The Websky extragalactic CMB simulations

We present a new pipeline for the efficient generation of synthetic observations of the extragalactic microwave sky, tailored to large ground-based CMB experiments such as the Simons Observatory, Advanced ACTPol, SPT-3G, and CMB-S4. Such simulated observations are a key technical challenge in cosmology because of the dynamic range and accuracy required. The first part of the pipeline generates a random cosmological realization in the form of a dark matter halo catalog and matter displacement field, as seen from a given position. The halo catalog and displacement field are modeled with ellipsoidal collapse dynamics and Lagrangian perturbation theory, respectively. In the second part, the cosmological realization is converted into a set of intensity maps over the range 10–103 GHz using models based on existing observations and hydrodynamical simulations. These maps include infrared emission from dusty star forming galaxies (CIB), Comptonization of CMB photons by hot gas in groups and clusters through the thermal Sunyaev-Zel'dovich effect (tSZ), Doppler boosting by Thomson scattering of the CMB by bulk flows through the kinetic Sunyaev-Zel'dovich effect (kSZ), and weak gravitational lensing of primary CMB anisotropies by the large-scale distribution of matter in the universe. After describing the pipeline and its implementation, we present the Websky maps, created from a realization of the cosmic web on our past light cone in the redshift interval 0<z<4.6 over the full-sky and a volume of ∼ 600 (Gpc/h)3 resolved with ∼1012 resolution elements. The Websky maps and halo catalog are publicly available at https://mocks.cita.utoronto.ca/websky.

[1]  Edward J. Wollack,et al.  Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect , 2020, Physical Review D.

[2]  Adrian T. Lee,et al.  Galaxy Clusters Selected via the Sunyaev–Zel’dovich Effect in the SPTpol 100-square-degree Survey , 2019, The Astronomical Journal.

[3]  R. B. Barreiro,et al.  Planck 2018 results , 2018, Astronomy & Astrophysics.

[4]  Ching-Hsing Yu,et al.  Deploying a Top-100 Supercomputer for Large Parallel Workloads: the Niagara Supercomputer , 2019, PEARC.

[5]  A. Lewis,et al.  CMB lensing reconstruction biases in cross-correlation with large-scale structure probes , 2019, Journal of Cosmology and Astroparticle Physics.

[6]  S. Meyer,et al.  A Measurement of the Cosmic Microwave Background Lensing Potential and Power Spectrum from 500 deg2 of SPTpol Temperature and Polarization Data , 2019, The Astrophysical Journal.

[7]  G. Holder,et al.  An excess of non-Gaussian fluctuations in the cosmic infrared background consistent with gravitational lensing , 2019, 1905.02084.

[8]  G. Lagache,et al.  Large-scale Maps of the Cosmic Infrared Background from Planck , 2019, The Astrophysical Journal.

[9]  D. Gerdes,et al.  Constraints on the redshift evolution of astrophysical feedback with Sunyaev-Zel’dovich effect cross-correlations , 2019, Physical Review D.

[10]  Leo Singer,et al.  healpy: equal area pixelization and spherical harmonics transforms for data on the sphere in Python , 2019, J. Open Source Softw..

[11]  Wei Chen,et al.  Learning to predict the cosmological structure formation , 2018, Proceedings of the National Academy of Sciences.

[12]  Hal Finkel,et al.  The Borg Cube Simulation: Cosmological Hydrodynamics with CRK-SPH , 2018, The Astrophysical Journal.

[13]  Edward J. Wollack,et al.  The Simons Observatory: science goals and forecasts , 2018, Journal of Cosmology and Astroparticle Physics.

[14]  P. Fosalba,et al.  Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles , 2018, Monthly Notices of the Royal Astronomical Society.

[15]  P. Amaro-Seoane,et al.  Our supermassive black hole rivaled the Sun in the ancient X-ray sky , 2014, Journal of Cosmology and Astroparticle Physics.

[16]  S. Pilipenko,et al.  Modelling Cosmic Infrared Background with evolving galaxies , 2018, 1812.08575.

[17]  George Stein,et al.  The mass-Peak Patch algorithm for fast generation of deep all-sky dark matter halo catalogues and itsN-body validation , 2018, Monthly Notices of the Royal Astronomical Society.

[18]  R. B. Barreiro,et al.  Planck2018 results , 2018, Astronomy & Astrophysics.

[19]  Pablo Fosalba,et al.  Comparing approximate methods for mock catalogues and covariance matrices – III: bispectrum , 2018, Monthly Notices of the Royal Astronomical Society.

