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Title: A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

Abstract

Here, we describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg 2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF–redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. Wemore » find a well-defined X-ray luminosity– λMCMF relation with an intrinsic scatter of δln ( λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF–mass relation.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [5];  [8];  [9];  [10];  [8];  [11];  [12];  [13];  [14];  [15];  [9];  [5];  [16] more »;  [17];  [18];  [19];  [8];  [20];  [21];  [9];  [22];  [12];  [23];  [24];  [25];  [26];  [5];  [13];  [25];  [27];  [5];  [28]; ORCiD logo [29];  [30];  [13] « less
  1. Ludwig-Maximilians-Univ. Munich (Germany); Max Planck Institute for Extraterrestrial Physics, Garching (Germany)
  2. Ludwig-Maximilians-Univ. Munich (Germany); Max Planck Institute for Extraterrestrial Physics, Garching (Germany); Excellence Cluster Universe, Garching (Germany)
  3. IIT Hyderabad, Telangana (India)
  4. Ludwig-Maximilians-Univ. Munich (Germany)
  5. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  6. Institut d'Astrophysique de Paris, Paris (France); Univ. College London, London (United Kingdom); UPMC Univ. Paris, Paris (France)
  7. Univ. College London, London (United Kingdom)
  8. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Observatorio Nacional, Rio de Janeiro (Brazil)
  9. Univ. of Illinois, Urbana, IL (United States); National Center for Supercomputing Applications, Urbana, IL (United States)
  10. Stanford Univ.,Stanford, CA (United States)
  11. Ludwig-Maximilians-Univ. Munich (Germany); Excellence Cluster Universe, Garching (Germany)
  12. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  13. Univ. of Michigan, Ann Arbor, MI (United States)
  14. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Univ. of Chicago, Chicago, IL (United States)
  15. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
  16. The Ohio State Univ., Columbus, OH (United States)
  17. Univ. of Washington, Seattle, WA (United States); National Optical Astronomy Observatory, La Serena (Chile)
  18. Australian Astronomical Observatory, North Ryde, NSW (Australia)
  19. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Univ. de Sao Paulo, Sao Paulo (Brazil)
  20. Univ. of Pennsylvania, Philadelphia, PA (United States)
  21. Princeton Univ., Princeton, NJ (United States)
  22. Institucio Catalana de Recerca i Estudis Avancats, Barcelona (Spain); The Barcelona Institute of Science and Technology, Bellaterra (Barcelona) (Spain)
  23. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  24. Univ. of Sussex, Brighton (United Kingdom)
  25. Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain)
  26. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Instituto de Fisica, Porto Alegre (Brazil)
  27. Univ. of Southampton, Southampton (United Kingdom)
  28. Lab. Interinstitucional de e-Astronomia - LIneA, Rio de Janeiro (Brazil); Univ. Federal do ABC, Santo Andre (Brazil)
  29. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  30. National Center for Supercomputing Applications, Urbana, IL (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Contributing Org.:
The DES Collaboration
OSTI Identifier:
1423126
Alternate Identifier(s):
OSTI ID: 1408217; OSTI ID: 1422381
Report Number(s):
arXiv:1706.06577; FERMILAB-PUB-17-025-AE
Journal ID: ISSN 0035-8711; TRN: US1801710
Grant/Contract Number:  
AC02-76SF00515; AC05-00OR22725; AC02-07CH11359
Resource Type:
Accepted Manuscript
Journal Name:
Monthly Notices of the Royal Astronomical Society
Additional Journal Information:
Journal Volume: 474; Journal Issue: 3; Journal ID: ISSN 0035-8711
Publisher:
Royal Astronomical Society
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; galaxies: clusters: general; galaxies: clusters: intracluster medium; galaxies: distances and redshifts; X-rays: galaxies: clusters

Citation Formats

Klein, M., Mohr, Joseph J., Desai, S., Israel, H., Allam, S., Benoit-Lévy, A., Brooks, D., Buckley-Geer, E., Carnero Rosell, A., Carrasco Kind, M., Cunha, C. E., da Costa, L. N., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Frieman, J., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Maia, M. A. G., March, M., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Reil, K., Romer, A. K., Sanchez, E., Santiago, B., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., and Tarle, G. A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets. United States: N. p., 2017. Web. doi:10.1093/mnras/stx2929.
Klein, M., Mohr, Joseph J., Desai, S., Israel, H., Allam, S., Benoit-Lévy, A., Brooks, D., Buckley-Geer, E., Carnero Rosell, A., Carrasco Kind, M., Cunha, C. E., da Costa, L. N., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Frieman, J., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Maia, M. A. G., March, M., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Reil, K., Romer, A. K., Sanchez, E., Santiago, B., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., & Tarle, G. A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets. United States. doi:10.1093/mnras/stx2929.
Klein, M., Mohr, Joseph J., Desai, S., Israel, H., Allam, S., Benoit-Lévy, A., Brooks, D., Buckley-Geer, E., Carnero Rosell, A., Carrasco Kind, M., Cunha, C. E., da Costa, L. N., Dietrich, J. P., Eifler, T. F., Evrard, A. E., Frieman, J., Gruen, D., Gruendl, R. A., Gutierrez, G., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Maia, M. A. G., March, M., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Reil, K., Romer, A. K., Sanchez, E., Santiago, B., Scarpine, V., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., and Tarle, G. Tue . "A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets". United States. doi:10.1093/mnras/stx2929. https://www.osti.gov/servlets/purl/1423126.
@article{osti_1423126,
title = {A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets},
author = {Klein, M. and Mohr, Joseph J. and Desai, S. and Israel, H. and Allam, S. and Benoit-Lévy, A. and Brooks, D. and Buckley-Geer, E. and Carnero Rosell, A. and Carrasco Kind, M. and Cunha, C. E. and da Costa, L. N. and Dietrich, J. P. and Eifler, T. F. and Evrard, A. E. and Frieman, J. and Gruen, D. and Gruendl, R. A. and Gutierrez, G. and Honscheid, K. and James, D. J. and Kuehn, K. and Lima, M. and Maia, M. A. G. and March, M. and Melchior, P. and Menanteau, F. and Miquel, R. and Plazas, A. A. and Reil, K. and Romer, A. K. and Sanchez, E. and Santiago, B. and Scarpine, V. and Schubnell, M. and Sevilla-Noarbe, I. and Smith, M. and Soares-Santos, M. and Sobreira, F. and Suchyta, E. and Swanson, M. E. C. and Tarle, G.},
abstractNote = {Here, we describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF–redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity–λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF–mass relation.},
doi = {10.1093/mnras/stx2929},
journal = {Monthly Notices of the Royal Astronomical Society},
number = 3,
volume = 474,
place = {United States},
year = {2017},
month = {11}
}

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