Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Euclid Collaboration; V. Ajani; M. Baldi; A. Barthelemy; A. Boyle; P. Burger; V. F. Cardone; S. Cheng; S. Codis; C. Giocoli; J. Harnois-Déraps; S. Heydenreich; V. Kansal; M. Kilbinger; L. Linke; C. Llinares; N. Martinet; C. Parroni; A. Peel; S. Pires; L. Porth; I. Tereno; C. Uhlemann; M. Vicinanza; S. Vinciguerra; N. Aghanim; N. Auricchio; D. Bonino; E. Branchini; M. Brescia; J. Brinchmann; S. Camera; V. Capobianco; C. Carbone; J. Carretero; F. J. Castander; M. Castellano; S. Cavuoti; A. Cimatti; R. Cledassou; G. Congedo; C. J. Conselice; L. Conversi; L. Corcione; F. Courbin; M. Cropper; A. Da Silva; H. Degaudenzi; A. M. Di Giorgio; J. Dinis; M. Douspis; F. Dubath; X. Dupac; S. Farrens; S. Ferriol; P. Fosalba; M. Frailis; E. Franceschi; S. Galeotta; B. Garilli; B. Gillis; A. Grazian; F. Grupp; H. Hoekstra; W. Holmes; A. Hornstrup; P. Hudelot; K. Jahnke; M. Jhabvala; M. Kümmel; T. Kitching; M. Kunz; H. Kurki-Suonio; P. B. Lilje; I. Lloro; E. Maiorano; O. Mansutti; O. Marggraf; K. Markovic; F. Marulli; R. Massey; S. Mei; Y. Mellier; M. Meneghetti; M. Moresco; L. Moscardini; S.-M. Niemi; J. Nightingale; T. Nutma; C. Padilla; S. Paltani; K. Pedersen; V. Pettorino; G. Polenta; M. Poncet; L. A. Popa; F. Raison; A. Renzi; J. Rhodes; G. Riccio; E. Romelli; M. Roncarelli; E. Rossetti; R. Saglia; D. Sapone; B. Sartoris; P. Schneider; T. Schrabback; A. Secroun; G. Seidel; S. Serrano; C. Sirignano; L. Stanco; J.-L. Starck; P. Tallada-Crespí; A. N. Taylor; R. Toledo-Moreo; F. Torradeflot; I. Tutusaus; E. A. Valentijn; L. Valenziano; T. Vassallo; Y. Wang; J. Weller; G. Zamorani; J. Zoubian; S. Andreon; S. Bardelli; A. Boucaud; E. Bozzo; C. Colodro-Conde; D. Di Ferdinando; G. Fabbian; M. Farina; J. Graciá-Carpio; E. Keihänen; V. Lindholm; D. Maino; N. Mauri; C. Neissner; M. Schirmer; V. Scottez; E. Zucca; Y. Akrami; C. Baccigalupi; A. Balaguera-Antolínez; M. Ballardini; F. Bernardeau; A. Biviano; A. Blanchard; S. Borgani; A. S. Borlaff; C. Burigana; R. Cabanac; A. Cappi; C. S. Carvalho; S. Casas; G. Castignani; T. Castro; K. C. Chambers; A. R. Cooray; J. Coupon; H. M. Courtois; S. Davini; S. de la Torre; G. De Lucia; G. Desprez; H. Dole; J. A. Escartin; S. Escoffier; I. Ferrero; F. Finelli; K. Ganga; J. Garcia-Bellido; K. George; F. Giacomini; G. Gozaliasl; H. Hildebrandt; A. Jimenez Muñoz; B. Joachimi; J. J. E. Kajava; C. C. Kirkpatrick; L. Legrand; A. Loureiro; M. Magliocchetti; R. Maoli; S. Marcin; M. Martinelli; C. J. A. P. Martins; S. Matthew; L. Maurin; R. B. Metcalf; P. Monaco; G. Morgante; S. Nadathur; A. A. Nucita; V. Popa; D. Potter; A. Pourtsidou; M. Pöntinen; P. Reimberg; A. G. Sánchez; Z. Sakr; A. Schneider; E. Sefusatti; M. Sereno; A. Shulevski; A. Spurio Mancini; J. Steinwagner; R. Teyssier; J. Valiviita; A. Veropalumbo; M. Viel; I. A. Zinchenko