[20]  P. Fosalba,et al.  Comparing approximate methods for mock catalogues and covariance matrices – I. Correlation function , 2018, Monthly Notices of the Royal Astronomical Society.

[21]  D. Beck,et al.  Lensing reconstruction in post-Born cosmic microwave background weak lensing , 2018, Physical Review D.

[22]  Philippe Berger,et al.  A volumetric deep Convolutional Neural Network for simulation of dark matter halo catalogues , 2018, Monthly Notices of the Royal Astronomical Society.

[23]  U. Seljak,et al.  A gradient based method for modeling baryons and matter in halos of fast simulations , 2018, Journal of Cosmology and Astroparticle Physics.

[24]  E. Komatsu,et al.  Dark energy constraints from the thermal Sunyaev–Zeldovich power spectrum , 2017, 1712.00788.

[25]  David N. Spergel,et al.  The Atacama Cosmology Telescope: The Two-season ACTPol Sunyaev–Zel’dovich Effect Selected Cluster Catalog , 2017, 1709.05600.

[26]  Cca,et al.  First results from the IllustrisTNG simulations: matter and galaxy clustering , 2017, 1707.03397.

[27]  J. Richard Bond,et al.  The Impact of Baryonic Physics on the Kinetic Sunyaev–Zel’dovich Effect , 2017, 1710.02792.

[28]  S. Pilipenko,et al.  A model of the cosmic infrared background produced by distant galaxies , 2017, 1710.06665.

[29]  David N. Spergel,et al.  Two-season Atacama Cosmology Telescope polarimeter lensing power spectrum , 2017 .

[30]  R. Takahashi,et al.  Full-sky Gravitational Lensing Simulation for Large-area Galaxy Surveys and Cosmic Microwave Background Experiments , 2017, 1706.01472.

[31]  M. Baldi,et al.  The kinematic Sunyaev-Zel'dovich effect of the large-scale structure (I): dependence on neutrino mass , 2017, 1702.00676.

[32]  J. Mohr,et al.  SZE observables, pressure profiles and centre offsets in Magneticum simulation galaxy clusters , 2016, 1612.05266.

[33]  J. Schaye,et al.  The BAHAMAS project: Calibrated hydrodynamical simulations for large-scale structure cosmology , 2016, 1603.02702.

[34]  N. Battaglia The tau of galaxy clusters , 2016, 1607.02442.

[35]  Edward J. Wollack,et al.  Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope , 2016, 1607.02139.

[36]  C. Pichon,et al.  The Horizon-AGN Simulation: Morphological Diversity of Galaxies ,Promoted by AGN Feedback , 2016, 1606.03086.

[37]  A. G. Vieregg,et al.  Bicep2/KECK ARRAY VIII: MEASUREMENT OF GRAVITATIONAL LENSING FROM LARGE-SCALE B-MODE POLARIZATION , 2016, 1606.01968.

[38]  J. Frieman,et al.  Detection of the kinematic Sunyaev-Zel'dovich effect with DES Year 1 and SPT , 2016, 1603.03904.

[39]  D. Spergel,et al.  Kinematic Sunyaev-Zel'dovich Effect with Projected Fields: A Novel Probe of the Baryon Distribution with Planck, WMAP, and WISE Data. , 2016, Physical review letters.

[40]  P. Mcdonald,et al.  FastPM: a new scheme for fast simulations of dark matter and haloes , 2016, 1603.00476.

[41]  Klaus Dolag,et al.  SZ effects in the Magneticum Pathfinder Simulation: Comparison with the Planck, SPT, and ACT results , 2015, 1509.05134.

[42]  Pablo Fosalba,et al.  ICE-COLA: towards fast and accurate synthetic galaxy catalogues optimizing a quasi-N-body method , 2015, 1509.04685.

[43]  R. B. Barreiro,et al.  Planck 2015 results - XXII. A map of the thermal Sunyaev-Zeldovich effect , 2015, 1502.01596.

[44]  Marcelo A. Alvarez,et al.  THE KINETIC SUNYAEV–ZEL’DOVICH EFFECT FROM REIONIZATION: SIMULATED FULL-SKY MAPS AT ARCMINUTE RESOLUTION , 2015, 1511.02846.

[45]  S. Flender,et al.  SIMULATIONS OF THE PAIRWISE KINEMATIC SUNYAEV–ZEL’DOVICH SIGNAL , 2015, 1511.02843.

[46]  C. A. Oxborrow,et al.  Planck 2015 results: XXIII. The thermal Sunyaev-Zeldovich effect-cosmic infrared background correlation , 2015, 1509.06555.

