T
Tomasz Kacprzak
Researcher at ETH Zurich
Publications - 45
Citations - 2355
Tomasz Kacprzak is an academic researcher from ETH Zurich. The author has contributed to research in topics: Weak gravitational lensing & Galaxy. The author has an hindex of 20, co-authored 45 publications receiving 1956 citations. Previous affiliations of Tomasz Kacprzak include University of Manchester & University College London.
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Journal ArticleDOI
GALSIM: The modular galaxy image simulation toolkit
Barnaby Rowe,Barnaby Rowe,Mike Jarvis,Rachel Mandelbaum,Gary Bernstein,James Bosch,Melanie Simet,Joshua Meyers,Tomasz Kacprzak,Tomasz Kacprzak,Reiko Nakajima,Joe Zuntz,Hironao Miyatake,Hironao Miyatake,J. P. Dietrich,Robert Armstrong,Peter Melchior,Mandeep S. S. Gill +17 more
TL;DR: The performance of GALSIM meets the stringent requirements of high precision image analysis applications such as weak gravitational lensing, fo r current datasets and for the Stage IV dark energy surveys of the Large Synoptic Survey Telescope, ESA's Euclid mission, and NASA’s WFIRST-AFTAmission.
Journal ArticleDOI
The third gravitational lensing accuracy testing (great3) challenge handbook
Rachel Mandelbaum,Barnaby Rowe,Barnaby Rowe,James Bosch,Chihway Chang,Frederic Courbin,M. S. S. Gill,Mike Jarvis,Arun Kannawadi,Tomasz Kacprzak,Claire Lackner,Alexie Leauthaud,Hironao Miyatake,Reiko Nakajima,Jason Rhodes,Melanie Simet,Joe Zuntz,Bob Armstrong,Sarah Bridle,Jean Coupon,J. P. Dietrich,Marc Gentile,Catherine Heymans,Alden S. Jurling,Alden S. Jurling,Stephen M. Kent,D. Kirkby,Daniel Margala,Richard Massey,Peter Melchior,John R. Peterson,A. Roodman,Tim Schrabback +32 more
TL;DR: The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge as discussed by the authors is the third in a series of image analysis challenges, with a goal of testing and facilitating the development of methods for analyzing astronomical images that will be used to measure weak gravitational lensing.
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GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology
Rachel Mandelbaum,Barnaby Rowe,Robert Armstrong,D. J. Bard,Emmanuel Bertin,James Bosch,D. Boutigny,Frederic Courbin,William A. Dawson,Annamaria Donnarumma,Ian Fenech Conti,Raphael Gavazzi,Marc Gentile,M. S. S. Gill,David W. Hogg,E. M. Huff,M. James Jee,Tomasz Kacprzak,Tomasz Kacprzak,Martin Kilbinger,T. Kuntzer,Dustin Lang,Wentao Luo,M. March,Philip J. Marshall,Joshua Meyers,Lance Miller,Hironao Miyatake,Hironao Miyatake,R. Nakajima,Fred Maurice Ngolè Mboula,Guldariya Nurbaeva,Yuki Okura,Stephane Paulin-Henriksson,Jason Rhodes,Michael Schneider,Huanyuan Shan,Erin Sheldon,Melanie Simet,Jean-Luc Starck,Florent Sureau,M. Tewes,Kristian Zarb Adami,Kristian Zarb Adami,Jun Zhang,Joe Zuntz +45 more
TL;DR: The recent GRavitational lEnsing Accuracy Testing (GREAT3) challenge as discussed by the authors was the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images.
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Image analysis for cosmology: results from the GREAT10 Galaxy Challenge
Thomas D. Kitching,Sreekumar Balan,Sarah Bridle,N. Cantale,Frederic Courbin,Tim Eifler,Marc Gentile,M. S. S. Gill,M. S. S. Gill,Stefan Harmeling,Catherine Heymans,Michael Hirsch,K. Honscheid,Tomasz Kacprzak,D. Kirkby,Daniel Margala,Richard Massey,Peter Melchior,Guldariya Nurbaeva,K. Patton,Jason Rhodes,Barnaby Rowe,Barnaby Rowe,Andy Taylor,Malte Tewes,Massimo Viola,D. K. Witherick,L. M. Voigt,J. Young,J. Zuntz,J. Zuntz +30 more
TL;DR: The first blind point spread function (PSF) reconstruction challenge was held by the GRavitational lEnsing Accuracy Testing 2010 (GREAT10) Star Challenge as discussed by the authors, where participants were presented with 27,500 stars over 1300 images subdivided into 26 sets, where in each set a category change was made in the type or spatial variation of the PSF.
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Noise bias in weak lensing shape measurements
Alexandre Refregier,Tomasz Kacprzak,Adam Amara,Sarah Bridle,Barnaby Rowe,Barnaby Rowe,Barnaby Rowe +6 more
TL;DR: In this article, the authors derived analytical expressions for the bias of general maximum-likelihood estimators in the presence of additive noise and found that the noise bias is generically of the order of the inverse-squared signal-to-noise ratio (SNR) of the galaxies.