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Euclid preparation LXX. Forecasting detection limits for intracluster light in the Euclid Wide Survey




TekijätBellhouse, C.; Golden-Marx, J. B.; Bamford, S. P.; Hatch, N. A.; Kluge, M.; Ellien, A.; Ahad, S. L.; Dimauro, P.; Durret, F.; Gonzalez, A. H.; Jimenez-Teja, Y.; Montes, M.; Sereno, M.; Slezak, E.; Bolzonella, M.; Castignani, G.; Cucciati, O.; De Lucia, G.; Ghaffari, Z.; Moscardini, L.; Pello, R.; Pozzetti, L.; Saifollahi, T.; Borlaff, A. S.; Aghanim, N.; Altieri, B.; Amara, A.; Andreon, S.; Baccigalupi, C.; Baldi, M.; Bardelli, S.; Basset, A.; Battaglia, P.; Bender, R.; Bonino, D.; Branchini, E.; Brescia, M.; Caillat, A.; Camera, S.; Capobianco, V.; Carbone, C.; Cardone, V. F.; Carretero, J.; Casas, S.; Castellano, M.; Cavuoti, S.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conselice, C. J.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Cuillandre, J. -c.; Da Silva, A.; Degaudenzi, H.; Di Giorgio, A. M.; Dinis, J.; Dubath, F.; Duncan, C. A. J.; Dupac, X.; Dusini, S.; Farina, M.; Farrens, S.; Faustini, F.; Ferriol, S.; Fotopoulou, S.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; George, K.; Gillis, B.; Giocoli, C.; Gomez-Alvarez, P.; Grazian, A.; Grupp, F.; Haugan, S. V. H.; Hoekstra, H.; Holliman, M. S.; Holmes, W.; Hook, I.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Keihaenen, E.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kubik, B.; Kuemmel, M.; Kunz, M.; Kurki-Suonio, H.; Liebing, P.; Ligori, S.; Lilje, P. B.; Lindholm, V.; Lloro, I.; Mainetti, G.; Maino, D.; Maiorano, E.; Mansutti, O.; Marggraf, O.; Markovic, K.; Martinelli, M.; Martinet, N.; Marulli, F.; Massey, R.; Maurogordato, S.; Medinaceli, E.; Mei, S.; Melchior, M.; Meneghetti, M.; Merlin, E.; Meylan, G.; Moresco, M.; Nakajima, R.; Neissner, C.; Niemi, S. -m.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L. A.; Raison, F.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Rossetti, E.; Saglia, R.; Sakr, Z.; Sapone, D.; Sartoris, B.; Schneider, P.; Schrabback, T.; Seidel, G.; Serrano, S.; Sirignano, C.; Sirri, G.; Stanco, L.; Steinwagner, J.; Tallada-Crespi, P.; Tereno, I.; Toledo-Moreo, R.; Torradeflot, F.; Tsyganov, A.; Tutusaus, I.; Valenziano, L.; Vassallo, T.; Verdoes Kleijn, G.; Veropalumbo, A.; Wang, Y.; Weller, J.; Zamorani, G.; Zucca, E.; Biviano, A.; Bozzo, E.; Burigana, C.; Calabrese, M.; Di Ferdinando, D.; Escartin Vigo, J. A.; Farinelli, R.; Finelli, F.; Gabarra, L.; Gracia-Carpio, J.; Matthew, S.; Mauri, N.; Mora, A.; Poentinen, M.; Scottez, V.; Simon, P.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Andika, I. T.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Ballardini, M.; Bethermin, M.; Blanchard, A.; Blot, L.; Boehringer, H.; Borgani, S.; Brown, M. L.; Bruton, S.; Cabanac, R.; Calabro, A.; Canas-Herrera, G.; Cappi, A.; Caro, F.; Carvalho, C. S.; Castro, T.; Chambers, K. C.; Cogato, F.; Contini, T.; Cooray, A. R.; De Paolis, F.; Desprez, G.; Diaz-Sanchez, A.; Diaz, J. J.; Di Domizio, S.; Diego, J. M.; Dole, H.; Escoffier, S.; Ferrari, A. G.; Ferreira, P. G.; Finoguenov, A.; Fontana, A.; Ganga, K.; Garcia-Bellido, J.; Gasparetto, T.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Gregorio, A.; Guidi, M.; Gutierrez, C. M.; Hall, A.; Hartley, W. G.; Hemmati, S.; Hildebrandt, H.; Hjorth, J.; Jimenez Munoz, A.; Kajava, J. J. E.; Kang, Y.; Kansal, V.; Karagiannis, D.; Kirkpatrick, C. C.; Kruk, S.; Lattanzi, M.; Le Brun, A. M. C.; Le Graet, J.; Legrand, L.; Lembo, M.; Lesgourgues, J.; Liaudat, T. I.; Liu, S. J.; Loureiro, A.; Magliocchetti, M.; Mannucci, F.; Maoli, R.; Martin-Fleitas, J.; Martins, C. J. A. P.; Maurin, L.; Metcalf, R. B.; Miluzio, M.; Monaco, P.; Moretti, C.; Morgante, G.; Murray, C.; Naidoo, K.; Navarro-Alsina, A.; Nesseris, S.; Paterson, K.; Patrizii, L.; Pisani, A.; Popa, V.; Potter, D.; Risso, I.; Rocci, P. -f.; Sahlen, M.; Sarpa, E.; Schneider, A.; Schultheis, M.; Sciotti, D.; Sellentin, E.; Smith, L. C.; Stanford, S. A.; Tanidis, K.; Tao, C.; Testera, G.; Teyssier, R.; Toft, S.; Tosi, S.; Troja, A.; Tucci, M.; Valieri, C.; Valiviita, J.; Vergani, D.; Verza, G.; Vielzeuf, P.; Walton, N. A.; Euclid Collaboration

