Searcharxiv⌕ Search

arXiv · 2609.31944

SLICE: Unveiling the Multi-Component Merging Core of SPT-CLJ1150-2805 Through Strong-Lensing Mass Modelling

Abstract

We present a new strong-lensing and X-ray mass model of the merging galaxy cluster SPT-CLJ1150-2805 ($z=0.383$), combining JWST NIRCam, HST, Chandra, and VLT/MUSE data to robustly decompose its collisionless and collisional components. Exploiting JWST, we expand the multiple-image catalogue with 66 new images (30 comprising 6 new systems). Our baseline model uses 118 spectroscopically confirmed images from 20 systems, achieving an image-plane root-mean-square offset of $0.56''$. An expanded model incorporating 31 additional photometric images from 8 additional systems yields a near-identical mass distribution, confirming excellent model stability. We resolve a complex multi-axis post-merger system requiring five cluster-scale dark matter haloes, including a bimodal core with distinct haloes coincident with each brightest cluster galaxy. The remaining mass components are independently supported by kinematics of 291 cluster members ($σ_v=1960^{+84}_{-92}$ km s$^{-1}$), which reveal two new galaxy substructures - the northernmost of which we tentatively identify as the baryonic counterpart to our fifth dark matter halo. The cluster is an extraordinarily efficient lens, possessing an effective Einstein radius $θ_E=42.41^{+0.05}_{-0.04}{''}$ and an enclosed mass $M(<θ_E)=3.35^{+0.04}_{-0.03}\times10^{14}M_\odot$ for a source at $z_s=2$. For a high-redshift source at $z_s=9$, it produces a magnification cross-section of $A(>10)\simeq0.15$ arcmin$^2$ and $A(>30)\simeq0.020$ arcmin$^2$. This global lensing power surpasses all Hubble Frontier Fields clusters. In a regime where systematic uncertainties between mass models dominate high-redshift magnification errors, the stability of our reconstruction sets this lens apart. This combination of extreme lensing power and a robust mass model establishes SPT-CLJ1150-2805 as a premier cosmic telescope for high-redshift studies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

James R. Betts, Benjamin Beauchesne, Mathilde Jauzac, David Lagattuta, Guillaume Mahler, Jean-Paul Kneib, Gavin Leroy, Marceau Limousin, Priyamvada Natarajan, Sameeksha Saini, Keren Sharon, Stephane V. Werner, Catherine Cerny, Isaque Dutra, Dominique Eckert, Alaina Einsig, Michael D. Gladders, Gourav Khullarm, Manon Regamey. 2026-09-25. SLICE: Unveiling the Multi-Component Merging Core of SPT-CLJ1150-2805 Through Strong-Lensing Mass Modelling. https://arxiv.org/abs/2609.31944

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

KEEP EXPLORING

Related papers

Euclid Quick Data Release (Q1). The first Euclid view of Planck galaxy protocluster candidates at cosmic noon

[ABRIGED ABSTRACT] A large catalogue of candidate galaxy protoclusters with high star-formation rates was produced by the Planck collaboration. We search, in the first data release (Q1) of the Euclid survey, for the visible and infrared counterparts of the Planck galaxy protocluster candidates expected to be above $z > 1.5$. Eight of them are in Euclid Q1. Our goal is to investigate the optical nature of these overdensities previously detected in the submillimetre wavelength range. We search for overdensities using the DETECTIFz algorithm, an overdensity finder based on Delaunay tessellation that uses photometric redshift probability distributions through Monte Carlo simulations. Focusing our search on the eight high-star forming Planck protocluster candidates, we find that two of them have one Euclid counterpart, and six have between two and four Euclid counterparts, which amounts to a total of 20 Euclid counterparts. These Euclid counterparts lie at photometric redshifts $1.4<z_{\rm ph} < 2.7$ and 12 of them also have partial Herschel coverage. All detections have also been confirmed by at least one other independent protocluster detection algorithm. We study the colours, derived stellar masses and star-formation rates (SFRs) of the detected member galaxies of those protocluster candidate counterparts. We also estimate the total stellar masses, SFRs, and the halo mass lower limits for all Euclid protocluster candidates. We find that in the dark matter halo mass ($M_{\rm h}$) / redshift plane, these Planck and Euclid overdense regions lie in the region $12.6 <\log_{10} (M_{\rm h}/M_\odot)< 13.4$, $1.4<z< 2.7$. This means that the halos of our objects are expected to have experienced a transition between cold flows in hot media to accretion of hot material.

