We report the discovery of two Einstein Crosses (ECs) in the footprint of the Kilo-Degree Survey (KiDS): KIDS J232940-340922 and KIDS J122456+005048. Using integral field spectroscopy from the Multi ...Unit Spectroscopic Explorer at the Very Large Telescope, we confirm their gravitational-lens nature. In both cases, the four spectra of the source clearly show a prominence of absorption features, hence revealing an evolved stellar population with little star formation. The lensing model of the two systems, assuming a singular isothermal ellipsoid (SIE) with external shear, shows that: (1) the two crosses, located at redshift z = 0.38 and 0.24, have Einstein radius RE = 5.2 kpc and 5.4 kpc, respectively; (2) their projected dark matter fractions inside the half effective radius are 0.60 and 0.56 (Chabrier initial mass function); (3) the sources are ultra-compact galaxies, Re ∼ 0.9 kpc (at redshift, zs = 1.59) and Re ∼ 0.5 kpc (zs = 1.10), respectively. These results are unaffected by the underlying mass density assumption. Due to size, blue color, and absorption-dominated spectra, corroborated by low specific star formation rates derived from optical-near-infrared spectral energy distribution fitting, we argue that the two lensed sources in these ECs are blue nuggets migrating toward their quenching phase.
The inner regions of active galaxies host the most extreme and energetic phenomena in the universe including, relativistic jets, supermassive black hole binaries, and recoiling supermassive black ...holes. However, many of these sources cannot be resolved with direct observations. I review how strong gravitational lensing can be used to elucidate the structures of these sources from radio frequencies up to very high energy gamma rays. The deep gravitational potentials surrounding galaxies act as natural gravitational lenses. These gravitational lenses split background sources into multiple images, each with a gravitationally-induced time delay. These time delays and positions of lensed images depend on the source location, and thus, can be used to infer the spatial origins of the emission. For example, using gravitationally-induced time delays improves angular resolution of modern gamma-ray instruments by six orders of magnitude (×106), and provides evidence that gamma-ray outbursts can be produced at even thousands of light years from a supermassive black hole, and that the compact radio emission does not always trace the position of the supermassive black hole. These findings provide unique physical information about the central structure of active galaxies, force us to revise our models of operating particle acceleration mechanisms, and challenge our assumptions about the origin of compact radio emission. Future surveys, including LSST, SKA, and Euclid, will provide observations for hundreds of thousands of gravitationally lensed sources, which will allow us to apply strong gravitational lensing to study the multi-wavelength structure for large ensembles of sources. This large ensemble of gravitationally lensed active galaxies will allow us to elucidate the physical origins of multi-wavelength emissions, their connections to supermassive black holes, and their cosmic evolution.
Abstract
In recent years, a crisis in the standard cosmology has been caused by inconsistencies in the measurements of some key cosmological parameters, the Hubble constant
H
0
and cosmic curvature ...parameter Ω
K
, for example. It is necessary to remeasure them with the cosmological model-independent methods. In this paper, based on the distance sum rule, we present such a way to constrain
H
0
and Ω
K
simultaneously in the late universe from strong gravitational lensing time-delay (SGLTD) data and gravitational wave (GW) standard siren data simulated from the future observation of the Einstein Telescope (ET). Based on the data for six currently observed SGLTDs, we find that the constraint precision of
H
0
from the combined 100 GW events can be comparable with the measurement from the SH0ES collaboration. As the number of GW events increases to 700, the constraint precision of
H
0
will exceed that of the Planck 2018 results. Considering 1000 GW events as the conservative estimation of ET in the 10 yr observation, we obtain
H
0
= 73.69 ± 0.36 km s
−1
Mpc
−1
with a 0.5% uncertainty and
Ω
K
=
0.076
−
0.087
+
0.068
. In addition, we simulate 55 strong gravitational lensing (SGL) systems with a 6.6% uncertainty for the measurement of time-delay distance. By combining with 1000 GWs, we infer that
H
0
= 73.65 ± 0.35 km s
−1
Mpc
−1
and Ω
K
= 0.008 ± 0.048. Our results suggest that this approach can play an important role in exploring cosmological tensions.