doi:10.1051/0004-6361/202346017

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Euclid Collaboration, V. Ajani, M. Baldi, A. Barthelemy, A. Boyle, P. Burger, V. F. Cardone, S. Cheng, S. Codis, C. Giocoli, J. Harnois-Déraps, S. Heydenreich, V. Kansal, M. Kilbinger, L. Linke, C. Llinares, N. Martinet, C. Parroni, A. Peel, S. PiresL. Porth, I. Tereno, C. Uhlemann, M. Vicinanza, S. Vinciguerra, N. Aghanim, N. Auricchio, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, F. J. Castander, M. Castellano, S. Cavuoti, A. Cimatti, R. Cledassou, G. Congedo, C. J. Conselice, L. Conversi, L. Corcione, F. Courbin, M. Cropper, A. Da Silva, H. Degaudenzi, A. M. Di Giorgio, J. Dinis, M. Douspis, F. Dubath, X. Dupac, S. Farrens, S. Ferriol, P. Fosalba, M. Frailis, E. Franceschi, S. Galeotta, B. Garilli, B. Gillis, A. Grazian, F. Grupp, H. Hoekstra, W. Holmes, A. Hornstrup, P. Hudelot, K. Jahnke, M. Jhabvala, M. Kümmel, T. Kitching, M. Kunz, H. Kurki-Suonio, P. B. Lilje, I. Lloro, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovic, F. Marulli, R. Massey, S. Mei, Y. Mellier, M. Meneghetti, M. Moresco, L. Moscardini, S.-M. Niemi, J. Nightingale, T. Nutma, C. Padilla, S. Paltani, K. Pedersen, V. Pettorino, G. Polenta, M. Poncet, L. A. Popa, F. Raison, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, E. Rossetti, R. Saglia, D. Sapone, B. Sartoris, P. Schneider, T. Schrabback, A. Secroun, G. Seidel, S. Serrano, C. Sirignano, L. Stanco, J.-L. Starck, P. Tallada-Crespí, A. N. Taylor, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, E. A. Valentijn, L. Valenziano, T. Vassallo, Y. Wang, J. Weller, G. Zamorani, J. Zoubian, S. Andreon, S. Bardelli, A. Boucaud, E. Bozzo, C. Colodro-Conde, D. Di Ferdinando, G. Fabbian, M. Farina, J. Graciá-Carpio, E. Keihänen, V. Lindholm, D. Maino, N. Mauri, C. Neissner, M. Schirmer, V. Scottez, E. Zucca, Y. Akrami, C. Baccigalupi, A. Balaguera-Antolínez, M. Ballardini, F. Bernardeau, A. Biviano, A. Blanchard, S. Borgani, A. S. Borlaff, C. Burigana, R. Cabanac, A. Cappi, C. S. Carvalho, S. Casas, G. Castignani, T. Castro, K. C. Chambers, A. R. Cooray, J. Coupon, H. M. Courtois, S. Davini, S. de la Torre, G. De Lucia, G. Desprez, H. Dole, J. A. Escartin, S. Escoffier, I. Ferrero, F. Finelli, K. Ganga, J. Garcia-Bellido, K. George, F. Giacomini, G. Gozaliasl, H. Hildebrandt, A. Jimenez Muñoz, B. Joachimi, J. J. E. Kajava, C. C. Kirkpatrick, L. Legrand, A. Loureiro, M. Magliocchetti, R. Maoli, S. Marcin, M. Martinelli, C. J. A. P. Martins, S. Matthew, L. Maurin, R. B. Metcalf, P. Monaco, G. Morgante, S. Nadathur, A. A. Nucita, V. Popa, D. Potter, A. Pourtsidou, M. Pöntinen, P. Reimberg, A. G. Sánchez, Z. Sakr, A. Schneider, E. Sefusatti, M. Sereno, A. Shulevski, A. Spurio Mancini, J. Steinwagner, R. Teyssier, J. Valiviita, A. Veropalumbo, M. Viel, I. A. Zinchenko

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Abstract

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ωm, σ8) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid. The data used in this analysis are publicly released with the paper.