astro-ph.CO↗

CNN+FoF: application of deep learning to the identification of dark matter haloes

We present a deep-learning-based approach for identifying dark matter haloes in cosmological N-body simulations. Our framework consists of a volumetric Convolutional Neural Network to classify individual simulation particles as either halo or non-halo members, followed by a highly optimised and parallelised Friends-of-Friends clustering algorithm that groups the classified halo members into distinct haloes. The training data comprise simulations generated using GADGET-4, with labels obtained with the ROCKSTAR halo finder. Our models incorporate two main halo mass definitions, $M_{200\mathrm{b}}$ and $M_{\text{vir}}$, with similar performance. For haloes defined by the ROCKSTAR $M_{200\mathrm{b}}$ criterion, the classification network demonstrated stable performance across multiple simulation resolutions. For the highest resolution, it achieved over $98\%$ across all primary performance metrics when identifying halo particles. Furthermore, the FoF algorithm yielded halo catalogues with a purity generally exceeding $99\%$ and a stable completeness of $94\%$ for masses above $5\times10^{11} \, M_\odot$. Our pipeline recovered the centre-of-mass positions, velocities and halo masses with high fidelity, yielding a halo mass function consistent to within $5\%$ of the reference while faithfully reconstructing the internal density profiles. The primary objective of this study is to offer a faster and scalable alternative to conventional halo finders, achieving a speed-up of approximately one order of magnitude relative to ROCKSTAR. While traditional N-body simulations remain dominated by the time required to solve gravitational dynamics, this post-processing acceleration becomes essential when coupled with fast field-level emulators, offering a promising pathway towards efficient, end-to-end forward modelling in modern simulation-based inference.

astro-ph.CO↗

Impact of Stochastic Pop~III X-ray Binaries on the Cosmological 21-cm Signal

High-mass X-ray binaries are one of the primary drivers of the 21-cm signal from Cosmic Dawn and Reionization, playing a leading role in the thermal history of the intergalactic medium. In traditional semi-numerical simulations, a deterministic scaling relation between the total X-ray luminosity of high-mass X-ray binaries, $L_{\rm X}$, and star formation rate (SFR) is usually adopted. However, this assumption is inaccurate for high-redshift low-SFR regions hosting few sources. The spatial variation in the number and luminosity of these sources is expected to enhance fluctuations in the Cosmic Dawn 21-cm signal. Here we quantify this effect by introducing a stochastic $L_{\rm X}$ model sampled from a power-law X-ray luminosity function. Implementing this in \texttt{21cmSPACE}, a large-scale simulation framework of Cosmic Dawn and Reionization, and adopting a soft X-ray spectral energy distribution ($β=1.5$, $E_{\rm min}=0.1\,\mathrm{keV}$) that leads to a relatively strong stochastic signature, we find that the stochasticity leads to enhanced fluctuations in X-ray heating rate fields, and affects the 21-cm power spectrum on small scales ($k>0.3~ \mathrm{cMpc^{-1}}$). The impact of stochasticity on the global 21-cm signal and on the large-scale power spectrum is found to be negligible. Our results suggest these effects will remain undetected by the upcoming Square Kilometer Array. However, large-scale lunar-based experiments may be sensitive to the signatures of stochastic X-ray heating at $z\sim 25$. Quantifying these corrections is a vital step toward robust 21-cm modeling and ensuring that future precision data interpretation is free from astrophysical biases.

astro-ph.CO↗