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

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 . 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 (σ_8, w_0) plane for a -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, ell1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of 2.5 on the w_0 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 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. Euclid Euclid Euclid

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Publication Details

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Springer Link (Chiba Institute of Technology)
Published
2026-01-07
DOI
https://doi.org/10.1051/0004-6361/202557573/pdf
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Galaxies: Formation, Evolution, Phenomena
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article
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Euclid preparation. LXXXV. Toward a DR1 application of higher-order weak lensing statistics

Diego Jm, W. Hartley, Sanchez Ag, S. Mei et al.
Springer Link (Chiba Institute of Technology)
Galaxies: Formation, Evolution, Phenomena
article

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

Diego Jm, W. Hartley, Sanchez Ag, S. Mei, V.F. CARDONE, D. Maino, P.A. Lanser A.M. Burger, A.R. Cooray, I.T Andika, J.E. Kajava, G.F Lesci, T.I. Liaudat, F.M. Zerbi, H. Hildebrandt, E. Branchini, D. Paoletti, L. Gabarra, R. Scaramella, S. Anselmi, M. Frailis, S. Bardelli, S. Cavuoti, L. Maurin, A.M.C. Le Brun, O. Marggraf, A. Díaz-Sánchez, J. Lesgourgues, S. Mei, T. Vassallo, P.G. Ferreira, H. Degaudenzi, J. Martín-Fleitas, N. Dagoneau, M. Tenti, A. Blanchard, F. Dubath, J.-L. Starck, S.V.H. Haugan, Z. Sakr, F. Courbin, L. Legrand, D. Potter, A. Calabro, S. de la Torre, P. Hudelot, G. Verza, A. Cimatti, R. Farinelli, Y. Fang, P.L. Taylor, M. Fumana, J. García-Bellido, S. Serrano, E. Medinaceli, B. Gillis, K. Jahnke, S. Quai, S. Camera, S. Bruton, S.-M. Niemi, K. George, S. Ferriol, H. Dole, S. Pires, A. Mora, G. Gozaliasl, N. Martinet, M. Sahlén, I. Risso, G. Morgante, J. Weller, G. Congedo, K. Tanidis, G. Seidel, S. Hemmati, F. Finelli, D. Vergani, C. Giocoli, S. Andreon, A. Renzi, J. Gracia-Carpio, E. Romelli, F. Cogato, R. Toledo-Moreo, L. Porth, S. Nadathur, A. Pisani, E. Zucca, G. Meylan, Y. Wang, J. Kim, A. Vadalà, G. Castignani, M. Meneghetti, M. Miluzio, B. Sartoris, A. Troja, N.A. Walton, F. Bernardeau, S. Heydenreich, M. Farina, N. Porqueres, L. Moscardini, J. Valiviita, H.M. Courtois, S. Farrens, M. Castellano, C. Tao, S. Matthew, F. Torradeflot, F. Lepori, I. Tutusaus, M. Cropper, C. Kirkpatrick, A. Tersenov, C. Baccigalupi, B. Altieri, A. Hornstrup, D. Sciotti, F. Pasian, M. Melchior, A. Pezzotta, A. Secroun, M.L. Brown, R. Saglia, F. Bouchè, F. Raison, E. Sellentin, B. Kubik, M. Kunz, F. Giacomini, I. Lloro, J. Rhodes, K. Naidoo, A. Spurio Mancini, E. Keihänen, V. Tinnaneri Sreekanth, M. Wiesmann, X. Dupac, R.E. Angulo, A.N. Taylor, S. Dusini, J. Steinwagner, E. Aubourg, V. Scottez, A. Cappi, S. Escoffier, M. Magliocchetti, C. Uhlemann, K. Pedersen, C. Carbone, F. Marulli, G. Polenta, M. Gatti, F. Faustini, B. Camacho Quevedo, V. Pettorino, C. Neissner, J. Hjorth, Y. Kang, M. Béthermin, K. Paterson, M. Calabrese, A. Hall, S. Kruk, D. Sapone, F. Mannucci, L.A. Popa, R. Cabanac, B. Joachimi, M.Y. Elkhashab, G. Sirri, K. Kiiveri, C.M. Gutierrez, M. Lembo, D. Bertacca, S. Galeotta, A. Zacchei, L.C. Smith, D.B. Sanders, L. Blot, A. Da Silva, F. Caro, S. Toft, D. Maino, S. Ligori, M. Radovich, Y. Copin, C. Colodro-Conde, R. Teyssier, M. Tucci, V. Gautard, H. Kurki-Suonio, A. Finoguenov, S. Paltani, C. Burigana, F. Passalacqua, F. Gianotti, J. Macias-Perez, M. Viel, A. Franco, A. Barthelemy, P. Monaco, L. Patrizii, E. Sarpa, J.A. Escartin Vigo, S. Borgani, O. Mansutti, T. Gasparetto, G. Cañas-Herrera, D. Karagiannis, P. Schneider, M. Guidi, E. Gaztañaga, C. Moretti, G. Leroy, N. Tessore, G. De Lucia, J. S. Díaz, V. Capobianco, G. Desprez, M. Ballardini, M. Jhabvala, J. Harnois-Déraps, K.C. Chambers, M. Pöntinen, M. Archidiacono, S. Kermiche, G. Riccio, M. Poncet, J. Carretero, L. Castiblanco, F. Grupp, M. Bonici, E. Bozzo, M. Kilbinger, A. W. Schneider, A. Biviano, C. Padilla, E. Franceschi, J.C. Broxterman, S. Vinciguerra, R.B. Metcalf, V. Lindholm, L. Conversi, A. Kiessling, S. Nesseris, D. Grandón, R. Maoli, S. Sacquegna, M. Martinelli, I. Tereno, N. Mauri, M. Bolzonella, W. Holmes, A. Boucaud, Y. Akrami, M. Brescia, L. Linke, G. Testera, M. Baldi, C.J.A.P. Martins, S. Di Domizio, S. Tosi, M. Sereno, C. Sirignano, A. Navarro-Alsina, S. Cheng, Y. Mellier, M. Roncarelli, M. Moresco, G. Zamorani, S. Conseil, F. Atrio-Barandela, A. Grazian, K. Ganga, C.S. Carvalho, T. Schrabback, H. Hoekstra, N. Auricchio, P. Tallada-Crespí, L. Stanco, R. Gavazzi, T. Castro, G. Mainetti, F. Hormuth
article en

Abstract

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 . 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 (σ_8, w_0) plane for a -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, ell1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of 2.5 on the w_0 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 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. Euclid Euclid Euclid

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 88%
Galaxies: Formation, Evolution, Phenomena
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