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Euclid: Searching for pair-instability supernovae with the Deep Survey⋆

Astronomy & Astrophysics EDP Sciences 666 (2022) a157

Authors:

TJ Moriya, C Inserra, M Tanaka, E Cappellaro, M Della Valle, I Hook, R Kotak, G Longo, F Mannucci, S Mattila, C Tao, B Altieri, A Amara, N Auricchio, D Bonino, E Branchini, M Brescia, J Brinchmann, S Camera, V Capobianco, C Carbone, J Carretero, M Castellano, S Cavuoti, A Cimatti, R Cledassou, G Congedo, CJ Conselice, L Conversi, Y Copin, L Corcione, F Courbin, M Cropper, A Da Silva, H Degaudenzi, M Douspis, F Dubath, CAJ Duncan, X Dupac, S Dusini, A Ealet, S Farrens, S Ferriol, M Frailis, E Franceschi, M Fumana, B Garilli, W Gillard, B Gillis, C Giocoli, A Grazian, F Grupp, SVH Haugan, W Holmes, F Hormuth, A Hornstrup, K Jahnke, S Kermiche, A Kiessling, M Kilbinger, T Kitching, H Kurki-Suonio, S Ligori, PB Lilje, I Lloro, E Maiorano, O Mansutti, O Marggraf, K Markovic, F Marulli, R Massey, HJ McCracken, M Melchior, M Meneghetti, G Meylan, M Moresco, L Moscardini, E Munari, SM Niemi, C Padilla, S Paltani, F Pasian, K Pedersen, V Pettorino, M Poncet, L Popa, F Raison, J Rhodes, G Riccio, E Rossetti, R Saglia, B Sartoris, P Schneider, A Secroun, G Seidel, C Sirignano, G Sirri, L Stanco, P Tallada-Crespí, AN Taylor, I Tereno, R Toledo-Moreo, F Torradeflot, Y Wang, G Zamorani, J Zoubian, S Andreon, V Scottez, PW Morris
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ShapePipe: A new shape measurement pipeline and weak-lensing application to UNIONS/CFIS data

Astronomy & Astrophysics EDP Sciences 666 (2022) a162

Authors:

Axel Guinot, Martin Kilbinger, Samuel Farrens, Austin Peel, Arnau Pujol, Morgan Schmitz, Jean-Luc Starck, Thomas Erben, Raphael Gavazzi, Stephen Gwyn, Michael J Hudson, Hendrik Hildebrandt, Liaudat Tobias, Lance Miller, Isaac Spitzer, Ludovic Van Waerbeke, Jean-Charles Cuillandre, Sébastien Fabbro, Alan McConnachie, Yannick Mellier
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The shape of dark matter haloes: results from weak lensing in the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS)

ArXiv 2209.09088 (2022)

Authors:

Bailey Robison, Michael J Hudson, Jean-Charles Cuillandre, Thomas Erben, Sébastien Fabbro, Raphaël Gavazzi, Axel Guinot, Stephen Gwyn, Hendrik Hildebrandt, Martin Kilbinger, Alan McConnachie, Lance Miller, Isaac Spitzer, Ludovic van Waerbeke
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Measurement and modelling of the chromatic dependence of a reflected wavefront on the Euclid space telescope dichroic mirror

Proceedings of SPIE--the International Society for Optical Engineering SPIE, the international society for optics and photonics 12180 (2022) 121804v-121804v-12

Authors:

M Baron, B Sassolas, P-A Frugier, LM Gaspar Venancio, J Amiaux, M Castelnau, F Keller, G Dovillaire, P Treimany, R Juvénal, L Miller, L Pinard, A Ealet
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Euclid: Fast two-point correlation function covariance through linear construction

Astronomy & Astrophysics EDP Sciences 666 (2022) A129-A129

Authors:

E Keihänen, V Lindholm, P Monaco, L Blot, C Carbone, K Kiiveri, AG Sánchez, A Viitanen, J Valiviita, A Amara, N Auricchio, M Baldi, D Bonino, E Branchini, M Brescia, J Brinchmann, S Camera, V Capobianco, J Carretero, M Castellano, S Cavuoti, A Cimatti, R Cledassou, G Congedo, L Conversi, CAJ Duncan

Abstract:

We present a method for fast evaluation of the covariance matrix for a two-point galaxy correlation function (2PCF) measured with the Landy-Szalay estimator. The standard way of evaluating the covariance matrix consists in running the estimator on a large number of mock catalogs, and evaluating their sample covariance. With large random catalog sizes (random-to-data objects' ratio M >> 1) the computational cost of the standard method is dominated by that of counting the data-random and random-random pairs, while the uncertainty of the estimate is dominated by that of data-data pairs. We present a method called Linear Construction (LC), where the covariance is estimated for small random catalogs with a size of M = 1 and M = 2, and the covariance for arbitrary M is constructed as a linear combination of the two. We show that the LC covariance estimate is unbiased. We validated the method with PINOCCHIO simulations in the range r = 20-200 h(-1) Mpc. With M = 50 and with 2h(-1) Mpc bins, the theoretical speedup of the method is a factor of 14. We discuss the impact on the precision matrix and parameter estimation, and present a formula for the covariance of covariance.Peer reviewe
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