Strongly lensed quasar systems with time delay measurements provide "time delay distances," which are a combination of three angular diameter distances and serve as powerful tools to determine the ...Hubble constant H0. However, current results often rely on the assumption of the ΛCDM model. Here we use a model-independent method based on Gaussian process to directly constrain the value of H0. By using Gaussian process regression, we can generate posterior samples of unanchored supernova distances independent of any cosmological model and anchor them with strong lens systems. The combination of a supernova sample with large statistics but no sensitivity to H0 with a strong lens sample with small statistics but H0 sensitivity gives a precise H0 measurement without the assumption of any cosmological model. We use four well-analyzed lensing systems from the state-of-art lensing program H0LiCOW and the Pantheon supernova compilation in our analysis. Assuming the universe is flat, we derive the constraint H0 = 72.2 2.1 km s−1 Mpc−1, a precision of 2.9%. Allowing for cosmic curvature with a prior of k = −0.2, 0.2, the constraint becomes .
With the distance sum rule in the Friedmann-Lemaître-Robertson-Walker metric, model-independent constraints on both the Hubble constant H0 and spatial curvature can be obtained using strong lensing ...time-delay data and Type Ia supernovae (SNe Ia) luminosity distances. This method is limited by the relatively low redshifts of SNe Ia, however. Here, we propose using quasars as distance indicators, extending the coverage to encompass the redshift range of strong lensing systems. We provide a novel and improved method of determining H0 and simultaneously. By applying this technique to the time-delay measurements of seven strong lensing systems and the known ultraviolet versus X-ray luminosity correlation of quasars, we constrain the possible values of both H0 and , and find that km and . The measured is consistent with zero spatial curvature, indicating that there is no significant deviation from a flat universe. If we use flatness as a prior, we infer that km , representing a precision of 2.5%. If we further combine these data with the 1048 current Pantheon SNe Ia, our model-independent constraints can be further improved to km and . In every case, we find that the Hubble constant measured with this technique is strongly consistent with the value (∼74 km ) measured using the local distance ladder, as opposed to the value optimized by Planck.
Abstract
We assemble a large comprehensive sample of 2534
z
∼ 2, 3, 4, 5, 6, 7, 8, and 9 galaxies lensed by the six clusters from the Hubble Frontier Fields (HFF) program. Making use of the ...availability of multiple independent magnification models for each of the HFF clusters and alternatively treating one of the models as the “truth,” we show that the median magnification factors from the v4 parametric models are typically reliable to values of 30–50, and in one case to 100. Using the median magnification factor from the latest v4 models, we estimate the UV luminosities of the 2534 lensed
z
∼ 2–9 galaxies, finding sources as faint as −12.4 mag at
z
∼ 3 and −12.9 mag at
z
∼ 7. We explicitly demonstrate the power of the surface density–magnification relations Σ(
z
) versus
μ
in the HFF clusters to constrain both distant galaxy properties and cluster lensing properties. Based on the Σ(
z
) versus
μ
relations, we show that the median magnification estimates from existing public models must be reliable predictors of the true magnification
μ
to
μ
< 15 (95% confidence). We also use the observed Σ(
z
) versus
μ
relations to derive constraints on the evolution of the luminosity function faint-end slope from
z
∼ 7 to
z
∼ 2, showing that faint-end slope results can be consistent with blank-field studies if, and only if, the selection efficiency shows no strong dependence on the magnification factor
μ
. This can only be the case if very low-luminosity galaxies are very small, being unresolved in deep lensing probes.
