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

Autor: Euclid Collaboration, 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., 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, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., 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, P. B., 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, L. A., 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, A. N., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., 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, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Castro, T., Chambers, K. C., Cooray, A. R., Coupon, J., Courtois, H. M., Davini, S., de la Torre, S., De Lucia, G., Desprez, G., Dole, H., Escartin, J. A., Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., Garcia-Bellido, J., George, K., Giacomini, F., Gozaliasl, G., Hildebrandt, H., Muñoz, A. Jimenez, Joachimi, B., Kajava, J. J. E., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Popa, V., Potter, D., Pourtsidou, A., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Schneider, A., Sefusatti, E., Sereno, M., Shulevski, A., Mancini, A. Spurio, Steinwagner, J., Teyssier, R., Valiviita, J., Veropalumbo, A., Viel, M., Zinchenko, I. A.

Publikováno v: A&A 675, A120 (2023)

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-

Externí odkaz: http://arxiv.org/abs/2301.12890

Higher order statistics of shear field: a machine learning approach

Autor: Parroni, Carolina, Tollet, Edouard, Cardone, Vincenzo F., Maoli, Roberto, Scaramella, Roberto

Publikováno v: A&A 645, A123 (2021)

The unprecedented amount and the excellent quality of lensing data that the upcoming ground- and space-based surveys will produce represent a great opportunity to shed light on the questions that still remain unanswered concerning our universe and th

Externí odkaz: http://arxiv.org/abs/2011.10438

Going deep with Minkowski functionals of convergence maps

Autor: Parroni, Carolina, Cardone, Vincenzo F., Maoli, Roberto, Scaramella, Roberto

Publikováno v: A&A 633, A71 (2020)

Stage IV lensing surveys promise to make available an unprecedented amount of excellent data which will represent a huge leap in terms of both quantity and quality. This will open the way to the use of novel tools, which go beyond the standard second

Externí odkaz: http://arxiv.org/abs/1911.06243

Next Generation Virgo Cluster Survey. XXI. The weak lensing masses of the CFHTLS and NGVS RedGOLD galaxy clusters and calibration of the optical richness

Autor: Parroni, Carolina, Mei, Simona, Erben, Thomas, Van Waerbeke, Ludovic, Raichoor, Anand, Ford, Jes, Licitra, Rossella, Meneghetti, Massimo, Hildebrandt, Hendrik, Miller, Lance, Côté, Patrick, Covone, Giovanni, Cuillandre, Jean-Charles, Duc, Pierre-Alain, Ferrarese, Laura, Gwyn, Stephen D. J., Puzia, Thomas H.

Publikováno v: The Astrophysical Journal, Volume 848, Issue 2, article id. 114, 20 pp. (2017)

We measured stacked weak lensing cluster masses for a sample of 1325 galaxy clusters detected by the RedGOLD algorithm in the Canada-France-Hawaii Telescope Legacy Survey W1 and the Next Generation Virgo Cluster Survey at $0.2