Original language	English
Article number	A120
Journal	Astronomy and Astrophysics
Volume	675
Number of pages	32
ISSN	0004-6361
DOIs	https://doi.org/10.1051/0004-6361/202346017
Publication status	Published - 2023

Keywords

Gravitational lensing: weak
Methods: statistical
Surveys
Large-scale structure of Universe
Cosmological parameters

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Collaboration, E., Ajani, V., Baldi, M., Barthelemy, A., Boyle, A., Burger, P., Cardone, V. F., Cheng, S., Codis, S., Giocoli, C., Harnois-Déraps, J., Heydenreich, S., Kansal, V., Kilbinger, M., Linke, L., Llinares, C., Martinet, N., Parroni, C., Peel, A., ... Zinchenko, I. A. (2023). Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics. Astronomy and Astrophysics, 675, Article A120. https://doi.org/10.1051/0004-6361/202346017

@article{132aca6e6598464792ec7fef915f4750,

title = "Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics",

abstract = "Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ωm, σ8) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid. The data used in this analysis are publicly released with the paper.",

keywords = "Gravitational lensing: weak, Methods: statistical, Surveys, Large-scale structure of Universe, Cosmological parameters",

author = "Euclid Collaboration and V. Ajani and M. Baldi and A. Barthelemy and A. Boyle and P. Burger and Cardone, {V. F.} and S. Cheng and S. Codis and C. Giocoli and J. Harnois-D{\'e}raps and S. Heydenreich and V. Kansal and M. Kilbinger and L. Linke and C. Llinares and N. Martinet and C. Parroni and A. Peel and S. Pires and L. Porth and I. Tereno and C. Uhlemann and M. Vicinanza and S. Vinciguerra and N. Aghanim and N. Auricchio and D. Bonino and E. Branchini and M. Brescia and J. Brinchmann and S. Camera and V. Capobianco and C. Carbone and J. Carretero and Castander, {F. J.} and M. Castellano and S. Cavuoti and A. Cimatti and R. Cledassou and G. Congedo and Conselice, {C. J.} and L. Conversi and L. Corcione and F. Courbin and M. Cropper and {Da Silva}, A. and H. Degaudenzi and {Di Giorgio}, {A. M.} and J. Dinis and M. Douspis and F. Dubath and X. Dupac and S. Farrens and S. Ferriol and P. Fosalba and M. Frailis and E. Franceschi and S. Galeotta and B. Garilli and B. Gillis and A. Grazian and F. Grupp and H. Hoekstra and W. Holmes and A. Hornstrup and P. Hudelot and K. Jahnke and M. Jhabvala and M. K{\"u}mmel and T. Kitching and M. Kunz and H. Kurki-Suonio and Lilje, {P. B.} and I. Lloro and E. Maiorano and O. Mansutti and O. Marggraf and K. Markovic and F. Marulli and R. Massey and S. Mei and Y. Mellier and M. Meneghetti and M. Moresco and L. Moscardini and S.-M. Niemi and J. Nightingale and T. Nutma and C. Padilla and S. Paltani and K. Pedersen and V. Pettorino and G. Polenta and M. Poncet and Popa, {L. A.} and F. Raison and A. Renzi and J. Rhodes and G. Riccio and E. Romelli and M. Roncarelli and E. Rossetti and R. Saglia and D. Sapone and B. Sartoris and P. Schneider and T. Schrabback and A. Secroun and G. Seidel and S. Serrano and C. Sirignano and L. Stanco and J.-L. Starck and P. Tallada-Cresp{\'i} and Taylor, {A. N.} and R. Toledo-Moreo and F. Torradeflot and I. Tutusaus and Valentijn, {E. A.} and L. Valenziano and T. Vassallo and Y. Wang and J. Weller and G. Zamorani and J. Zoubian and S. Andreon and S. Bardelli and A. Boucaud and E. Bozzo and C. Colodro-Conde and {Di Ferdinando}, D. and G. Fabbian and M. Farina and J. Graci{\'a}-Carpio and E. Keih{\"a}nen and V. Lindholm and D. Maino and N. Mauri and C. Neissner and M. Schirmer and V. Scottez and E. Zucca and Y. Akrami and C. Baccigalupi and A. Balaguera-Antol{\'i}nez and M. Ballardini and F. Bernardeau and A. Biviano and A. Blanchard and S. Borgani and Borlaff, {A. S.} and C. Burigana and R. Cabanac and A. Cappi and Carvalho, {C. S.} and S. Casas and G. Castignani and T. Castro and Chambers, {K. C.} and Cooray, {A. R.} and J. Coupon and Courtois, {H. M.} and S. Davini and {de la Torre}, S. and {De Lucia}, G. and G. Desprez and H. Dole and Escartin, {J. A.} and S. Escoffier and I. Ferrero and F. Finelli and K. Ganga and J. Garcia-Bellido and K. George and F. Giacomini and G. Gozaliasl and H. Hildebrandt and {Jimenez Mu{\~n}oz}, A. and B. Joachimi and Kajava, {J. J. E.} and Kirkpatrick, {C. C.} and L. Legrand and A. Loureiro and M. Magliocchetti and R. Maoli and S. Marcin and M. Martinelli and Martins, {C. J. A. P.} and S. Matthew and L. Maurin and Metcalf, {R. B.} and P. Monaco and G. Morgante and S. Nadathur and Nucita, {A. A.} and V. Popa and D. Potter and A. Pourtsidou and M. P{\"o}ntinen and P. Reimberg and S{\'a}nchez, {A. G.} and Z. Sakr and A. Schneider and E. Sefusatti and M. Sereno and A. Shulevski and {Spurio Mancini}, A. and J. Steinwagner and R. Teyssier and J. Valiviita and A. Veropalumbo and M. Viel and Zinchenko, {I. A.}",