[47]  C. A. Oxborrow,et al.  Planck 2015 results Special feature Planck 2015 results XXVII . The second Planck catalogue of Sunyaev-Zeldovich sources , 2016 .

[48]  Chris Power,et al.  halogen: a tool for fast generation of mock halo catalogues , 2014, 1412.5228.

[49]  D. Spergel,et al.  THE STACKED THERMAL SUNYAEV–ZEL’DOVICH SIGNAL OF LOCALLY BRIGHTEST GALAXIES IN PLANCK FULL MISSION DATA: EVIDENCE FOR GALAXY FEEDBACK? , 2014, 1409.6747.

[50]  J. Bond,et al.  ON THE CLUSTER PHYSICS OF SUNYAEV–ZEL’DOVICH AND X-RAY SURVEYS. IV. CHARACTERIZING DENSITY AND PRESSURE CLUMPING DUE TO INFALLING SUBSTRUCTURES , 2014, 1405.3346.

[51]  T. D. Matteo,et al.  The MassiveBlack-II simulation: The evolution of haloes and galaxies to z ~ 0 , 2014, 1402.0888.

[52]  C. Baccigalupi,et al.  Multiple lensing of the cosmic microwave background anisotropies , 2014, 1409.7680.

[53]  Adrian T. Lee,et al.  GALAXY CLUSTERS DISCOVERED VIA THE SUNYAEV–ZEL'DOVICH EFFECT IN THE 2500-SQUARE-DEGREE SPT-SZ SURVEY , 2014, 1409.0850.

[54]  M. Lueker,et al.  A MEASUREMENT OF SECONDARY COSMIC MICROWAVE BACKGROUND ANISOTROPIES FROM THE 2500 SQUARE-DEGREE SPT-SZ SURVEY , 2014, 1408.3161.

[55]  M Hazumi,et al.  Measurement of the cosmic microwave background polarization lensing power spectrum with the POLARBEAR experiment. , 2013, Physical review letters.

[56]  J. Schaye,et al.  Towards a realistic population of simulated galaxy groups and clusters , 2013, 1312.5462.

[57]  Fangzhou Jiang,et al.  Generating merger trees for dark matter haloes: a comparison of methods , 2013, 1311.5225.

[58]  C. A. Oxborrow,et al.  Planck 2013 results. XXX. Cosmic infrared background measurements and implications for star formation , 2013, 1309.0382.

[59]  Francisco-Shu Kitaura,et al.  Modelling baryon acoustic oscillations with perturbation theory and stochastic halo biasing , 2013, 1307.3285.

[60]  G. W. Pratt,et al.  Planck2013 results. XXIX. ThePlanckcatalogue of Sunyaev-Zeldovich sources , 2013, Astronomy &amp; Astrophysics.

[61]  G. W. Pratt,et al.  Planck 2013 results. XVIII. The gravitational lensing-infrared background correlation , 2013, 1303.5078.

[62]  G. P. Holder,et al.  CMB LENSING POWER SPECTRUM BIASES FROM GALAXIES AND CLUSTERS USING HIGH-ANGULAR RESOLUTION TEMPERATURE MAPS , 2013, 1310.7023.

[63]  S. Borgani,et al.  An accurate tool for the fast generation of dark matter halo catalogues. , 2013, 1305.1505.

[64]  M. Lueker,et al.  A COSMIC MICROWAVE BACKGROUND LENSING MASS MAP AND ITS CORRELATION WITH THE COSMIC INFRARED BACKGROUND , 2013, 1303.5048.

[65]  Peter A. R. Ade,et al.  The Atacama Cosmology Telescope: cosmological parameters from three seasons of data , 2013, 1301.0824.

[66]  Matias Zaldarriaga,et al.  Solving large scale structure in ten easy steps with COLA , 2013, 1301.0322.

[67]  Elena Pierpaoli,et al.  SUNYAEV–ZEL'DOVICH-MEASURED PRESSURE PROFILES FROM THE BOLOCAM X-RAY/SZ GALAXY CLUSTER SAMPLE , 2012, 1211.1632.

[68]  J. Bond,et al.  ON THE CLUSTER PHYSICS OF SUNYAEV–ZEL'DOVICH AND X-RAY SURVEYS. III. MEASUREMENT BIASES AND COSMOLOGICAL EVOLUTION OF GAS AND STELLAR MASS FRACTIONS , 2012, 1209.4082.

[69]  J. Brinkmann,et al.  The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey:a large sample of mock galaxy catalogues , 2012, 1203.6609.

[70]  Matthew Hasselfield,et al.  The Atacama Cosmology Telescope: Sunyaev-Zel'dovich selected galaxy clusters at 148 GHz from three seasons of data , 2013 .

