23 research outputs found
Constraining the dark matter particle mass through galaxy-galaxy strong gravitational lensing
We study several possible ways of constraining the dark matter particle mass through galaxy-galaxy strong gravitational lensing, where the key underlying idea is that a strong lens image could be perturbed by low-mass haloes that happen to be close to light-rays emitted from a background source galaxy. Under the Approximate Bayesian Computation framework, we develop a forward-modelling procedure aimed at directly placing constraints on the dark particle's thermal relic mass using a set of observations. We use mock images to demonstrate its ability to extract subhalo information from the power spectrum of image residuals and unbiasedly recover the input mass of the dark matter particles. We re-derive the number density of detectable intervening line-of-sight haloes relative to lens subhaloes in galaxy-galaxy strong lens observations. Unlike previous methods determining the detectability through fitting deflections or idealistic images, we regard a perturber as detectable only if adding it to a smooth model generates a statistically significant improvement in the reconstructed image. Our new results show that line-of-sight haloes are still important but, in most cases, no longer completely dominate detections over those of subhaloes. Finally, we study the effects on subhalo inference from the complexity of the lens through simulating mock lensed images with a lens from a high-resolution hydrodynamic simulation. We find that the commonly used lens model, a power-law profile, could wrongly infer the subhalo information if it cannot capture the non-elliptical features of the lens galaxy. We also consider a decomposed model for the lens mass, which separately models the stellar and dark matter mass. We find the decomposed model can successfully capture the complexity of the simulated galaxy and correctly infer the subhalo information
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 two
compelling DM subhalo candidates (including one previously found in
SLACS0946+1006), where a subhalo is favoured after every systematic test we
perform. We find that the detectability of subhalos depends upon the assumed
parametric form for the lens galaxy's mass distribution. Comparing fits which
assume several more complex mass models reveals additional (generally lower
mass) DM subhalo candidates worthy of further study, and the removal of 7 false
positives. We identify 38 non-detections, which are vital to building up enough
statistical power to test DM models. Future work will apply even more flexible
models to the results of this study, to constrain different DM models. Our full
analysis results are available at
https://github.com/Jammy2211/autolens_subhalo.Comment: 25 Pages, 15 Figure
Beyond the bulgeâhalo conspiracy? Density profiles of early-type galaxies from extended-source strong lensing
Observations suggest that the dark matter and stars in early-type galaxies âconspireâ to produce a surprisingly simple distribution of total mass, Ï(r) â ÏâÎł, with Îł â 2. 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 âšÎłâ©=2.075+0.023â0.024 with an intrinsic scatter between galaxies of ÏÎł=0.172+0.022â0.032 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 Îł for individual lenses using both techniques, we find a statistically insignificant correlation of â0.150+0.223â0.217 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, ââšÎłâ©/z=0.345+0.322â0.296â , that is consistent with traditional techniques for the same sample of Sloan Lens ACS and GALaxy-Lyα EmitteR sYstems (GALLERY) lenses. Interestingly, the consistency breaks down when we measure the dependence of Îł 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 â breaking the conspiracy
Strong gravitational lensingâs âexternal shearâ is not shear
The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power-law plus âexternal shearâ, which notionally accounts for neighbouring galaxies and cosmic shear along our line of sight. A small amount of external shear could come from these sources, but we show that the vast majority does not. Except in a handful of rare systems, the best-fitting values do not correlate with independent measurements of line-of-sight 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 external shear is aligned with the major or minor axis of 88 per cent of lens galaxies; and the amplitude of the external shear increases if that galaxy is discy. We conclude that âexternal shearâ 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
A forward-modelling method to infer the dark matter particle mass from strong gravitational lenses
A fundamental prediction of the cold dark matter (CDM) model of structure formation is the existence of a vast population of dark matter haloes extending to subsolar masses. By contrast, other dark matter models, such as a warm thermal relic (WDM), predict a cutoff in the mass function at a mass which, for popular models, lies approximately between 107 and 1010Mââ . We use mock observations to demonstrate the viability of a forward modelling approach to extract information about low-mass dark haloes lying along the line of sight to galaxyâgalaxy strong lenses. This can be used to constrain the mass of a thermal relic dark matter particle, mDM. With 50 strong lenses at Hubble Space Telescope resolution and a maximum pixel signal-to-noise ratio of âŒ50, the expected median 2Ï constraint for a CDM-like model (with a halo mass cutoff at 107Mââ ) is mDM>4.10keV (50 perâcent chance of constraining mDM to be better than 4.10 keV). If, however, the dark matter is a warm particle of mDM=2.2keVâ , our âapproximate Bayesian computationâ method would result in a median estimate of mDM between 1.43 and 3.21 keV. Our method can be extended to the large samples of strong lenses that will be observed by future telescopes and could potentially rule out the standard CDM model of cosmogony. To aid future survey design, we quantify how these constraints will depend on data quality (spatial resolution and integration time) as well as on the lensing geometry (source and lens redshifts)
