Euclid preparation: LXXXV. Toward a DR1 application of higher-order weak lensing statistics;
: Vinciguerra, S.; Bouchè, F.; Martinet, N.; Castiblanco, L.; Uhlemann, C.; Pires, S.; Harnois-Déraps, J.; Giocoli, C.; Baldi, M.; Cardone, V. F.; Vadalà, A.; Dagoneau, N.; Linke, L.; Sellentin, E.; Taylor, P. L.; Broxterman, J. C.; Heydenreich, S.; Tinnaneri Sreekanth, V.; Porqueres, N.; Porth, L.; Gatti, M.; Grandón, D.; Barthelemy, A.; Bernardeau, F.; Tersenov, A.; Hoekstra, H.; Starck, J.-L.; Cheng, S.; Burger, P. A.; Tereno, I.; Scaramella, R.; Altieri, B.; Andreon, S.; Auricchio, N.; Baccigalupi, C.; Bardelli, S.; Biviano, A.; Branchini, E.; Brescia, M.; Camera, S.; Cañas-Herrera, G.; Capobianco, V.; Carbone, C.; Carretero, J.; Castellano, M.; Castignani, G.; Cavuoti, S.; Chambers, K. C.; Cimatti, A.; Colodro-Conde, C.; Congedo, G.; Conversi, L.; Copin, Y.; Courbin, F.; Courtois, H. M.; Cropper, M.; Da Silva, A.; Degaudenzi, H.; de la Torre, S.; De Lucia, G.; Dole, H.; Dubath, F.; Dupac, X.; Dusini, S.; Escoffier, S.; Farina, M.; Farinelli, R.; Farrens, S.; Faustini, F.; Ferriol, S.; Finelli, F.; Frailis, M.; Franceschi, E.; Fumana, M.; Galeotta, S.; George, K.; Gillis, B.; Gracia-Carpio, J.; Grazian, A.; Grupp, F.; Haugan, S. V. H.; Holmes, W.; Hormuth, F.; Hornstrup, A.; Hudelot, P.; Jahnke, K.; Jhabvala, M.; Joachimi, B.; Keihänen, E.; Kermiche, S.; Kiessling, A.; Kilbinger, M.; Kubik, B.; Kunz, M.; Kurki-Suonio, H.; Le Brun, A. M. C.; Ligori, S.; Lilje, P. B.; Lindholm, V.; Lloro, I.; Mainetti, G.; Maino, D.; Mansutti, O.; Marggraf, O.; Martinelli, M.; Marulli, F.; Massey, R. J.; Medinaceli, E.; Mei, S.; Melchior, M.; Mellier, Y.; Meneghetti, M.; Meylan, G.; Mora, A.; Moresco, M.; Moscardini, L.; Neissner, C.; Niemi, S.-M.; Padilla, C.; Paltani, S.; Pasian, F.; Pedersen, K.; Pettorino, V.; Polenta, G.; Poncet, M.; Popa, L. A.; Raison, F.; Renzi, A.; Rhodes, J.; Riccio, G.; Romelli, E.; Roncarelli, M.; Saglia, R.; Sakr, Z.; Sánchez, A. G.; Sapone, D.; Sartoris, B.; Schneider, P.; Schrabback, T.; Secroun, A.; Seidel, G.; Serrano, S.; Sirignano, C.; Sirri, G.; Spurio Mancini, A.; Stanco, L.; Steinwagner, J.; Tallada-Crespí, P.; Taylor, A. N.; Tessore, N.; Toft, S.; Toledo-Moreo, R.; Torradeflot, F.; Tutusaus, I.; Valiviita, J.; Vassallo, T.; Wang, Y.; Weller, J.; Zacchei, A.; Zamorani, G.; Zerbi, F. M.; Zucca, E.; Ballardini, M.; Bolzonella, M.; Boucaud, A.; Bozzo, E.; Burigana, C.; Cabanac, R.; Calabrese, M.; Cappi, A.; Escartin Vigo, J. A.; Gabarra, L.; Hartley, W. G.; Maoli, R.; Martín-Fleitas, J.; Matthew, S.; Mauri, N.; Metcalf, R. B.; Pezzotta, A.; Pöntinen, M.; Risso, I.; Scottez, V.; Sereno, M.; Tenti, M.; Viel, M.; Wiesmann, M.; Akrami, Y.; Andika, I. T.; Angulo, R. E.; Anselmi, S.; Archidiacono, M.; Atrio-Barandela, F.; Aubourg, E.; Bertacca, D.; Bethermin, M.; Blanchard, A.; Blot, L.; Bonici, M.; Borgani, S.; Brown, M. L.; Bruton, S.; Calabro, A.; Camacho Quevedo, B.; Caro, F.; Carvalho, C. S.; Castro, T.; Cogato, F.; Conseil, S.; Cooray, A. R.; Desprez, G.; Díaz-Sánchez, A.; Diaz, J. J.; Di