens models into a hierarchical Bayesian inference to recover the population distribution of lens mass parameters, accounting for out-of-distribution shift. After verifying our method using simulated analogs of the STRIDES lens sample, we apply our method to 14 Hubble Space Telescope single-filter observations. We find the population mean of the power-law elliptical mass distribution slope, $\gamma_{\text{lens}}$, to be $\mathcal{M}_{\gamma_{\text{lens}}}=2.13 \pm 0.06$. Our result represents the first population-level constraint for these systems. This population-level inference from fully automated modeling is an important stepping stone towards cosmological inference with large samples of strongly lensed quasars.

astro-ph.IM