Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data
Abstract
Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg2 field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 0 < S/N < 4 . To predict the peak counts as a function of cosmological parameters, we use a suite of N-body simulations spanning 158 models with varying Ωm and σ8, fixing w = –1, Ωb = 0.04, h = 0.7 and ns = 1, to which we have applied the DES SV mask and redshift distribution. In our fiducial analysis we measure σ8(Ωm/0.3)0.6 = 0.77 ± 0.07, after marginalizing over the shear multiplicative bias and the error on the mean redshift of the galaxy sample. We introduce models of intrinsic alignments, blending and source contamination by cluster members. These models indicate that peaks with S/N > 4 would require significant corrections, which is why we do not include them in our analysis. We compare our results tomore »
- Authors:
- more »
- Publication Date:
- Research Org.:
- Brookhaven National Laboratory (BNL), Upton, NY (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); The Ohio State Univ., Columbus, OH (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Contributing Org.:
- The DES Collaboration
- OSTI Identifier:
- 1351749
- Alternate Identifier(s):
- OSTI ID: 1254143; OSTI ID: 1360807; OSTI ID: 1602520
- Report Number(s):
- BNL-113770-2017-JA; FERMILAB-PUB-15-566-AE; arXiv:1603.05040
Journal ID: ISSN 0035-8711; TRN: US1701708
- Grant/Contract Number:
- SC0012704; AC02-76SF00515; AC02-07CH11359; SC0011726
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Additional Journal Information:
- Journal Volume: 463; Journal Issue: 4; Journal ID: ISSN 0035-8711
- Publisher:
- Royal Astronomical Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTRONOMY AND ASTROPHYSICS; gravitational lensing: weak; methods: data analysis; methods: statistical; cosmological parameter; cosmology: observations; dark matter; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Citation Formats
Kacprzak, T., Kirk, D., Friedrich, O., Amara, A., Refregier, A., Marian, L., Dietrich, J. P., Suchyta, E., Aleksić, J., Bacon, D., Becker, M. R., Bonnett, C., Bridle, S. L., Chang, C., Eifler, T. F., Hartley, W. G., Huff, E. M., Krause, E., MacCrann, N., Melchior, P., Nicola, A., Samuroff, S., Sheldon, E., Troxel, M. A., Weller, J., Zuntz, J., Abbott, T. M. C., Abdalla, F. B., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Crocce, M., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Evrard, A. E., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jarvis, M., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., March, M., Marshall, J. L., Martini, P., Miller, C. J., Miquel, R., Mohr, J. J., Nichol, R. C., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Rykoff, E. S., Sanchez, E., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., and Zhang, Y. Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data. United States: N. p., 2016.
Web. doi:10.1093/mnras/stw2070.
Kacprzak, T., Kirk, D., Friedrich, O., Amara, A., Refregier, A., Marian, L., Dietrich, J. P., Suchyta, E., Aleksić, J., Bacon, D., Becker, M. R., Bonnett, C., Bridle, S. L., Chang, C., Eifler, T. F., Hartley, W. G., Huff, E. M., Krause, E., MacCrann, N., Melchior, P., Nicola, A., Samuroff, S., Sheldon, E., Troxel, M. A., Weller, J., Zuntz, J., Abbott, T. M. C., Abdalla, F. B., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Crocce, M., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Evrard, A. E., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jarvis, M., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., March, M., Marshall, J. L., Martini, P., Miller, C. J., Miquel, R., Mohr, J. J., Nichol, R. C., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Rykoff, E. S., Sanchez, E., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., & Zhang, Y. Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data. United States. https://doi.org/10.1093/mnras/stw2070
Kacprzak, T., Kirk, D., Friedrich, O., Amara, A., Refregier, A., Marian, L., Dietrich, J. P., Suchyta, E., Aleksić, J., Bacon, D., Becker, M. R., Bonnett, C., Bridle, S. L., Chang, C., Eifler, T. F., Hartley, W. G., Huff, E. M., Krause, E., MacCrann, N., Melchior, P., Nicola, A., Samuroff, S., Sheldon, E., Troxel, M. A., Weller, J., Zuntz, J., Abbott, T. M. C., Abdalla, F. B., Armstrong, R., Benoit-Lévy, A., Bernstein, G. M., Bernstein, R. A., Bertin, E., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Crocce, M., D'Andrea, C. B., da Costa, L. N., Desai, S., Diehl, H. T., Evrard, A. E., Neto, A. Fausti, Flaugher, B., Fosalba, P., Frieman, J., Gerdes, D. W., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., Jain, B., James, D. J., Jarvis, M., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., March, M., Marshall, J. L., Martini, P., Miller, C. J., Miquel, R., Mohr, J. J., Nichol, R. C., Nord, B., Plazas, A. A., Romer, A. K., Roodman, A., Rykoff, E. S., Sanchez, E., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, R. C., Soares-Santos, M., Sobreira, F., Swanson, M. E. C., Tarle, G., Thomas, D., Vikram, V., Walker, A. R., and Zhang, Y. 2016.
"Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data". United States. https://doi.org/10.1093/mnras/stw2070. https://www.osti.gov/servlets/purl/1351749.
@article{osti_1351749,
title = {Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data},
author = {Kacprzak, T. and Kirk, D. and Friedrich, O. and Amara, A. and Refregier, A. and Marian, L. and Dietrich, J. P. and Suchyta, E. and Aleksić, J. and Bacon, D. and Becker, M. R. and Bonnett, C. and Bridle, S. L. and Chang, C. and Eifler, T. F. and Hartley, W. G. and Huff, E. M. and Krause, E. and MacCrann, N. and Melchior, P. and Nicola, A. and Samuroff, S. and Sheldon, E. and Troxel, M. A. and Weller, J. and Zuntz, J. and Abbott, T. M. C. and Abdalla, F. B. and Armstrong, R. and Benoit-Lévy, A. and Bernstein, G. M. and Bernstein, R. A. and Bertin, E. and Brooks, D. and Burke, D. L. and Rosell, A. Carnero and Kind, M. Carrasco and Carretero, J. and Castander, F. J. and Crocce, M. and D'Andrea, C. B. and da Costa, L. N. and Desai, S. and Diehl, H. T. and Evrard, A. E. and Neto, A. Fausti and Flaugher, B. and Fosalba, P. and Frieman, J. and Gerdes, D. W. and Goldstein, D. A. and Gruen, D. and Gruendl, R. A. and Gutierrez, G. and Honscheid, K. and Jain, B. and James, D. J. and Jarvis, M. and Kuehn, K. and Kuropatkin, N. and Lahav, O. and Lima, M. and March, M. and Marshall, J. L. and Martini, P. and Miller, C. J. and Miquel, R. and Mohr, J. J. and Nichol, R. C. and Nord, B. and Plazas, A. A. and Romer, A. K. and Roodman, A. and Rykoff, E. S. and Sanchez, E. and Scarpine, V. and Schubnell, M. and Sevilla-Noarbe, I. and Smith, R. C. and Soares-Santos, M. and Sobreira, F. and Swanson, M. E. C. and Tarle, G. and Thomas, D. and Vikram, V. and Walker, A. R. and Zhang, Y.},
abstractNote = {Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg2 field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 0 < S/N < 4 . To predict the peak counts as a function of cosmological parameters, we use a suite of N-body simulations spanning 158 models with varying Ωm and σ8, fixing w = –1, Ωb = 0.04, h = 0.7 and ns = 1, to which we have applied the DES SV mask and redshift distribution. In our fiducial analysis we measure σ8(Ωm/0.3)0.6 = 0.77 ± 0.07, after marginalizing over the shear multiplicative bias and the error on the mean redshift of the galaxy sample. We introduce models of intrinsic alignments, blending and source contamination by cluster members. These models indicate that peaks with S/N > 4 would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two-point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. Lastly, we discuss prospects for future peak statistics analysis with upcoming DES data.},
doi = {10.1093/mnras/stw2070},
url = {https://www.osti.gov/biblio/1351749},
journal = {Monthly Notices of the Royal Astronomical Society},
issn = {0035-8711},
number = 4,
volume = 463,
place = {United States},
year = {Fri Aug 19 00:00:00 EDT 2016},
month = {Fri Aug 19 00:00:00 EDT 2016}
}
Web of Science
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