Extensive Spectroscopic Information Research Articles

Searching for strong galaxy-scale lenses in galaxy clusters with deep networks

Strong galaxy-scale lenses in galaxy clusters provide a unique tool with which to investigate the inner mass distribution of these clusters and the subhalo density profiles in the low-mass regime, which can be compared with predictions from ΛCDM cosmological simulations. We search for galaxy–galaxy strong-lensing systems in theHubbleSpace Telescope (HST) multi-band imaging of galaxy cluster cores by exploring the classification capabilities of deep learning techniques. Convolutional neural networks (CNNs) are trained utilising highly realistic simulations of galaxy-scale strong lenses injected into the HST cluster fields around cluster members (CLMs). To this aim, we take advantage of extensive spectroscopic information available in 16 clusters and accurate knowledge of the deflection fields in half of these from high-precision strong-lensing models. Using observationally based distributions, we sample the magnitudes (down toF814W = 29 AB), redshifts, and sizes of the background galaxy population. By placing these sources within the secondary caustics associated with the cluster galaxies, we build a sample of approximately 3000 strong galaxy–galaxy lenses, which preserve the full complexity of real multi-colour data and produce a wide diversity of strong-lensing configurations. We study two deep learning networks, processing a large sample of image cutouts, in three bands, acquired by HST Advanced Camera for Survey (ACS), and we quantify their classification performance using several standard metrics. We find that both networks achieve a very good trade-off between purity and completeness (85%–95%), as well as a good stability, with fluctuations within 2%–4%. We characterise the limited number of false negatives (FNs) and false positives (FPs) in terms of the physical properties of the background sources (magnitudes, colours, redshifts, and effective radii) and CLMs (Einstein radii and morphology). We also demonstrate the high degree of generalisation of the neural networks by applying our method to HST observations of 12 clusters with previously known galaxy-scale lensing systems.

The search for galaxy cluster members with deep learning of panchromatic HST imaging and extensive spectroscopy

Context.The next generation of extensive and data-intensive surveys are bound to produce a vast amount of data, which can be efficiently dealt with using machine-learning and deep-learning methods to explore possible correlations within the multi-dimensional parameter space.Aims.We explore the classification capabilities of convolution neural networks (CNNs) to identify galaxy cluster members (CLMs) by usingHubbleSpace Telescope (HST) images of fifteen galaxy clusters at redshift 0.19 ≲ z ≲ 0.60, observed as part of the CLASH andHubbleFrontier Field programmes.Methods.We used extensive spectroscopic information, based on the CLASH-VLT VIMOS programme combined with MUSE observations, to define the knowledge base. We performed various tests to quantify how well CNNs can identify cluster members on ht basis of imaging information only. Furthermore, we investigated the CNN capability to predict source memberships outside the training coverage, in particular, by identifying CLMs at the faint end of the magnitude distributions.Results.We find that the CNNs achieve a purity-completeness rate ≳90%, demonstrating stable behaviour across the luminosity and colour of cluster galaxies, along with a remarkable generalisation capability with respect to cluster redshifts. We concluded that if extensive spectroscopic information is available as a training base, the proposed approach is a valid alternative to catalogue-based methods because it has the advantage of avoiding photometric measurements, which are particularly challenging and time-consuming in crowded cluster cores. As a byproduct, we identified 372 photometric cluster members, with mag(F814) < 25, to complete the sample of 812 spectroscopic members in four galaxy clusters RX J2248-4431, MACS J0416-2403, MACS J1206-0847 and MACS J1149+2223.Conclusions.When this technique is applied to the data that are expected to become available from forthcoming surveys, it will be an efficient tool for a variety of studies requiring CLM selection, such as galaxy number densities, luminosity functions, and lensing mass reconstruction.