year = "2023",

doi = "10.1051/0004-6361/202346017",

language = "English",

volume = "675",

journal = "Astronomy and Astrophysics",

issn = "0004-6361",

publisher = "EDP Sciences",

}

Collaboration, E, Ajani, V, Baldi, M, Barthelemy, A, Boyle, A, Burger, P, Cardone, VF, Cheng, S, Codis, S, Giocoli, C, Harnois-Déraps, J, Heydenreich, S, Kansal, V, Kilbinger, M, Linke, L, Llinares, C, Martinet, N, Parroni, C, Peel, A, Pires, S, Porth, L, Tereno, I, Uhlemann, C, Vicinanza, M, Vinciguerra, S, Aghanim, N, Auricchio, N, Bonino, D, Branchini, E, Brescia, M, Brinchmann, J, Camera, S, Capobianco, V, Carbone, C, Carretero, J, Castander, FJ, Castellano, M, Cavuoti, S, Cimatti, A, Cledassou, R, Congedo, G, Conselice, CJ, Conversi, L, Corcione, L, Courbin, F, Cropper, M, Da Silva, A, Degaudenzi, H, Di Giorgio, AM, Dinis, J, Douspis, M, Dubath, F, Dupac, X, Farrens, S, Ferriol, S, Fosalba, P, Frailis, M, Franceschi, E, Galeotta, S, Garilli, B, Gillis, B, Grazian, A, Grupp, F, Hoekstra, H, Holmes, W, Hornstrup, A, Hudelot, P, Jahnke, K, Jhabvala, M, Kümmel, M, Kitching, T, Kunz, M, Kurki-Suonio, H, Lilje, PB, Lloro, I, Maiorano, E, Mansutti, O, Marggraf, O, Markovic, K, Marulli, F, Massey, R, Mei, S, Mellier, Y, Meneghetti, M, Moresco, M, Moscardini, L, Niemi, S-M, Nightingale, J, Nutma, T, Padilla, C, Paltani, S, Pedersen, K, Pettorino, V, Polenta, G, Poncet, M, Popa, LA, Raison, F, Renzi, A, Rhodes, J, Riccio, G, Romelli, E, Roncarelli, M, Rossetti, E, Saglia, R, Sapone, D, Sartoris, B, Schneider, P, Schrabback, T, Secroun, A, Seidel, G, Serrano, S, Sirignano, C, Stanco, L, Starck, J-L, Tallada-Crespí, P, Taylor, AN, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valentijn, EA, Valenziano, L, Vassallo, T, Wang, Y, Weller, J, Zamorani, G, Zoubian, J, Andreon, S, Bardelli, S, Boucaud, A, Bozzo, E, Colodro-Conde, C, Di Ferdinando, D, Fabbian, G, Farina, M, Graciá-Carpio, J, Keihänen, E, Lindholm, V, Maino, D, Mauri, N, Neissner, C, Schirmer, M, Scottez, V, Zucca, E, Akrami, Y, Baccigalupi, C, Balaguera-Antolínez, A, Ballardini, M, Bernardeau, F, Biviano, A, Blanchard, A, Borgani, S, Borlaff, AS, Burigana, C, Cabanac, R, Cappi, A, Carvalho, CS, Casas, S, Castignani, G, Castro, T, Chambers, KC, Cooray, AR, Coupon, J, Courtois, HM, Davini, S, de la Torre, S, De Lucia, G, Desprez, G, Dole, H, Escartin, JA, Escoffier, S, Ferrero, I, Finelli, F, Ganga, K, Garcia-Bellido, J, George, K, Giacomini, F, Gozaliasl, G, Hildebrandt, H, Jimenez Muñoz, A, Joachimi, B, Kajava, JJE, Kirkpatrick, CC, Legrand, L, Loureiro, A, Magliocchetti, M, Maoli, R, Marcin, S, Martinelli, M, Martins, CJAP, Matthew, S, Maurin, L, Metcalf, RB, Monaco, P, Morgante, G, Nadathur, S, Nucita, AA, Popa, V, Potter, D, Pourtsidou, A, Pöntinen, M, Reimberg, P, Sánchez, AG, Sakr, Z, Schneider, A, Sefusatti, E, Sereno, M, Shulevski, A, Spurio Mancini, A, Steinwagner, J, Teyssier, R, Valiviita, J, Veropalumbo, A, Viel, M & Zinchenko, IA 2023, 'Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics', Astronomy and Astrophysics, vol. 675, A120. https://doi.org/10.1051/0004-6361/202346017

