Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063

ABSTRACT Mapping the small-scale structure of the universe through gravitational lensing is a promising tool for probing the particle nature of dark matter. Curved Arc Basis (CAB) has been proposed as a local lensing formalism in galaxy clusters, with the potential to detect low-mass dark matter substructure. In this work, we analyse the cluster lens Abell S1063 in search of dark matter substructure with the CAB formalism, using multiband imaging data from James Webb Space Telescope (JWST). We use two different source modelling methods: shapelets and pixel-based source reconstruction based on Delaunay triangulation. We find that source modelling systematics from shapelets result in a disagreement between CAB parameters measured from different filters. Source modelling with Delaunay significantly alleviates this systematic, as seen in the improvement in agreement across filters. We also find that inadequate complexity in source modelling can result in convincing spurious detections of dark matter substructure from strong gravitational lenses, as seen by our $\Delta \text{BIC} > 20$ measurement of a $M \sim 10^{10}$ ${\rm M}_{\odot }$ subhalo with shapelets, a spurious detection that is not reproduced with Delaunay source modelling. We demonstrate that multiband analysis with different JWST filters is key for disentangling source and lens model systematics from dark matter substructure detections.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-08-22
DOI
https://doi.org/10.1093/mnras/staf1366
Citations
4
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
4.77
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article

Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063

Atınç Çağan Şengül, Cora Dvorkin, Nino Ephremidze, Chandrika Chandrashekar
4 citations
Monthly Notices of the Royal Astronomical Society
Astronomy and Astrophysical Research
4.77
article

Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063

Atınç Çağan Şengül, Cora Dvorkin, Nino Ephremidze, Chandrika Chandrashekar
article en
4 citations

Abstract

ABSTRACT Mapping the small-scale structure of the universe through gravitational lensing is a promising tool for probing the particle nature of dark matter. Curved Arc Basis (CAB) has been proposed as a local lensing formalism in galaxy clusters, with the potential to detect low-mass dark matter substructure. In this work, we analyse the cluster lens Abell S1063 in search of dark matter substructure with the CAB formalism, using multiband imaging data from James Webb Space Telescope (JWST). We use two different source modelling methods: shapelets and pixel-based source reconstruction based on Delaunay triangulation. We find that source modelling systematics from shapelets result in a disagreement between CAB parameters measured from different filters. Source modelling with Delaunay significantly alleviates this systematic, as seen in the improvement in agreement across filters. We also find that inadequate complexity in source modelling can result in convincing spurious detections of dark matter substructure from strong gravitational lenses, as seen by our $\Delta \text{BIC} > 20$ measurement of a $M \sim 10^{10}$ ${\rm M}_{\odot }$ subhalo with shapelets, a spurious detection that is not reproduced with Delaunay source modelling. We demonstrate that multiband analysis with different JWST filters is key for disentangling source and lens model systematics from dark matter substructure detections.

Monthly Notices of the Royal Astronomical SocietyVol. 542(3)
Harvard University (US), University of Pittsburgh (US), Harvard University Press (US)
Openalex Percentile: Top 5%
Astronomy and Astrophysical Research
4.77
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Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063 — Atınç Çağan Şengül, Cora Dvorkin, et al. · Monthly Notices of the Royal Astronomical Society (2025) | TGRS Research Map | TGRS