Euclid preparation: LXXXV. Toward a DR1 application of higher-order weak lensing statistics

Null, Null; 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.

doi:10.1051/0004-6361/202557573

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.