Cosmic shear power spectra in practice

被引:44
作者
Nicola, Andrina [1 ]
Garcia-Garcia, Carlos [2 ,3 ,4 ]
Alonso, David [4 ]
Dunkley, Jo [1 ,5 ]
Ferreira, Pedro G. [4 ]
Slosar, Anze [6 ]
Spergel, David N. [1 ,7 ]
机构
[1] Princeton Univ, Dept Astrophys Sci, Peyton Hall, Princeton, NJ 08544 USA
[2] CSIC, Inst Fis Fundamental, C Serrano 123, E-28006 Madrid, Spain
[3] Inst Ciencies Cosmos UB IEEC, C Marti i Franques 1, E-0802 Barcelona, Spain
[4] Univ Oxford, Dept Phys, Denys Wilkinson Bldg,Keble Rd, Oxford OX1 3RH, England
[5] Princeton Univ, Dept Phys, Jadwin Hall, Princeton, NJ 08544 USA
[6] Brookhaven Natl Lab, Phys Dept, Upton, NY 11973 USA
[7] Flatiron Inst, Ctr Computat Astrophys, 162 Fifth Ave, New York, NY 10010 USA
基金
英国科学技术设施理事会; 美国国家航空航天局; 日本科学技术振兴机构; 欧洲研究理事会; 日本学术振兴会; 美国国家科学基金会;
关键词
power spectrum; weak gravitational lensing; COSMOLOGICAL PARAMETER CONSTRAINTS; MICROWAVE BACKGROUND TEMPERATURE; INTRINSIC CORRELATION; STATISTICAL-ANALYSIS; GALAXY SHAPES; LENSING BIAS; WEAK; SIMULATIONS; COVARIANCE; ESTIMATORS;
D O I
10.1088/1475-7516/2021/03/067
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Cosmic shear is one of the most powerful probes of Dark Energy, targeted by several current and future galaxy surveys. Lensing shear, however, is only sampled at the positions of galaxies with measured shapes in the catalog, making its associated sky window function one of the most complicated amongst all projected cosmological probes of inhomogeneities, as well as giving rise to inhomogeneous noise. Partly for this reason, cosmic shear analyses have been mostly carried out in real-space, making use of correlation functions, as opposed to Fourier-space power spectra. Since the use of power spectra can yield complementary information and has numerical advantages over real-space pipelines, it is important to develop a complete formalism describing the standard unbiased power spectrum estimators as well as their associated uncertainties. Building on previous work, this paper contains a study of the main complications associated with estimating and interpreting shear power spectra, and presents fast and accurate methods to estimate two key quantities needed for their practical usage: the noise bias and the Gaussian covariance matrix, fully accounting for survey geometry, with some of these results also applicable to other cosmological probes. We demonstrate the performance of these methods by applying them to the latest public data releases of the Hyper Suprime-Cam and the Dark Energy Survey collaborations, quantifying the presence of systematics in our measurements and the validity of the covariance matrix estimate. We make the resulting power spectra, covariance matrices, null tests and all associated data necessary for a full cosmological analysis publicly available.
引用
收藏
页数:45
相关论文
共 100 条
[81]   On the insufficiency of arbitrarily precise covariance matrices: non-Gaussian weak-lensing likelihoods [J].
Sellentin, Elena ;
Heavens, Alan F. .
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2018, 473 (02) :2355-2363
[82]   Mitigating Shear-dependent Object Detection Biases with Metacalibration [J].
Sheldon, Erin S. ;
Becker, Matthew R. ;
MacCrann, Niall ;
Jarvis, Michael .
ASTROPHYSICAL JOURNAL, 2020, 902 (02)
[83]   Practical Weak-lensing Shear Measurement with Metacalibration [J].
Sheldon, Erin S. ;
Huff, Eric M. .
ASTROPHYSICAL JOURNAL, 2017, 841 (01)
[84]   Power spectrum super-sample covariance [J].