Abstract
Exploiting the fundamentally achromatic nature of gravitational lensing, we present a lens model for the massive galaxy cluster SMACS J0723.3−7323 (SMACS J0723;
z
= 0.388) that significantly ...improves upon earlier work. Building on strong-lensing constraints identified in prior Hubble Space Telescope (HST) observations, the mass model utilizes 21 multiple-image systems, 17 of which were newly discovered in Early Release Observation data from the JWST. The resulting lens model maps the cluster mass distribution to an rms spatial precision of 0.″32, and is publicly available. Consistent with previous analyses, our study shows SMACS J0723.3 to be well described by a single large-scale component centered on the location of the brightest cluster galaxy. However, satisfying all lensing constraints provided by the JWST data, the model points to the need for the inclusion of an additional, diffuse component west of the cluster. A comparison of the galaxy, mass, and gas distributions in the core of SMACS J0723 based on HST, JWST, and Chandra data reveals a concentrated regular elliptical profile along with tell-tale signs of a recent merger, possibly proceeding almost along our line of sight. The exquisite sensitivity of JWST’s NIRCam reveals in spectacular fashion both the extended intracluster light distribution and numerous star-forming clumps in magnified background galaxies. The high-precision lens model derived here for SMACS J0723 demonstrates the unprecedented power of combining HST and JWST data for studies of structure formation and evolution in the distant universe.
Abstract
Detecting substructure within strongly lensed images is a promising route to shed light on the nature of dark matter. However, it is a challenging task, which traditionally requires detailed ...lens modeling and source reconstruction, taking weeks to analyze each system. We use machine learning to circumvent the need for lens and source modeling and develop a neural network to both locate subhalos in an image as well as determine their mass using the technique of image segmentation. The network is trained on images with a single subhalo located near the Einstein ring across a wide range of apparent source magnitudes. The network is then able to resolve subhalos with masses
m
≳ 10
8.5
M
⊙
. Training in this way allows the network to learn the gravitational lensing of light, and, remarkably, it is then able to detect entire populations of substructure, even for locations further away from the Einstein ring than those used in training. Over a wide range of the apparent source magnitude, the false-positive rate is around three false subhalos per 100 images, coming mostly from the lightest detectable subhalo for that signal-to-noise ratio. With good accuracy and a low false-positive rate, counting the number of pixels assigned to each subhalo class over multiple images allows for a measurement of the subhalo mass function (SMF). When measured over three mass bins from 10
9
–10
10
M
⊙
the SMF slope is recovered with an error of 36% for 50 images, and this improves to 10% for 1000 images with Hubble Space Telescope-like noise.
Abstract
In the past few years, approximate Bayesian Neural Networks (BNNs) have demonstrated the ability to produce statistically consistent posteriors on a wide range of inference problems at ...unprecedented speed and scale. However, any disconnect between training sets and the distribution of real-world objects can introduce bias when BNNs are applied to data. This is a common challenge in astrophysics and cosmology, where the unknown distribution of objects in our universe is often the science goal. In this work, we incorporate BNNs with flexible posterior parameterizations into a hierarchical inference framework that allows for the reconstruction of population hyperparameters and removes the bias introduced by the training distribution. We focus on the challenge of producing posterior PDFs for strong gravitational lens mass model parameters given Hubble Space Telescope–quality single-filter, lens-subtracted, synthetic imaging data. We show that the posterior PDFs are sufficiently accurate (statistically consistent with the truth) across a wide variety of power-law elliptical lens mass distributions. We then apply our approach to test data sets whose lens parameters are drawn from distributions that are drastically different from the training set. We show that our hierarchical inference framework mitigates the bias introduced by an unrepresentative training set’s interim prior. Simultaneously, we can precisely reconstruct the population hyperparameters governing our test distributions. Our full pipeline, from training to hierarchical inference on thousands of lenses, can be run in a day. The framework presented here will allow us to efficiently exploit the full constraining power of future ground- and space-based surveys (https://github.com/swagnercarena/ovejero).
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