Strong lensing models of eight CLASH clusters from extensive spectroscopy: Accurate total mass reconstructions in the cores

We carried out a detailed strong lensing analysis of a sub-sample of eight galaxy clusters of the Cluster Lensing And Supernova survey with Hubble (CLASH) in the redshift range of zcluster = [0.23 − 0.59] using extensive spectroscopic information, primarily from the Multi Unit Spectroscopic Explorer (MUSE) archival data and complemented with CLASH-VLT redshift measurements. The observed positions of the multiple images of strongly lensed background sources were used to constrain parametric models describing the cluster total mass distributions. Different models were tested in each cluster depending on the complexity of its mass distribution and on the number of detected multiple images. Four clusters show more than five spectroscopically confirmed multiple image families. In this sample, we did not make use of families that are only photometrically identified in order to reduce model degeneracies between the values of the total mass of a cluster source redshifts, in addition to systematics due to the potential misidentifications of multiple images. For the remaining four clusters, we used additional families without any spectroscopic confirmation to increase the number of strong lensing constraints up to the number of free parameters in our parametric models. We present spectroscopic confirmation of 27 multiply lensed sources, with no previous spectroscopic measurements, spanning over the redshift range of zsrc = [0.7 − 6.1]. Moreover, we confirm an average of 48 galaxy members in the core of each cluster thanks to the high efficiency and large field of view of MUSE. We used this information to derive precise strong lensing models, projected total mass distributions, and magnification maps. We show that, despite having different properties (i.e. number of mass components, total mass, redshift, etc.), the projected total mass and mass density profiles of all clusters have very similar shapes when rescaled by independent measurements of M200c and R200c. Specifically, we measured the mean value of the projected total mass of our cluster sample within 10 (20)% of R200c to be 0.13 (0.32) of M200c, with a remarkably small scatter of 5 (6)%. Furthermore, the large number of high-z sources and the precise magnification maps derived in this work for four clusters add up to the sample of high-quality gravitational telescopes to be used to study the faint and distant Universe.

Measuring the Value of the Hubble Constant “à la Refsdal”

Abstract Realizing Refsdal’s original idea from 1964, we present estimates of the Hubble constant that are complementary to, and potentially competitive with, those of other cosmological probes. We use the observed positions of 89 multiple images, with extensive spectroscopic information, from 28 background sources and the measured time delays between the images S1–S4 and SX of supernova “Refsdal” (z = 1.489), which were obtained thanks to Hubble Space Telescope deep imaging and Multi Unit Spectroscopic Explorer data. We extend the strong-lensing modeling of the Hubble Frontier Fields galaxy cluster MACS J1149.5+2223 (z = 0.542), published by Grillo et al. (2016), and explore different ΛCDM models. Taking advantage of the lensing information associated to the presence of very close pairs of multiple images at various redshifts, and to the extended surface brightness distribution of the SN Refsdal host, we can reconstruct the total mass-density profile of the cluster very precisely. The combined dependence of the multiple-image positions and time delays on the cosmological parameters allows us to infer the values of H 0 and Ωm with relative (1σ) statistical errors of, respectively, 6% (7%) and 31% (26%) in flat (general) cosmological models, assuming a conservative 3% uncertainty on the final time delay of image SX and, remarkably, no priors from other cosmological experiments. Our best estimate of H 0, based on the model described in this work, will be presented when the final time-delay measurement becomes available. Our results show that it is possible to utilize time delays in lens galaxy clusters as an important alternative tool for measuring the expansion rate and the geometry of the universe.

CLASH-VLT: A highly precise strong lensing model of the galaxy cluster RXC J2248.7−4431 (Abell S1063) and prospects for cosmography