TY - JOUR

T1 - Euclid preparation

T2 - XXVIII. Forecasts for ten different higher-order weak lensing statistics

AU - Collaboration, Euclid

AU - Ajani, V.

AU - Baldi, M.

AU - Barthelemy, A.

AU - Boyle, A.

AU - Burger, P.

AU - Cardone, V. F.

AU - Cheng, S.

AU - Codis, S.

AU - Giocoli, C.

AU - Harnois-Déraps, J.

AU - Heydenreich, S.

AU - Kansal, V.

AU - Kilbinger, M.

AU - Linke, L.

AU - Llinares, C.

AU - Martinet, N.

AU - Parroni, C.

AU - Peel, A.

AU - Pires, S.

AU - Porth, L.

AU - Tereno, I.

AU - Uhlemann, C.

AU - Vicinanza, M.

AU - Vinciguerra, S.

AU - Aghanim, N.

AU - Auricchio, N.

AU - Bonino, D.

AU - Branchini, E.

AU - Brescia, M.

AU - Brinchmann, J.

AU - Camera, S.

AU - Capobianco, V.

AU - Carbone, C.

AU - Carretero, J.

AU - Castander, F. J.

AU - Castellano, M.

AU - Cavuoti, S.

AU - Cimatti, A.

AU - Cledassou, R.

AU - Congedo, G.

AU - Conselice, C. J.

AU - Conversi, L.

AU - Corcione, L.

AU - Courbin, F.

AU - Cropper, M.

AU - Da Silva, A.

AU - Degaudenzi, H.

AU - Di Giorgio, A. M.

AU - Dinis, J.

AU - Douspis, M.

AU - Dubath, F.

AU - Dupac, X.

AU - Farrens, S.

AU - Ferriol, S.

AU - Fosalba, P.

AU - Frailis, M.

AU - Franceschi, E.

AU - Galeotta, S.

AU - Garilli, B.

AU - Gillis, B.

AU - Grazian, A.

AU - Grupp, F.

AU - Hoekstra, H.

AU - Holmes, W.

AU - Hornstrup, A.

AU - Hudelot, P.

AU - Jahnke, K.

AU - Jhabvala, M.

AU - Kümmel, M.

AU - Kitching, T.

AU - Kunz, M.

AU - Kurki-Suonio, H.

AU - Lilje, P. B.

AU - Lloro, I.

AU - Maiorano, E.

AU - Mansutti, O.

AU - Marggraf, O.

AU - Markovic, K.

AU - Marulli, F.

AU - Massey, R.

AU - Mei, S.

AU - Mellier, Y.

AU - Meneghetti, M.

AU - Moresco, M.

AU - Moscardini, L.

AU - Niemi, S.-M.

AU - Nightingale, J.

AU - Nutma, T.

AU - Padilla, C.

AU - Paltani, S.

AU - Pedersen, K.

AU - Pettorino, V.

AU - Polenta, G.

AU - Poncet, M.

AU - Popa, L. A.

