{"language":[{"iso":"eng"}],"issue":"10","article_type":"original","date_published":"2012-04-10T00:00:00Z","main_file_link":[{"url":" https://doi.org/10.48550/arXiv.1109.6334","open_access":"1"}],"day":"10","status":"public","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","date_created":"2024-09-06T07:51:45Z","author":[{"first_name":"Jan M.","full_name":"Kratochvil, Jan M.","last_name":"Kratochvil"},{"first_name":"Eugene A.","full_name":"Lim, Eugene A.","last_name":"Lim"},{"first_name":"Sheng","full_name":"Wang, Sheng","last_name":"Wang"},{"first_name":"Zoltán","full_name":"Haiman, Zoltán","last_name":"Haiman","id":"7c006e8c-cc0d-11ee-8322-cb904ef76f36"},{"last_name":"May","first_name":"Morgan","full_name":"May, Morgan"},{"first_name":"Kevin","full_name":"Huffenberger, Kevin","last_name":"Huffenberger"}],"citation":{"mla":"Kratochvil, Jan M., et al. “Probing Cosmology with Weak Lensing Minkowski Functionals.” Physical Review D, vol. 85, no. 10, 103513, American Physical Society, 2012, doi:10.1103/physrevd.85.103513.","chicago":"Kratochvil, Jan M., Eugene A. Lim, Sheng Wang, Zoltán Haiman, Morgan May, and Kevin Huffenberger. “Probing Cosmology with Weak Lensing Minkowski Functionals.” Physical Review D. American Physical Society, 2012. https://doi.org/10.1103/physrevd.85.103513.","short":"J.M. Kratochvil, E.A. Lim, S. Wang, Z. Haiman, M. May, K. Huffenberger, Physical Review D 85 (2012).","ama":"Kratochvil JM, Lim EA, Wang S, Haiman Z, May M, Huffenberger K. Probing cosmology with weak lensing Minkowski functionals. Physical Review D. 2012;85(10). doi:10.1103/physrevd.85.103513","apa":"Kratochvil, J. M., Lim, E. A., Wang, S., Haiman, Z., May, M., & Huffenberger, K. (2012). Probing cosmology with weak lensing Minkowski functionals. Physical Review D. American Physical Society. https://doi.org/10.1103/physrevd.85.103513","ista":"Kratochvil JM, Lim EA, Wang S, Haiman Z, May M, Huffenberger K. 2012. Probing cosmology with weak lensing Minkowski functionals. Physical Review D. 85(10), 103513.","ieee":"J. M. Kratochvil, E. A. Lim, S. Wang, Z. Haiman, M. May, and K. Huffenberger, “Probing cosmology with weak lensing Minkowski functionals,” Physical Review D, vol. 85, no. 10. American Physical Society, 2012."},"article_number":"103513","oa_version":"Preprint","date_updated":"2024-09-25T08:41:09Z","publisher":"American Physical Society","type":"journal_article","doi":"10.1103/physrevd.85.103513","publication_identifier":{"issn":["1550-7998","1550-2368"]},"year":"2012","publication":"Physical Review D","scopus_import":"1","month":"04","quality_controlled":"1","oa":1,"title":"Probing cosmology with weak lensing Minkowski functionals","_id":"17675","extern":"1","volume":85,"article_processing_charge":"No","intvolume":" 85","publication_status":"published","abstract":[{"text":"In this paper, we show that Minkowski Functionals (MFs) of weak gravitational lensing (WL) convergence maps contain significant non-Gaussian, cosmology-dependent information. To do this, we use a large suite of cosmological ray-tracing N-body simulations to create mock WL convergence maps, and study the cosmological information content of MFs derived from these maps. Our suite consists of 80 independent 512^3 N-body runs, covering seven different cosmologies, varying three cosmological parameters Omega_m, w, and sigma_8 one at a time, around a fiducial LambdaCDM model. In each cosmology, we use ray-tracing to create a thousand pseudo-independent 12 deg^2 convergence maps, and use these in a Monte Carlo procedure to estimate the joint confidence contours on the above three parameters. We include redshift tomography at three different source redshifts z_s=1, 1.5, 2, explore five different smoothing scales theta_G=1, 2, 3, 5, 10 arcmin, and explicitly compare and combine the MFs with the WL power spectrum. We find that the MFs capture a substantial amount of information from non-Gaussian features of convergence maps, i.e. beyond the power spectrum. The MFs are particularly well suited to break degeneracies and to constrain the dark energy equation of state parameter w (by a factor of ~ three better than from the power spectrum alone). The non-Gaussian information derives partly from the one-point function of the convergence (through V_0, the \"area\" MF), and partly through non-linear spatial information (through combining different smoothing scales for V_0, and through V_1 and V_2, the boundary length and genus MFs, respectively). In contrast to the power spectrum, the best constraints from the MFs are obtained only when multiple smoothing scales are combined.","lang":"eng"}],"external_id":{"arxiv":["1109.6334"]}}