Euclid preparation: LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling

LENSMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov...

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Detalles Bibliográficos
Autores: Congedo, G., Miller, L., Taylor, A.N., Cross, N., Duncan, C.A.J., Kitching, T., Martinet, N., Matthew, S., Schrabback, T., Tewes, M., Welikala, N., Kermiche, S., Kiessling, A., Kilbinger, M., Ferrero, I., Kubik, B., Aghanim, N., Kuijken, K., Kümmel, M., Kunz, M., Valenziano, L., Martins, C.J.A.P., Kurki-Suonio, H., Ligori, S., Lilje, P.B., Lindholm, V., Lloro, I., Finelli, F., Maino, D., Maiorano, E., Rebolo, R., Mansutti, O., Maturi, M., Gozaliasl, G., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Maurogordato, S., McCracken, H.J., Gabarra, L., Medinaceli, E., Mei, S., Maurin, L., Melchior, M., Degaudenzi, H., Renzi, A., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morin, B., Moscardini, L., García-Bellido, J., Percival, W.J., Munari, E., Niemi, S.-M., Vassallo, T., Nightingale, J.W., Padilla, C., Rhodes, J., Paltani, S., Riccio, G., Romelli, E., Roncarelli, M., Metcalf, R.B., Rossetti, E., Gaztanaga, E., Saglia, R., Veropalumbo, A., Sapone, D., Sartoris, B., Amara, A., Schneider, P., Secroun, A., Seidel, G., Brescia, M., Serrano, S., Sirignano, C., Sirri, G., Giacomini, F., Wang, Yan, Stanco, L., Euclid Collaboration, Weller, J., Zamorani, G., Auricchio, N., Migliaccio, M., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Di Giorgio, A.M., Bonino, D., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Monaco, P., Di Ferdinando, D., Graciá-Carpio, J., Baldi, M., Mauri, Nuria, Neissner, C., Dinis, J., Nucita, A.A., Pasian, F., Sakr, Z., Scottez, V., Morgante, G., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Bardelli, S., Dubath, F., Anselmi, S., Baccigalupi, C., Guinet, D., Fosalba, Pablo, Ballardini, M., Borgani, S., Borlaff, A.S., Bruton, S., Cabanac, R., Cappi, A., Carvalho, C.S., Dupac, X., Castignani, G., Bender, R., Tallada-Crespí, P., Castro, T., Hall, A., Cañas-Herrera, G., Chambers, K.C., Cooray, A.R., Coupon, J., Davini, S., De Lucia, G., Farina, M., Desprez, G., Nadathur, S., Di Domizio, S., Dole, H., Bodendorf, C., Hildebrandt, H., Díaz-Sánchez, A., Iliac, S., Jimenez Muñoz, A., Joudaki, S., Kajava, J.J.E., Farrens, S., Patrizii, L., Kansal, V., Karagiannis, D., Kirkpatrick, C.C., Pedersen, K., Branchini, E., Legrand, L., MacIas-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Peel, A., Ferriol, S., Martinelli, M., Pezzotta, A., Popa, V., Pettorino, V., Porciani, C., Potter, D., Brinchmann, J., Pöntinen, M., Tavagnacco, D., Pozzetti, L., Reimberg, P., Rocci, P.-F., Sánchez, A.G., Schewtschenko, J.A., Schneider, A., Sefusatti, E., Pires, S., Sereno, M., Simon, P., Tereno, I., Spurio Mancini, A., Escartin Vigo, J.A., Camera, S., Stadel, J., Steinwagner, J., Testera, G., Teyssier, R., Toft, Søren, Tosi, S., Polenta, G., Andreon, S., Troja, A., Tucci, M., Frailis, M., Valieri, C., Valiviita, J., Capobianco, V., Vergani, D., Carbone, C., Cardone, V.F., Carretero, Jorge, Toledo-Moreo, R., Casas, S., Poncet, M., Castander, Francisco Javier, Franceschi, E., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C.J., Conversi, L., Copin, Y., Torradeflot, F., Courbin, Frédéric, Courtois, H.M., Cropper, M., Popa, L.A., Galeotta, S., Da Silva, A., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Tutusaus, I., Grupp, F., Haugan, S.V.H., Holliman, M.S., Escoffier, S., Raison, F., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Valentijn, E.A., Keihänen, E.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/218850
Acceso en línea:https://hdl.handle.net/2445/218850
Access Level:acceso abierto
Palabra clave:Cosmologia
Observacions astronòmiques
Astrofísica
Telescopis espacials
Cosmology
Astronomical observations
Astrophysics
Space telescopes
Descripción
Sumario:LENSMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies, sampling the posterior distribution of galaxy parameters via Markov chain Monte Carlo, and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. We quantified the scientific performance through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images, realistic clustering with a mean surface number density of 250 arcmin−2 (IE < 29.5) for galaxies, and 6 arcmin−2 (IE < 26) for stars, and a diffraction-limited chromatic PSF with a full width at half maximum of 0. ′′2 and spatial variation across the field of view. LENSMC measured objects with a density of 90 arcmin−2 (IE < 26.5) in 4500 deg2 . The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed in future work). We found measurement multiplicative and additive biases of m1 = (−3.6 ± 0.2) × 10−3 , m2 = (−4.3 ± 0.2) × 10−3 , c1 = (−1.78 ± 0.03) × 10−4 , and c2 = (0.09 ± 0.03) × 10−4 ; a large detection bias with a multiplicative component of 1.2 × 10−2 and an additive component of −3 × 10−4 ; and a measurement PSF leakage of α1 = (−9 ± 3) × 10−4 and α2 = (2 ± 3) × 10−4 . When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies (−5 × 10−3 ). Although significant, model bias will be straightforward to calibrate given its weak sensitivity on galaxy morphology parameters. LENSMC is publicly available at gitlab.com/gcongedo/LensMC.

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