AU - Raison, F.

AU - Renzi, A.

AU - Rhodes, J.

AU - Riccio, G.

AU - Romelli, E.

AU - Roncarelli, M.

AU - Rossetti, E.

AU - Saglia, R.

AU - Sapone, D.

AU - Sartoris, B.

AU - Schneider, P.

AU - Schrabback, T.

AU - Secroun, A.

AU - Seidel, G.

AU - Serrano, S.

AU - Sirignano, C.

AU - Stanco, L.

AU - Starck, J.-L.

AU - Tallada-Crespí, P.

AU - Taylor, A. N.

AU - Toledo-Moreo, R.

AU - Torradeflot, F.

AU - Tutusaus, I.

AU - Valentijn, E. A.

AU - Valenziano, L.

AU - Vassallo, T.

AU - Wang, Y.

AU - Weller, J.

AU - Zamorani, G.

AU - Zoubian, J.

AU - Andreon, S.

AU - Bardelli, S.

AU - Boucaud, A.

AU - Bozzo, E.

AU - Colodro-Conde, C.

AU - Di Ferdinando, D.

AU - Fabbian, G.

AU - Farina, M.

AU - Graciá-Carpio, J.

AU - Keihänen, E.

AU - Lindholm, V.

AU - Maino, D.

AU - Mauri, N.

AU - Neissner, C.

AU - Schirmer, M.

AU - Scottez, V.

AU - Zucca, E.

AU - Akrami, Y.

AU - Baccigalupi, C.

AU - Balaguera-Antolínez, A.

AU - Ballardini, M.

AU - Bernardeau, F.

AU - Biviano, A.

AU - Blanchard, A.

AU - Borgani, S.

AU - Borlaff, A. S.

AU - Burigana, C.

AU - Cabanac, R.

AU - Cappi, A.

AU - Carvalho, C. S.

AU - Casas, S.

AU - Castignani, G.

AU - Castro, T.

AU - Chambers, K. C.

AU - Cooray, A. R.

AU - Coupon, J.

AU - Courtois, H. M.

AU - Davini, S.

AU - de la Torre, S.

AU - De Lucia, G.

AU - Desprez, G.

AU - Dole, H.

AU - Escartin, J. A.

AU - Escoffier, S.

AU - Ferrero, I.

AU - Finelli, F.

AU - Ganga, K.

AU - Garcia-Bellido, J.

AU - George, K.

AU - Giacomini, F.

AU - Gozaliasl, G.

AU - Hildebrandt, H.

AU - Jimenez Muñoz, A.

AU - Joachimi, B.

AU - Kajava, J. J. E.

AU - Kirkpatrick, C. C.

AU - Legrand, L.

AU - Loureiro, A.

AU - Magliocchetti, M.

AU - Maoli, R.

AU - Marcin, S.

AU - Martinelli, M.

AU - Martins, C. J. A. P.

AU - Matthew, S.

AU - Maurin, L.

AU - Metcalf, R. B.

AU - Monaco, P.

AU - Morgante, G.

AU - Nadathur, S.

AU - Nucita, A. A.

AU - Popa, V.

AU - Potter, D.

AU - Pourtsidou, A.

AU - Pöntinen, M.

AU - Reimberg, P.

AU - Sánchez, A. G.

AU - Sakr, Z.

AU - Schneider, A.

AU - Sefusatti, E.

AU - Sereno, M.

AU - Shulevski, A.

AU - Spurio Mancini, A.

AU - Steinwagner, J.

AU - Teyssier, R.

AU - Valiviita, J.

AU - Veropalumbo, A.

AU - Viel, M.

AU - Zinchenko, I. A.

PY - 2023

Y1 - 2023

N2 - Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ωm, σ8) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid. The data used in this analysis are publicly released with the paper.

AB - Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of Euclid-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic (Ωm, σ8) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a 4.5 times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with Euclid. The data used in this analysis are publicly released with the paper.

KW - Gravitational lensing: weak

KW - Methods: statistical

KW - Surveys

KW - Large-scale structure of Universe

KW - Cosmological parameters

U2 - 10.1051/0004-6361/202346017

DO - 10.1051/0004-6361/202346017

M3 - Journal article

SN - 0004-6361

VL - 675

JO - Astronomy and Astrophysics

JF - Astronomy and Astrophysics

M1 - A120

ER -

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

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