We perform a comprehensive study of the total mass distribution of the galaxy cluster RXCJ2248 ($z=0.348$) with a set of high-precision strong lensing models, which take advantage of extensive spectroscopic information on many multiply lensed systems. In the effort to understand and quantify inherent systematics in parametric strong lensing modelling, we explore a collection of 22 models where we use different samples of multiple image families, parametrizations of the mass distribution and cosmological parameters. As input information for the strong lensing models, we use the CLASH HST imaging data and spectroscopic follow-up observations, carried out with the VIMOS and MUSE spectrographs, to identify bona-fide multiple images. A total of 16 background sources, over the redshift range $1.0-6.1$, are multiply lensed into 47 images, 24 of which are spectroscopically confirmed and belong to 10 individual sources. The cluster total mass distribution and underlying cosmology in the models are optimized by matching the observed positions of the multiple images on the lens plane. We show that with a careful selection of a sample of spectroscopically confirmed multiple images, the best-fit model reproduces their observed positions with a rms of $0.3$ in a fixed flat $\Lambda$CDM cosmology, whereas the lack of spectroscopic information lead to biases in the values of the model parameters. Allowing cosmological parameters to vary together with the cluster parameters, we find (at $68\%$ confidence level) $\Omega_m=0.25^{+0.13}_{-0.16}$ and $w=-1.07^{+0.16}_{-0.42}$ for a flat $\Lambda$CDM model, and $\Omega_m=0.31^{+0.12}_{-0.13}$ and $\Omega_\Lambda=0.38^{+0.38}_{-0.27}$ for a universe with $w=-1$ and free curvature. Using toy models mimicking the overall configuration of RXCJ2248, we estimate the impact of the line of sight mass structure on the positional rms to be $0.3\pm 0.1$.(ABRIDGED)

CLASH-VLT: INSIGHTS ON THE MASS SUBSTRUCTURES IN THE FRONTIER FIELDS CLUSTER MACS J0416.1–2403 THROUGH ACCURATE STRONG LENS MODELING

We present a detailed mass reconstruction and a novel study on the substructure properties in the core of the CLASH and Frontier Fields galaxy cluster MACS J0416.1-2403. We show and employ our extensive spectroscopic data set taken with the VIMOS instrument as part of our CLASH-VLT program, to confirm spectroscopically 10 strong lensing systems and to select a sample of 175 plausible cluster members to a limiting stellar mass of log(M_*/M_Sun) ~ 8.6. We reproduce the measured positions of 30 multiple images with a remarkable median offset of only 0.3" by means of a comprehensive strong lensing model comprised of 2 cluster dark-matter halos, represented by cored elliptical pseudo-isothermal mass distributions, and the cluster member components. The latter have total mass-to-light ratios increasing with the galaxy HST/WFC3 near-IR (F160W) luminosities. The measurement of the total enclosed mass within the Einstein radius is accurate to ~5%, including systematic uncertainties. We emphasize that the use of multiple-image systems with spectroscopic redshifts and knowledge of cluster membership based on extensive spectroscopic information is key to constructing robust high-resolution mass maps. We also produce magnification maps over the central area that is covered with HST observations. We investigate the galaxy contribution, both in terms of total and stellar mass, to the total mass budget of the cluster. When compared with the outcomes of cosmological $N$-body simulations, our results point to a lack of massive subhalos in the inner regions of simulated clusters with total masses similar to that of MACS J0416.1-2403. Our findings of the location and shape of the cluster dark-matter halo density profiles and on the cluster substructures provide intriguing tests of the assumed collisionless, cold nature of dark matter and of the role played by baryons in the process of structure formation.

Investigation of shape changes in 87Mo

The level scheme of 87Mo was investigated with the reaction 58Ni( 32S, 2pn) at projectile energies of 110–130 MeV and the reaction 40Ca( 50Cr, 2pn) at 170 MeV. Extensive spectroscopic information was collected including γγ and neutron-gated γγ coincidences as well as coincidences with identified 87Mo residues. Level lifetimes were studied with the RDDS and DSA methods. The angular distributions of low-lying transitions were measured. The results indicate a sudden transition from single-particle-like to collective behavior which is caused by g 9 2 particle alignment. The level scheme was constructed up to 12 MeV excitation energy and a probable spin of 40 2 h ̵ .

Observations of the Two-Level Structure of Sunspot Magnetic Fields

Inhomogeneity of magnetic field structure, ‘granulation’ in sunspot umbrae and fine structure of the Evershed motions lead to the conclusion that the sunspot umbra is composed of magnetic ropes (or plaits) with dimensions near the limit of resolution. Progress in the study of these ropes is closely connected with the possibility of obtaining extensive spectroscopic information about some selected regions on the solar disc. It is extremely interesting to obtain a picture of short-time-scale variations of the magnetic field strength and the radial velocity field in connection with the transfer of energy from the photosphere to the upper layers of the solar atmosphere (chromosphere, corona).