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AtLAST -- Determination of Halo Mass Density Profiles at kpc Scales through Magnification Bias

Joaquín González-Nuevo, Laura Bonavera, Juan Alberto Cano, David Crespo, Rebeca Fernández-Fernández, Valentina Franco, Marcos M. Cueli, José Manuel Casas, Tony Mroczkowski, Caludia Ciccone, Evanthia Hatziminaoglou, Hugo Messias

TL;DR

Magnification bias provides a shape-independent probe of halo mass density profiles down to the $1$–$10$ kpc scale, enabling sub-$10$ kpc measurements that are challenging for shear. The paper argues that AtLAST—a 50 m submm telescope with wide-area mapping, high astrometric precision, and broad $30$–$950$ GHz coverage—can unlock this technique by delivering dense SMG catalogs and precise lens-source cross-correlations across many halos. It outlines three core science goals (inner halo profiles, anomalies due to massive satellites in less massive clusters, and splashback radii) and details the technical requirements needed to achieve robust, high-SNR measurements. By enabling large, homogeneous magnification-bias surveys, the work positions magnification bias as a precision tool for small-scale cosmology and tests of dark matter physics.

Abstract

Magnification bias, the lensing-induced modification of background source number counts, provides a uniquely powerful probe of the mass density profiles of galaxies and clusters down to kpc scales. Unlike shear-based weak lensing, magnification bias does not rely on galaxy shapes and thus avoids dominant small-scale systematics. Existing studies, however, are limited by sky coverage, positional uncertainty, and insufficiently deep, confusion-limited submillimetre (submm) surveys. A next-generation wide-field, high-throughput submm facility like the proposed 50m-telescope AtLAST is required to unlock this technique's full diagnostic power.

AtLAST -- Determination of Halo Mass Density Profiles at kpc Scales through Magnification Bias

TL;DR

Magnification bias provides a shape-independent probe of halo mass density profiles down to the – kpc scale, enabling sub- kpc measurements that are challenging for shear. The paper argues that AtLAST—a 50 m submm telescope with wide-area mapping, high astrometric precision, and broad – GHz coverage—can unlock this technique by delivering dense SMG catalogs and precise lens-source cross-correlations across many halos. It outlines three core science goals (inner halo profiles, anomalies due to massive satellites in less massive clusters, and splashback radii) and details the technical requirements needed to achieve robust, high-SNR measurements. By enabling large, homogeneous magnification-bias surveys, the work positions magnification bias as a precision tool for small-scale cosmology and tests of dark matter physics.

Abstract

Magnification bias, the lensing-induced modification of background source number counts, provides a uniquely powerful probe of the mass density profiles of galaxies and clusters down to kpc scales. Unlike shear-based weak lensing, magnification bias does not rely on galaxy shapes and thus avoids dominant small-scale systematics. Existing studies, however, are limited by sky coverage, positional uncertainty, and insufficiently deep, confusion-limited submillimetre (submm) surveys. A next-generation wide-field, high-throughput submm facility like the proposed 50m-telescope AtLAST is required to unlock this technique's full diagnostic power.

Paper Structure

This paper contains 3 sections, 2 figures.

Table of Contents

  1. Scientific context and motivation
  2. Science case
  3. Technical requirements

Figures (2)

  • Figure 1: Simulated stacking map showing the strong lensing effect and, in particular, the gap inside the Einstein ring.
  • Figure 1: Cross-correlation functions measured using the magnification bias of SMGs (red dots) showing the lensing gap around $10"$ and the oscillatory signal at larger angular scales. The blue dots are the renormalized mass density profile measured from the galaxy satellites distribution. The best NFW fit to the outer region is represented by a dashed black line. See Crespo et al. (2025) for more details.