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James W. Nightingale

Publications and source records attributed to James W. Nightingale.

25 records · Page 2Linked to original sources

Efficient PSF Modeling with ShOpt.jl: A PSF Benchmarking Study with JWST NIRCam Imaging

With their high angular resolutions of 30--100 mas, large fields of view, and complex optical systems, imagers on next-generation optical/near-infrared space observatories, such as the Near-Infrared Camera (NIRCam) on the James Webb Space Telescope (JWST), present both new opportunities for science and also new challenges for empirical point spread function (PSF) characterization. In this context, we introduce ShOpt, a new PSF fitting tool developed in Julia and designed to bridge the advanced features of PIFF (PSFs in the Full Field of View) with the computational efficiency of PSFEx (PSF Extractor). Along with ShOpt, we propose a suite of non-parametric statistics suitable for evaluating PSF fit quality in space-based imaging. Our study benchmarks ShOpt against the established PSF fitters PSFEx and PIFF using real and simulated COSMOS-Web Survey imaging. We assess their respective PSF model fidelity with our proposed diagnostic statistics and investigate their computational efficiencies, focusing on their processing speed relative to the complexity and size of the PSF models. We find that ShOpt can already achieve PSF model fidelity comparable to PSFEx and PIFF while maintaining competitive processing speeds, constructing PSF models for large NIRCam mosaics within minutes.

astro-ph.IM↗

Unveiling Lens Light Complexity with A Novel Multi-Gaussian Expansion Approach for Strong Gravitational Lensing

In a strong gravitational lensing system, the distorted light from a source is analysed to infer the properties of the lens. However, light emitted by the lens itself can contaminate the image of the source, introducing systematic errors in the analysis. We present a simple and efficient lens light model based on the well-tested multi-Gaussian expansion (MGE) method for representing galaxy surface brightness profiles, which we combine with a semi-linear inversion scheme for pixelized source modelling. Testing it against realistic mock lensing images, we show that our scheme can fit the lensed images to the noise level, with relative differences between the true input and best-fit lens light model remaining below 5%. We apply the MGE lens light model to 38 lenses from the HST SLACS sample. We find that the new scheme provides a good fit for the majority of the sample with only 3 exceptions -- these show clear asymmetric residuals in the lens light. We examine the radial dependence of the ellipticity and position angles and confirm that it is common for a typical lens galaxy to exhibit twisting, non-elliptical isophotes and boxy / disky isophotes. Our MGE lens light model will be a valuable tool for understanding the hidden complexity of the lens mass distribution.

astro-ph.GA↗

Strong gravitational lensing's 'external shear' is not shear

The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power law plus 'external shear', which notionally accounts for neighbouring galaxies and cosmic shear. We show that it does not. Except in a handful of rare systems, the best-fit values of external shear do not correlate with independent measurements of shear: from weak lensing in 45 Hubble Space Telescope images, or in 50 mock images of lenses with complex distributions of mass. Instead, the best-fit shear is aligned with the major or minor axis of 88% of lens galaxies; and the amplitude of the external shear increases if that galaxy is disky. We conclude that 'external shear' attached to a power law model is not physically meaningful, but a fudge to compensate for lack of model complexity. Since it biases other model parameters that are interpreted as physically meaningful in several science analyses (e.g. measuring galaxy evolution, dark matter physics or cosmological parameters), we recommend that future studies of galaxy-scale strong lensing should employ more flexible mass models.

astro-ph.CO↗

Scanning For Dark Matter Subhalos in Hubble Space Telescope Imaging of 54 Strong Lenses

The cold dark matter (DM) model predicts that every galaxy contains thousands of DM subhalos; almost all other DM models include a physical process that smooths away the subhalos. The subhalos are invisible, but could be detected via strong gravitational lensing, if they lie on the line of sight to a multiply-imaged background source, and perturb its apparent shape. We present a predominantly automated strong lens analysis framework, and scan for DM subhalos in Hubble Space Telescope imaging of 54 strong lenses. We identify five DM subhalo candidates, including two especially compelling candidates (one previously known in SLACS0946+1006) where a subhalo is favoured after all of our tests for systematics. We find that the detectability of subhalos depends upon the assumed parametric form for the lens galaxy's mass distribution, especially its degree of azimuthal freedom. Using separate components for dark matter and stellar mass reveals two DM subhalo candidates and removes four false-positives compared to the single power-law mass model that is common in the literature. We identify 45 lenses without substructures, the number of which is key to statistical tests able to rule out models of e.g. warm or self-interacting DM. Our full analysis results are available at https://github.com/Jammy2211/autolens_subhalo.

