KiDS-Legacy: Angular galaxy clustering from deep surveys with complex selection effects

¹ Ruhr University Bochum, Faculty of Physics and Astronomy, Astronomical Institute (AIRUB), German Centre for Cosmological Lensing, 44780 Bochum, Germany
² Institute for Theoretical Physics, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands
³ Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Av. Complutense 40, E-28040 Madrid, Spain
⁴ Institute of Cosmology & Gravitation, Dennis Sciama Building, University of Portsmouth, Portsmouth PO1 3FX, United Kingdom
⁵ The Oskar Klein Centre, Department of Physics, Stockholm University, AlbaNova University Centre, SE-106 91 Stockholm, Sweden
⁶ Imperial Centre for Inference and Cosmology (ICIC) Blackett Laboratory, Imperial College London, Prince Consort Road, London SW7 2AZ, UK
⁷ Argelander-Institut für Astronomie, Universität Bonn, Auf dem Hügel 71, D-53121 Bonn, Germany
⁸ School of Mathematics, Statistics and Physics, Newcastle University, Herschel Building, NE1 7RU Newcastle-upon-Tyne, UK
⁹ Center for Theoretical Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
¹⁰ Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, UK
¹¹ Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK
¹² Dipartimento di Fisica e Astronomia “Augusto Righi” – Alma Mater Studiorum Università di Bologna, Via Piero Gobetti 93/2, 40129 Bologna, Italy
¹³ INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Piero Gobetti 93/3, 40129 Bologna, Italy
¹⁴ Leiden Observatory, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
¹⁵ Aix-Marseille Université, CNRS, CNES, LAM, Marseille, France
¹⁶ Universität Innsbruck, Institut für Astro- und Teilchenphysik, Technikerstr. 25/8, 6020 Innsbruck, Austria
¹⁷ Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, United Kingdom
¹⁸ Donostia International Physics Center, Manuel Lardizabal Ibilbidea, 4, 20018 Donostia, Gipuzkoa, Spain
¹⁹ Istituto Nazionale di Fisica Nucleare (INFN) – Sezione di Bologna, Viale Berti Pichat 6/2, I-40127 Bologna, Italy
²⁰ Department of Physics “E. Pancini” University of Naples Federico II C.U. di Monte Sant’Angelo, Via Cintia, 21 ed. 6, 80126 Naples, Italy
²¹ Institute for Computational Cosmology, Ogden Centre for Fundament Physics – West, Department of Physics, Durham University, South Road, Durham DH1 3LE, UK
²² Centre for Extragalactic Astronomy, Ogden Centre for Fundament Physics – West, Department of Physics, Durham University, South Road, Durham DH1 3LE, UK

^⋆ Corresponding author; yanza21@astro.rub.de

Received: 30 October 2024
Accepted: 15 January 2025

Abstract

Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the high number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys can potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an r-band 5σ magnitude limit of 24.8 and survey footprint of 1347 deg², it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an organised random (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOMs) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this SOM+HC method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the 27σ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal set-up suggested by the mock tests.