[71]  L. Haw,et al.  A MEASUREMENT OF GRAVITATIONAL LENSING OF THE MICROWAVE BACKGROUND USING SOUTH POLE TELESCOPE DATA , 2013 .

[72]  Douglas Scott,et al.  A UNIFIED EMPIRICAL MODEL FOR INFRARED GALAXY COUNTS BASED ON THE OBSERVED PHYSICAL EVOLUTION OF DISTANT GALAXIES , 2012, 1208.6512.

[73]  H. Nguyen,et al.  HerMES: COSMIC INFRARED BACKGROUND ANISOTROPIES AND THE CLUSTERING OF DUSTY STAR-FORMING GALAXIES , 2012, 1208.5049.

[74]  Takahiro Nishimichi,et al.  REVISING THE HALOFIT MODEL FOR THE NONLINEAR MATTER POWER SPECTRUM , 2012, 1208.2701.

[75]  G. W. Pratt,et al.  Planck intermediate results: V. Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect , 2012, 1207.4061.

[76]  M. Lueker,et al.  GALAXY CLUSTERS DISCOVERED VIA THE SUNYAEV–ZEL’DOVICH EFFECT IN THE FIRST 720 SQUARE DEGREES OF THE SOUTH POLE TELESCOPE SURVEY , 2012, 1203.5775.

[77]  Adrian T. Lee,et al.  A MEASUREMENT OF GRAVITATIONAL LENSING OF THE MICROWAVE BACKGROUND USING SOUTH POLE TELESCOPE DATA , 2012, 1202.0546.

[78]  J. R. Bond,et al.  ON THE CLUSTER PHYSICS OF SUNYAEV–ZEL'DOVICH AND X-RAY SURVEYS. II. DECONSTRUCTING THE THERMAL SZ POWER SPECTRUM , 2011, 1109.3711.

[79]  Daisuke Nagai,et al.  DECONSTRUCTING THE KINETIC SZ POWER SPECTRUM , 2011, 1109.0553.

[80]  Z. Haiman,et al.  Improved models for cosmic infrared background anisotropies: new constraints on the infrared galaxy population , 2011, 1109.1522.

[81]  R. B. Barreiro,et al.  Planck early results. XVIII. The power spectrum of cosmic infrared background anisotropies , 2011, 1101.2028.

[82]  H. Trac,et al.  TEMPLATES FOR THE SUNYAEV–ZEL’DOVICH ANGULAR POWER SPECTRUM , 2010, 1006.2828.

[83]  H. Dole,et al.  Simulations of the cosmic infrared and submillimeter background for future large surveys: II. Removing the low-redshift contribution to the anisotropies using stacking , 2010, 1004.0123.

[84]  J. R. Bond,et al.  SIMULATIONS OF THE SUNYAEV–ZEL'DOVICH POWER SPECTRUM WITH ACTIVE GALACTIC NUCLEUS FEEDBACK , 2010, 1003.4256.

[85]  G. W. Pratt,et al.  The universal galaxy cluster pressure profile from a representative sample of nearby systems (REXCESS) and the Y-SZ-M-500 relation , 2009, 0910.1234.

[86]  Jeremiah P. Ostriker,et al.  SIMULATIONS OF THE MICROWAVE SKY , 2009, 0908.0540.

[87]  S. Kay,et al.  Statistics of the Sunyaev–Zel'dovich effect power spectrum , 2009, 0903.5473.

[88]  P. A. R. Ade,et al.  GALAXY CLUSTERS DISCOVERED WITH A SUNYAEV–ZEL'DOVICH EFFECT SURVEY , 2008, 0810.1578.

[89]  R. B. Barreiro,et al.  Component separation methods for the PLANCK mission , 2008, 0805.0269.

[90]  S. Kay,et al.  Dark matter halo concentrations in the Wilkinson Microwave Anisotropy Probe year 5 cosmology , 2008, 0804.2486.

[91]  Michael S. Warren,et al.  Toward a Halo Mass Function for Precision Cosmology: The Limits of Universality , 2008, 0803.2706.

[92]  M. Meneghetti,et al.  Statistical properties of SZ and X-ray cluster detections , 2008, 0802.1200.

[93]  G. Lagache,et al.  Simulations of the cosmic infrared and submillimeter background for future large surveys I. Presentation and first application to Herschel/SPIRE and Planck/HFI , 2008, 0801.4299.

[94]  C. Baccigalupi,et al.  Full-sky maps for gravitational lensing of the cosmic microwave background , 2007, 0711.2655.

