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Journal article

First constraints from marked angular power spectra with Subaru Hyper Suprime-Cam Survey First-Year Data

Abstract:
We present the first application of marked power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto and cross-spectra improves constraints on the clustering amplitude parameter by 43 per cent compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on . We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. We note that some of the additional information introduced by the marked field originates from scales smaller than the scale cut, and is partly Gaussian in nature. This does not invalidate our systematic tests. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/mnras/stag033

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Physics - Central
Role:
Author
ORCID:
0000-0002-7228-6621
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Role:
Author
ORCID:
0000-0002-5795-7028
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Role:
Author
ORCID:
0000-0003-2911-9163
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Role:
Author
ORCID:
0000-0002-5845-3649


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Funder identifier:
https://ror.org/02ap3w078


Publisher:
Oxford University Press
Journal:
Monthly Notices of the Royal Astronomical Society More from this journal
Volume:
546
Issue:
2
Pages:
stag033
Article number:
stag033
Publication date:
2026-01-08
Acceptance date:
2025-01-03
DOI:
EISSN:
1365-2966
ISSN:
0035-8711


Language:
English
Keywords:
UUID:
uuid_32c9f3ba-4d75-45a6-9fc6-11e555db2c07
Source identifiers:
3702093
Deposit date:
2026-01-28
ARK identifier:
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