Domizio, S.; Diego, J. M.; Elkhashab, M. Y.; Fang, Y.; Ferreira, P. G.; Finoguenov, A.; Franco, A.; Ganga, K.; García-Bellido, J.; Gasparetto, T.; Gautard, V.; Gavazzi, R.; Gaztanaga, E.; Giacomini, F.; Gianotti, F.; Gozaliasl, G.; Guidi, M.; Gutierrez, C. M.; Hall, A.; Hemmati, S.; Hildebrandt, H.; Hjorth, J.; Kajava, J. J. E.; Kang, Y.; Karagiannis, D.; Kiiveri, K.; Kim, J.; Kirkpatrick, C. C.; Kruk, S.; Legrand, L.; Lembo, M.; Lepori, F.; Leroy, G.; Lesci, G. F.; Lesgourgues, J.; Liaudat, T. I.; Macias-Perez, J.; Magliocchetti, M.; Mannucci, F.; Martins, C. J. A. P.; Maurin, L.; Miluzio, M.; Monaco, P.; Moretti, C.; Morgante, G.; Nadathur, S.; Naidoo, K.; Navarro-Alsina, A.; Nesseris, S.; Paoletti, D.; Passalacqua, F.; Paterson, K.; Patrizii, L.; Pisani, A.; Potter, D.; Quai, S.; Radovich, M.; Sacquegna, S.; Sahlén, M.; Sanders, D. B.; Sarpa, E.; Schneider, A.; Sciotti, D.; Smith, L. C.; Tanidis, K.; Tao, C.; Testera, G.; Teyssier, R.; Tosi, S.; Troja, A.; Tucci, M.; Vergani, D.; Verza, G.; Walton, N. A.; Euclid Collaboration
Publisher: EDP Sciences
: 2026
Astronomy and Astrophysics
: A235
: 707
: 0004-6361
: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202557573
: https://doi.org/10.1051/0004-6361/202557573
: https://research.utu.fi/converis/portal/detail/Publication/523435968
This is the second paper in the HOWLS (higher-order weak lensing statistics) series exploring the usage of non-Gaussian statistics for cosmology inference within Euclid. With respect to our first paper, we develop a full tomographic analysis based on realistic photometric redshifts that allows us to derive Fisher forecasts in the (8, w0) plane for a Euclid-like data release 1 (DR1) setup. We find that the five higher-order statistics (HOS) that satisfy the Gaussian likelihood assumption of the Fisher formalism (one-point probability distribution function, 1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of 2.5 on the w0 forecasts, with only marginal improvement when used in combination with two-point estimators, suggesting that every HOS is able to retrieve both the non-Gaussian and Gaussian information of the matter density field. The similar performance of the different estimators is explained by a homogeneous use of multi-scale and tomographic information, optimized to lower computational costs. These results hold for the three mass mapping techniques of the Euclid pipeline, aperture mass, Kaiser-Squires, and Kaiser-Squires plus, and they are unaffected by the application of realistic star masks. Finally, we explored the use of HOS with the Bernardeau-Nishimichi-Taruya (BNT) nulling scheme approach, finding promising results toward applying physical scale cuts to HOS.
cosmological parameters, dark energy, large-scale structure of Universe
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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 BMIMI, 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 (www.euclid-ec.org). This work has made use of CosmoHub, developed by PIC (maintained by IFAE and CIEMAT) in collaboration with ICE-CSIC. CosmoHub received funding from the Spanish government (MCIN/AEI/10.13039/501100011033), the EU NextGeneration/PRTR (PRTR-C17.I1), and the Generalitat de Catalunya. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. Simone Vinciguerra & Nicolas Martinet acknowledge the funding of the French Agence Nationale de la Recherche for the PISCO project (grant ANR-22-CE31-0004). Andreas Tersenov and Jean-Starck acknowledge the funding of the TITAN ERA Chair project (contract no. 101086741) within the Horizon Europe Framework Program of the European Commission and of the French Agence Nationale de la Recherche (ANR-22-CE31-0014-01 TOSCA).