[95]  Los Alamos National Laboratory,et al.  The Santa Fe Light Cone Simulation Project. I. Confusion and the Warm-Hot Intergalactic Medium in Upcoming Sunyaev-Zel’dovich Effect Surveys , 2007, 0704.2607.

[96]  L. Moscardini,et al.  The Sunyaev–Zel'dovich effects from a cosmological hydrodynamical simulation: large-scale properties and correlation with the soft X-ray signal , 2007, astro-ph/0701680.

[97]  H. Trac,et al.  Microwave Sky Simulations and Projections for Galaxy Cluster Detection with the Atacama Cosmology Telescope , 2006, astro-ph/0612140.

[98]  T. Ensslin,et al.  Simulating cosmic rays in clusters of galaxies – I. Effects on the Sunyaev–Zel'dovich effect and the X-ray emission , 2006, astro-ph/0611037.

[99]  M. Bartelmann,et al.  Detecting Sunyaev–Zel'dovich clusters with Planck– III. Properties of the expected SZ cluster sample , 2006, astro-ph/0602406.

[100]  D. Nagai,et al.  The Impact of Galaxy Formation on the Sunyaev-Zel'dovich Effect of Galaxy Clusters , 2005, astro-ph/0512208.

[101]  Jack O. Burns,et al.  Accepted to ApJ Letters Preprint typeset using L ATEX style emulateapj v. 6/22/04 THE INTEGRATED SUNYAEV-ZELDOVICH EFFECT AS THE SUPERIOR METHOD FOR MEASURING THE MASS OF CLUSTERS OF GALAXIES , 2005 .

[102]  K. Gorski,et al.  HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere , 2004, astro-ph/0409513.

[103]  M. Bartelmann,et al.  Detecting Sunyaev-Zel'dovich clusters with Planck - I. Construction of all-sky thermal and kinetic SZ maps , 2004, astro-ph/0407089.

[104]  J. Gonz'alez-Nuevo,et al.  Predictions of the Angular Power Spectrum of Clustered Extragalactic Point Sources at Cosmic Microwave Background Frequencies from Flat and All-Sky Two-dimensional Simulations , 2004, astro-ph/0405553.

[105]  L. Moscardini,et al.  Measuring cluster peculiar velocities with the Sunyaev-Zel'dovich effect: scaling relations and systematics , 2004, astro-ph/0405365.

[106]  L. Toffolatti,et al.  EPSS-2 D : a fast computer code for simulating all – sky maps of clustered extragalactic point sources , 2004 .

[107]  Wayne Hu,et al.  Cosmic microwave background lensing reconstruction on the full sky , 2003 .

[108]  Wayne Hu,et al.  CMB Lensing Reconstruction on the Full Sky , 2003, astro-ph/0301031.

[109]  J. Peacock,et al.  Stable clustering, the halo model and non-linear cosmological power spectra , 2002, astro-ph/0207664.

[110]  Caltech,et al.  The Far-Infrared Background Correlation with Cosmic Microwave Background Lensing , 2002, astro-ph/0209001.

[111]  M. White,et al.  Simulating the Sunyaev-Zeldovich Effect(s): Including Radiative Cooling and Energy Injection by Galactic Winds , 2002, astro-ph/0205437.

[112]  T. Theuns,et al.  The pinocchio algorithm: pinpointing orbit-crossing collapsed hierarchical objects in a linear density field , 2001, astro-ph/0109323.

[113]  A. Balbi,et al.  WOMBAT & FORECAST: Making Realistic Maps of the Microwave Sky , 1999, astro-ph/9903248.

[114]  G. Smoot,et al.  Contribution of Extragalactic Infrared Sources to Cosmic Microwave Background Foreground Anisotropy , 1996, astro-ph/9603121.

[115]  J. Bond,et al.  The Peak-Patch Picture of Cosmic Catalogs. II. Validation , 1996 .

[116]  J. Bond,et al.  The Peak-Patch Picture of Cosmic Catalogs. I. Algorithms , 1996 .

[117]  HongSheng Zhao Analytical models for galactic nuclei , 1995, astro-ph/9509122.

[118]  S. Colombi,et al.  Perturbative Lagrangian Approach to Gravitational Instability , 1994, astro-ph/9406013.

[119]  S. Cole,et al.  Sunyaev–Zel'dovich fluctuations in the cold dark matter scenario , 1988 .

[120]  Nick Kaiser,et al.  Evolution and clustering of rich clusters , 1986 .

[121]  Y. Zeldovich,et al.  The interaction of matter and radiation in a hot-model universe , 1969 .