Jammy2211/PyAutoGalaxy: October 2023 (2023.10.23.3)
<ul>
<li>Support for Python 3.11 by updating requirement on core libraries (e.g. <code>numpy</code>, <code>scipy</code>, <code>scikit-learn</code>).</li>
<li>Fix issues with sqlite database following switch from <code>.pickle</code> outputs to <code>.json</code> / <code>.fits</code> / <code>.csv</code>.</li>
<li>Database use of <code>Samples</code> object much more efficient.</li>
<li>Methods to output classes to hard-disk (e.g. <code>output_to_json</code>, <code>from_json</code>, <code>to_dict</code>) are now all handled and called from <code>autoconf</code>.</li>
<li>Fix bug where <code>nautilus</code> parallel fits sometimes crashed.</li>
<li>Fix bug where <code>nautilus</code> single CPU fits did not work.</li>
</ul>
Halo concentration strengthens dark matter constraints in galaxy-galaxy strong lensing analyses
A defining prediction of the cold dark matter cosmological model is the existence of a very large population of low-mass haloes. This population is absent in models in which the dark matter particle is warm (WDM). These alternatives can, in principle, be distinguished observationally because haloes along the line of sight can perturb galaxyâgalaxy strong gravitational lenses. Furthermore, the WDM particle mass could be deduced because the cut-off in their halo mass function depends on the mass of the particle. We systematically explore the detectability of low-mass haloes in WDM models by simulating and fitting mock lensed images. Contrary to previous studies, we find that haloes are harder to detect when they are either behind or in front of the lens. Furthermore, we find that the perturbing effect of haloes increases with their concentration: Detectable haloes are systematically high-concentration haloes, and accounting for the scatter in the massâconcentration relation boosts the expected number of detections by as much as an order of magnitude. Haloes have lower concentration for lower particle masses and this further suppresses the number of detectable haloes beyond the reduction arising from the lower halo abundances alone. Taking these effects into account can make lensing constraints on the value of the mass function cut-off at least an order of magnitude more stringent than previously appreciated
Constraining the inner density slope of massive galaxy clusters
We determine the inner density profiles of massive galaxy clusters (M200 > 5 Ă 1014 Mâ) in the Cluster-EAGLE (C-EAGLE) hydrodynamic simulations, and investigate whether the dark matter density profiles can be correctly estimated from a combination of mock stellar kinematical and gravitational lensing data. From fitting mock stellar kinematics and lensing data generated from the simulations, we find that the inner density slopes of both the total and the dark matter mass distributions can be inferred reasonably well. We compare the density slopes of C-EAGLE clusters with those derived by Newman et al. for 7 massive galaxy clusters in the local Universe. We find that the asymptotic best-fit inner slopes of âgeneralizedâ NFW (gNFW) profiles, ÎłgNFW, of the dark matter haloes of the C-EAGLE clusters are significantly steeper than those inferred by Newman et al. However, the mean mass-weighted dark matter density slopes of the simulated clusters are in good agreement with the Newan et al. estimates. We also find that the estimate of ÎłgNFW is very sensitive to the constraints from weak lensing measurements in the outer parts of the cluster and a bias can lead to an underestimate of ÎłgNFW
Galaxyâgalaxy strong lens perturbations: line-of-sight haloes versus lens subhaloes
We rederive the number density of intervening line-of-sight haloes relative to lens subhaloes in galaxy-galaxy strong lensing observations, where these perturbers can generate detectable image fluctuations. Previous studies have calculated the detection limit of a line-of-sight small-mass dark halo by comparing the lensing deflection angles it would cause, to those caused by a subhalo within the lens. However, this overly simplifies the difference in observational consequences between a subhalo and a line-of-sight halo. Furthermore, it does not take into account degeneracies between an extra subhalo and the uncertain properties of the main lens. More in keeping with analyses of real-world observations, we regard a line-of-sight halo as detectable only if adding it to a smooth model generates a statistically significant improvement in the reconstructed image. We find that the number density of detectable line-of-sight perturbers has been overestimated by as much as a factor of two in the previous literature. For typical lensing geometries and configurations, very deep imaging is sensitive to twice as many line-of-sight perturbers as subhaloes, but moderate depth imaging is sensitive to only slightly more line-of-sight perturbers than subhaloes