Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2208.14020

A state-of-the-art strong lensing model of MACS J0416.1-2403 with the largest sample of spectroscopic multiple images

P. Bergamini·C. Grillo·P. Rosati·E. Vanzella·U. Mestric·A. Mercurio·A. Acebron·G. B. Caminha·G. Granata·M. Meneghetti·G. Angora·M. Nonino
View original source ↗Read source document ↗Export metadata ↓

Abstract

The combination of multi-band imaging from HST with MUSE integral field spectroscopy, obtained at the VLT, has recently driven remarkable progress in strong lensing (SL) modeling of galaxy clusters. From a few tens of multiple images with photometric redshifts per cluster, a new generation of high-precision SL models have recently been developed, by exploiting in some cases over a hundred of spectroscopically confirmed multiple images and cluster member galaxies. A further step forward is expected with JWST observations of SL clusters (from hundreds to possibly a thousand of multiple images). In this context, we present a new, state-of-the-art SL model of the galaxy cluster MACS J0416.1-2403, utilizing 237 spectroscopically confirmed multiple images, which is the largest sample of secure multiply lensed sources utilized to date. This model incorporates stellar kinematics information of 64 cluster galaxies and the hot-gas mass distribution of the cluster determined from Chandra X-ray observations. The observed positions of the many multiple images are reproduced with a remarkable accuracy of 0.43 arcsec. To further assess the reliability of this lens model and to highlight the improvement over previously published models, we show the extended surface brightness reconstruction of several lensed galaxies through a newly developed forward modeling software. The comparison with other SL models of the same cluster demonstrates that this new model is better suited to accurately reproduce the positions, shapes and fluxes of the observed multiple images. Besides a robust characterization of the total mass distribution of the cluster, our model can provide accurate and precise magnification maps that are key to studying the intrinsic physical properties of faint, high-redshift lensed sources. The model is made publicly available through our newly developed Strong Lensing Online Tool (or SLOT).

Explore related subjects

astro-ph.CO

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

P. Bergamini, C. Grillo, P. Rosati, E. Vanzella, U. Mestric, A. Mercurio, A. Acebron, G. B. Caminha, G. Granata, M. Meneghetti, G. Angora, M. Nonino. 2023-02-08. A state-of-the-art strong lensing model of MACS J0416.1-2403 with the largest sample of spectroscopic multiple images. https://doi.org/10.1051/0004-6361%2F202244834

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Constraints on the Thomson optical depth to the CMB from the Lyman-$α$ forest

We present the first constraints on the electron optical depth to reionization, $τ_{\mathrm{e}}$, from the Lyman-$α$ forest alone for physically motivated reionization models that match the reionization's end-point, $z_{\rm{end}}$, required by the same astrophysical probe, and for symmetric reionization models with fixed duration, $Δz$, commonly adopted in CMB reionization analyses. Compared to traditional estimates from the latter, the Lyman-$α$ forest traces the ionization state of the IGM through its coupling with the thermal state. We find an explicit mapping between the two solving the chemistry and temperature evolution equations for hydrogen and helium. Our results yield $τ_{\mathrm{e}}$=$0.040^{+0.042}_{-0.018}$ (95\% C.L) and $τ_{\mathrm{e}}$=$0.041^{+0.028}_{-0.017}$ for reionization models with $z_{\rm{end}}$ and $Δz$-fixed, respectively. With mock Lyman-$α$ forest data that mimics the precision of future larger quasar sample datasets, we would potentially obtain tighter $τ_{\mathrm{e}}$ constraints, paving the way for CMB-independent constraints on the epoch of reionization from a large-scale structure probe.

astro-ph.CO↗
arXiv2026

Non-minimally Coupled Running Curvaton for DESI-motivated Dynamical Dark Energy

Recent DESI BAO data combined with CMB and supernova measurements suggest a dynamical dark energy that can cross the phantom divide. We show that introducing a non-minimal coupling $ξχ^2R$ to the running-curvaton framework allows a single field to drive early-universe curvature perturbations and late-time phantom-crossing cosmic acceleration without ghost instabilities. Using MCMC background likelihoods with DESI DR2 BAO, Pantheon+ SNe, and a reduced CMB prior, we constrain the cosmological parameters: $H_0 = 67.88^{+0.53}_{-0.61}\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $Ω_m = 0.3072^{+0.0059}_{-0.0054}$, $w_0 = -0.922^{+0.055}_{-0.063}$, and $w_a = -0.205^{+0.173}_{-0.182}$. Parameter degeneracies leave the coupling constants weakly constrained, highlighting the need for full perturbation-level analysis using CMB spectra and lensing.

astro-ph.CO↗
arXiv2026

On the Relation Between Field-Level Posteriors, Correlators, and their Likelihoods

We develop a field-level posterior for cosmological data by marginalizing over initial conditions and noise in a general forward model. While our focus is on large-scale structure data, the results generalize to any weakly non-Gaussian observable. Moreover, the construction is non-perturbative with respect to the forward model and applies equally well to perturbative calculations, simulation-based predictions, and more general effective descriptions. Expanding the FLP around its Gaussian limit, we derive a general expression for the Fisher matrix and reorganize the field-level information into contributions associated with the connected correlators of the evolved field. This makes explicit which terms are captured by likelihood analyses based on the power spectrum, the bispectrum, or finite sets of summary statistics, and which are lost under compression. We recover the standard Gaussian-covariance result for the power spectrum, show that the Gaussian bispectrum likelihood reproduces the corresponding field-level contribution, and show how cross-covariances among summaries progressively reconstruct more of the full field-level information. As an application to the BAO scale, we show how the field contains all the information required for its optimal reconstruction in the presence of noise, and identify the contributions in the FLP needed to attain this limit. We also show that the reconstruction of the initial field arises naturally as a byproduct of our approach, yielding the optimal estimate of the initial conditions given the data and the noise. Our results provide a unified framework to compare field-level and correlator-based inference, to quantify the information loss induced by compression, and to explore the role of stochasticity.

astro-ph.CO↗