Takada, Masahiro ;
Hu, Wayne .
PHYSICAL REVIEW D, 2013, 87 (12)
[85]   The impact of non-Gaussian errors on weak lensing surveys [J].
Takada, Masahiro ;
Jain, Bhuvnesh .
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2009, 395 (04) :2065-2086
[86]   How to measure CMB power spectra without losing information [J].
Tegmark, M .
PHYSICAL REVIEW D, 1997, 55 (10) :5895-5907
[87]   Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear [J].
Troxel, M. A. ;
MacCrann, N. ;
Zuntz, J. ;
Eifler, T. F. ;
Krause, E. ;
Dodelson, S. ;
Gruen, D. ;
Blazek, J. ;
Friedrich, O. ;
Samuroff, S. ;
Prat, J. ;
Secco, L. F. ;
Davis, C. ;
Ferte, A. ;
DeRose, J. ;
Alarcon, A. ;
Amara, A. ;
Baxter, E. ;
Becker, M. R. ;
Bernstein, G. M. ;
Bridle, S. L. ;
Cawthon, R. ;
Chang, C. ;
Choi, A. ;
De Vicente, J. ;
Drlica-Wagner, A. ;
Elvin-Poole, J. ;
Frieman, J. ;
Gatti, M. ;
Hartley, W. G. ;
Honscheid, K. ;
Hoyle, B. ;
Huff, E. M. ;
Huterer, D. ;
Jain, B. ;
Jarvis, M. ;
Kacprzak, T. ;
Kirk, D. ;
Kokron, N. ;
Krawiec, C. ;
Lahav, O. ;
Liddle, A. R. ;
Peacock, J. ;
Rau, M. M. ;
Refregier, A. ;
Rollins, R. P. ;
Rozo, E. ;
Rykoff, E. S. ;
Sanchez, C. ;
Sevilla-Noarbe, I. .
PHYSICAL REVIEW D, 2018, 98 (04)
[88]   RETRACTED: Survey geometry and the internal consistency of recent cosmic shear measurements (Retracted Article) [J].
Troxel, M. A. ;
Krause, E. ;
Chang, C. ;
Eifler, T. F. ;
Friedrich, O. ;
Gruen, D. ;
MacCrann, N. ;
Chen, A. ;
Davis, C. ;
DeRose, J. ;
Dodelson, S. ;
Gatti, M. ;
Hoyle, B. ;
Huterer, D. ;
Jarvis, M. ;
Lacasa, F. ;
Lemos, P. ;
Peiris, H. V. ;
Prat, J. ;
Samuroff, S. ;
Sanchez, C. ;
Sheldon, E. ;
Vielzeuf, P. ;
Wang, M. ;
Zuntz, J. ;
Lahav, O. ;
Abdalla, F. B. ;
Allam, S. ;
Annis, J. ;
Avila, S. ;
Bertin, E. ;
Brooks, D. ;
Burke, D. L. ;
Rosell, A. Carnero ;
Kind, M. Carrasco ;
Carretero, J. ;
Crocce, M. ;
Cunha, C. E. ;
D'Andrea, C. B. ;
da Costa, L. N. ;
De Vicente, J. ;
Diehl, H. T. ;
Doel, P. ;
Evrard, A. E. ;
Flaugher, B. ;
Fosalba, P. ;
Frieman, J. ;
Garcia-Bellido, J. ;
Gaztanaga, E. ;
Gerdes, D. W. .
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2018, 479 (04) :4998-5004
[89]   The NumPy Array: A Structure for Efficient Numerical Computation [J].
van der Walt, Stefan ;
Colbert, S. Chris ;
Varoquaux, Gael .
COMPUTING IN SCIENCE & ENGINEERING, 2011, 13 (02) :22-30
[90]  
Van Waerbeke L, 2000, ASTRON ASTROPHYS, V358, P30