{"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","oa":1,"author":[{"last_name":"Matilla","first_name":"José Manuel Zorrilla","full_name":"Matilla, José Manuel Zorrilla"},{"full_name":"Waterval, Stefan","first_name":"Stefan","last_name":"Waterval"},{"last_name":"Haiman","id":"7c006e8c-cc0d-11ee-8322-cb904ef76f36","first_name":"Zoltán","full_name":"Haiman, Zoltán"}],"quality_controlled":"1","publication_identifier":{"issn":["0004-6256","1538-3881"]},"day":"29","article_processing_charge":"No","oa_version":"Published Version","publication_status":"published","date_created":"2024-09-05T09:35:49Z","publisher":"American Astronomical Society","publication":"The Astronomical Journal","date_updated":"2024-09-11T09:03:15Z","_id":"17528","article_number":"284","issue":"6","main_file_link":[{"url":"https://doi.org/10.3847/1538-3881/ab8f8c","open_access":"1"}],"volume":159,"article_type":"original","language":[{"iso":"eng"}],"doi":"10.3847/1538-3881/ab8f8c","year":"2020","abstract":[{"text":"We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in ray-tracing dark matter (DM)-only simulations, to two hyper-parameters that influence the accuracy as well as the computational cost of the predictions: the thickness of the lens planes used to build past light cones and the mass resolution of the underlying DM simulation. The statistics considered are the power spectrum (PS) and a series of non-Gaussian observables, including the one-point probability density function, lensing peaks, and Minkowski functionals. Counterintuitively, we find that using thin lens planes (< 60 h−1 Mpc on a 240 h−1 Mpc simulation box) suppresses the PS over a broad range of scales beyond what would be acceptable for a survey comparable to the Large Synoptic Survey Telescope (LSST). A mass resolution of 7.2 × 1011 h−1 M⊙ per DM particle (or 2563 particles in a (240 h−1 Mpc)3 box) is sufficient to extract information using the PS and non-Gaussian statistics from weak lensing data at angular scales down to 1' with LSST-like levels of shape noise.","lang":"eng"}],"citation":{"ieee":"J. M. Z. Matilla, S. Waterval, and Z. Haiman, “Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables,” <i>The Astronomical Journal</i>, vol. 159, no. 6. American Astronomical Society, 2020.","mla":"Matilla, José Manuel Zorrilla, et al. “Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables.” <i>The Astronomical Journal</i>, vol. 159, no. 6, 284, American Astronomical Society, 2020, doi:<a href=\"https://doi.org/10.3847/1538-3881/ab8f8c\">10.3847/1538-3881/ab8f8c</a>.","short":"J.M.Z. Matilla, S. Waterval, Z. Haiman, The Astronomical Journal 159 (2020).","apa":"Matilla, J. M. Z., Waterval, S., &#38; Haiman, Z. (2020). Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables. <i>The Astronomical Journal</i>. American Astronomical Society. <a href=\"https://doi.org/10.3847/1538-3881/ab8f8c\">https://doi.org/10.3847/1538-3881/ab8f8c</a>","ama":"Matilla JMZ, Waterval S, Haiman Z. Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables. <i>The Astronomical Journal</i>. 2020;159(6). doi:<a href=\"https://doi.org/10.3847/1538-3881/ab8f8c\">10.3847/1538-3881/ab8f8c</a>","ista":"Matilla JMZ, Waterval S, Haiman Z. 2020. Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables. The Astronomical Journal. 159(6), 284.","chicago":"Matilla, José Manuel Zorrilla, Stefan Waterval, and Zoltán Haiman. “Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables.” <i>The Astronomical Journal</i>. American Astronomical Society, 2020. <a href=\"https://doi.org/10.3847/1538-3881/ab8f8c\">https://doi.org/10.3847/1538-3881/ab8f8c</a>."},"extern":"1","month":"05","title":"Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables","scopus_import":"1","type":"journal_article","status":"public","intvolume":"       159","date_published":"2020-05-29T00:00:00Z"}