astro-ph.CO↗

COSMOS-Web: An Overview of the JWST Cosmic Origins Survey

We present the survey design, implementation, and outlook for COSMOS-Web, a 255 hour treasury program conducted by the James Webb Space Telescope in its first cycle of observations. COSMOS-Web is a contiguous 0.54 deg$^2$ NIRCam imaging survey in four filters (F115W, F150W, F277W, and F444W) that will reach 5$σ$ point source depths ranging $\sim$27.5-28.2 magnitudes. In parallel, we will obtain 0.19 deg$^2$ of MIRI imaging in one filter (F770W) reaching 5$σ$ point source depths of $\sim$25.3-26.0 magnitudes. COSMOS-Web will build on the rich heritage of multiwavelength observations and data products available in the COSMOS field. The design of COSMOS-Web is motivated by three primary science goals: (1) to discover thousands of galaxies in the Epoch of Reionization ($6 4$ and place constraints on the formation of the Universe's most massive galaxies ($M_\star>10^{10}$\,M$_\odot$), and (3) directly measure the evolution of the stellar mass to halo mass relation using weak gravitational lensing out to $z\sim2.5$ and measure its variance with galaxies' star formation histories and morphologies. In addition, we anticipate COSMOS-Web's legacy value to reach far beyond these scientific goals, touching many other areas of astrophysics, such as the identification of the first direct collapse black hole candidates, ultracool sub-dwarf stars in the Galactic halo, and possibly the identification of $z>10$ pair-instability supernovae. In this paper we provide an overview of the survey's key measurements, specifications, goals, and prospects for new discovery.

astro-ph.GA↗

Beyond the bulge-halo conspiracy? Density profiles of Early-type galaxies from extended-source strong lensing

Observations suggest that the dark matter and stars in early-type galaxies `conspire' to produce a surprisingly simple distribution of total mass, $ρ(r)\proptoρ^{-γ}$, with $γ\approx2$. We measure the distribution of mass in 48 early-type galaxies that gravitationally lens a resolved background source. By fitting the source light in every pixel of images from the Hubble Space Telescope, we find a mean $\langleγ\rangle=2.075_{-0.024}^{+0.023}$ with intrinsic scatter between galaxies of $σ_γ=0.172^{+0.022}_{-0.032}$ for the overall sample. This is consistent with, and has similar precision to traditional techniques that employ spectroscopic observations to supplement lensing with mass estimates from stellar dynamics. Comparing measurements of $γ$ for individual lenses using both techniques, we find a statistically insignificant correlation of $-0.150^{+0.223}_{-0.217}$ between the two, indicating a lack of statistical power or deviations from a power-law density in certain lenses. At fixed surface mass density, we measure a redshift dependence, $\partial\langleγ\rangle/\partial z=0.345^{+0.322}_{-0.296}$, that is consistent with traditional techniques for the same sample of SLACS and GALLERY lenses. Interestingly, the consistency breaks down when we measure the dependence of $γ$ on the surface mass density of a lens galaxy. We argue that this is tentative evidence for an inflection point in the total-mass density profile at a few times the galaxy effective radius -- breaking the conspiracy.

astro-ph.GA↗

Automated galaxy-galaxy strong lens modelling: no lens left behind

The distribution of dark and luminous matter can be mapped around galaxies that gravitationally lens background objects into arcs or Einstein rings. New surveys will soon observe hundreds of thousands of galaxy lenses, and current, labour-intensive analysis methods will not scale up to this challenge. We instead develop a fully automatic, Bayesian method which we use to fit a sample of 59 lenses imaged by the Hubble Space Telescope in uniform conditions. We set out to \textit{leave no lens behind} and focus on ways in which automated fits fail in a small handful of lenses, describing adjustments to the pipeline that allows us to infer accurate lens models. Our pipeline ultimately fits {\em all} 59 lenses in our sample, with a high success rate key because catastrophic outliers would bias large samples with small statistical errors. Machine Learning techniques might further improve the two most difficult steps: subtracting foreground lens light and initialising a first, approximate lens model. After that, increasing model complexity is straightforward. We find a mean $\sim1\%$ measurement precision on the measurement of the Einstein radius across the lens sample which {\em does not degrade with redshift} up to at least $z=0.7$ -- in stark contrast to other techniques used to study galaxy evolution, like stellar dynamics. Our \texttt{PyAutoLens} software is open source, and is also installed in the Science Data Centres of the ESA Euclid mission.

astro-ph.CO↗