KustantajaEDP Sciences

KustannuspaikkaLES ULIS CEDEX A

Julkaisuvuosi2025

JournalAstronomy and Astrophysics

Tietokannassa oleva lehden nimiAstronomy & Astrophysics

Lehden akronyymiASTRON ASTROPHYS

Artikkelin numeroA14

Vuosikerta698

Sivujen määrä21

ISSN0004-6361

eISSN1432-0746

DOIhttps://doi.org/10.1051/0004-6361/202553887

Verkko-osoitehttps://doi.org/10.1051/0004-6361/202553887

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/499065238


Tiivistelmä
The intracluster light (ICL) permeating galaxy clusters is a tracer of the cluster assembly history and potentially a tracer of their dark matter structure. In this work, we explore the capability of the Euclid Wide Survey to detect ICL using H-E-band mock images. We simulated clusters across a range of redshifts (0.3-1.8) and halo masses (10(13.9)-10(15.0) M-circle dot) using an observationally motivated model of ICL. We identified a 50-200 kpc circular annulus around the brightest cluster galaxy (BCG) in which the signal-to-noise ratio of the ICL is maximised and used the S/N within this aperture as our figure of merit for ICL detection. We compared three state-of-the-art methods for ICL detection and found that a method that performs simple aperture photometry after high-surface brightness source masking is able to detect ICL with minimal bias for clusters more massive than 10(14.2) M-circle dot. The S/N of the ICL detection is primarily limited by the redshift of the cluster, which is driven by cosmological dimming rather than the mass of the cluster. Assuming the ICL in each cluster contains 15% of the stellar light, we forecast that Euclid will be able to measure the presence of ICL in up to similar to 80 000 clusters of >10(14.2) M-circle dot between z = 0.3 and 1.5 with an S/N>3. Half of these clusters will reside below z = 0.75, and the majority of those below z = 0.6 will be detected with an S/N>20. A few thousand clusters at 1.3<1.5 will have ICL detectable with an S/N >3. The surface brightness profile of the ICL model is strongly dependent on both the mass of the cluster and the redshift at which it is observed so that the outer ICL is best observed in the most massive clusters of >10(14.7) M-circle dot. Euclid will detect the ICL at a distance of more than 500 kpc from the BCG, up to z = 0.7, in several hundred of these massive clusters over its large survey volume.

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Julkaisussa olevat rahoitustiedot
NAH and JBGM gratefully acknowledge support from the Leverhulme Trust through a Research Leadership Award. CB, NAH, and SB acknowledge support from the UK Science and Technology Facilities Council (STFC) under grant ST/X000982/1. FD acknowledges support from CNES. This research was supported by the International Space Science Institute (ISSI) in Bern, through ISSI International Team project #23-577. The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Agenzia Spaziale Italiana, the Austrian Forschungsförderungsgesellschaft, funded through BMK, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum für Luft- und Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d’Etudes Spatiales, the Fundação para a Ciência e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovación y Universidades, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Research Council of Finland, the Romanian Space Agency, the State Secretariat for Education, Research, and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid web site


Last updated on 2025-04-08 at 13:37