Separate Universe simulations with IllustrisTNG: baryonic effects on power spectrum responses and higher-order statistics

We measure power spectrum response functions in the presence of baryonic physical processes using separate universe simulations with the IllustrisTNG galaxy formation model. The response functions describe how the small-scale power spectrum reacts to long-wavelength perturbations and they can be efficiently measured with the separate universe technique by absorbing the effects of the long modes into a modified cosmology. Specifically, we focus on the total first-order matter power spectrum response to an isotropic density fluctuation R1(k, z), which is fully determined by the logarithmic derivative of the non-linear matter power spectrum dlnPm(k, z)/dlnk and the growth-only response function G1(k, z). We find that G1(k, z) is not affected by the baryonic physical processes in the simulations at redshifts z < 3 and on all scales probed (k ≲ 15 h Mpc−1; i.e. length scales $\gtrsim 0.4\, {\rm Mpc}\,h^{-1}$). In practice, this implies that the power spectrum fully specifies the baryonic dependence of its response function. Assuming an idealized lensing survey set-up, we evaluate numerically the baryonic impact on the squeezed-lensing bispectrum and the lensing supersample power spectrum covariance, which are given in terms of responses. Our results show that these higher-order lensing statistics can display varying levels of sensitivity to baryonic effects compared to the power spectrum, with the squeezed bispectrum being the least sensitive. We also show that ignoring baryonic effects on lensing covariances slightly overestimates the error budget (and is therefore conservative from the point of view of parameter error bars) and likely has negligible impact on parameter biases in inference analyses.

[1]  A. Barreira The squeezed matter bispectrum covariance with responses , 2019, Journal of Cosmology and Astroparticle Physics.

[2]  B. Hoyle,et al.  Graph Database Solution for Higher-order Spatial Statistics in the Era of Big Data , 2019, The Astrophysical Journal Supplement Series.

[3]  Annalisa Pillepich,et al.  The IllustrisTNG simulations: public data release , 2018, Computational Astrophysics and Cosmology.

[4]  C. Heymans,et al.  On the road to percent accuracy: non-linear reaction of the matter power spectrum to dark energy and modified gravity , 2018, Monthly Notices of the Royal Astronomical Society.

[5]  E. Armengaud,et al.  The one-dimensional power spectrum from the SDSS DR14 Lyα forests , 2018, Journal of Cosmology and Astroparticle Physics.

[6]  Eiichiro Komatsu,et al.  Position-dependent power spectra of the 21-cm signal from the epoch of reionization , 2018, Journal of Cosmology and Astroparticle Physics.

[7]  R. Teyssier,et al.  Quantifying baryon effects on the matter power spectrum and the weak lensing shear correlation , 2018, Journal of Cosmology and Astroparticle Physics.

[8]  David N. Spergel,et al.  Constraining neutrino mass with the tomographic weak lensing bispectrum , 2018, Journal of Cosmology and Astroparticle Physics.

[9]  David N. Spergel,et al.  Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data , 2018, Publications of the Astronomical Society of Japan.

[10]  Scott Dodelson,et al.  Modelling baryonic physics in future weak lensing surveys , 2018, Monthly Notices of the Royal Astronomical Society.

[11]  K. Benabed,et al.  Information content of the weak lensing bispectrum for the next generation of galaxy surveys , 2018 .

[12]  David Alonso,et al.  The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document , 2018, 1809.01669.

[13]  E. Krause,et al.  Accurate cosmic shear errors: do we need ensembles of simulations? , 2018, Journal of Cosmology and Astroparticle Physics.

[14]  David N. Spergel,et al.  Ingredients for 21 cm Intensity Mapping , 2018, The Astrophysical Journal.

[15]  S. White,et al.  Cosmological N-body simulations with a large-scale tidal field , 2018, Monthly Notices of the Royal Astronomical Society.

[16]  C. Pichon,et al.  The impact of baryons on the matter power spectrum from the Horizon-AGN cosmological hydrodynamical simulation , 2018, Monthly Notices of the Royal Astronomical Society.

[17]  Yu Feng,et al.  nbodykit: An Open-source, Massively Parallel Toolkit for Large-scale Structure , 2017, The Astronomical Journal.

[18]  S. Borgani,et al.  The effect of baryons in the cosmological lensing PDFs , 2017, 1711.10017.

[19]  E. Krause,et al.  Complete super-sample lensing covariance in the response approach , 2017, Journal of Cosmology and Astroparticle Physics.

[20]  M. Takada,et al.  Impact of large-scale tides on cosmological distortions via redshift-space power spectrum , 2017, 1711.00012.

[21]  B. Yanny,et al.  Dark Energy Survey year 1 results: Cosmological constraints from galaxy clustering and weak lensing , 2017, Physical Review D.

[22]  Karl Glazebrook,et al.  KiDS-450 + 2dFLenS: Cosmological parameter constraints from weak gravitational lensing tomography and overlapping redshift-space galaxy clustering , 2017, 1707.06627.

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

[24]  Annalisa Pillepich,et al.  First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies , 2017, 1707.03406.

[25]  V. Springel,et al.  First results from the IllustrisTNG simulations: radio haloes and magnetic fields , 2017, Monthly Notices of the Royal Astronomical Society.

[26]  E. Ramirez-Ruiz,et al.  First results from the IllustrisTNG simulations: a tale of two elements - chemical evolution of magnesium and europium , 2017, 1707.03401.

[27]  G. Kauffmann,et al.  First results from the IllustrisTNG simulations: the galaxy colour bimodality , 2017, 1707.03395.

[28]  Annalisa Pillepich,et al.  Simulating galaxy formation with the IllustrisTNG model , 2017, 1703.02970.

[29]  R. Croft,et al.  Line-Intensity Mapping: 2017 Status Report , 2017, 1709.09066.

[30]  Kazuhiro Yamamoto,et al.  Gravitational redshifts of clusters and voids , 2017, 1709.05756.

[31]  A. Barreira,et al.  Response approach to the matter power spectrum covariance , 2017, 1705.01092.

[32]  A. Barreira,et al.  Responses in large-scale structure , 2017, 1703.09212.

[33]  A. Slosar,et al.  Response approach to the squeezed-limit bispectrum: application to the correlation of quasar and Lyman-α forest power spectrum , 2017, 1701.03375.

[34]  M. Takada,et al.  Large-scale tidal effect on redshift-space power spectrum in a finite-volume survey , 2016, 1611.04723.

[35]  Kwan Chuen Chan,et al.  Assessment of the Information Content of the Power Spectrum and Bispectrum , 2016, 1610.06585.

[36]  V. Springel,et al.  Simulating galaxy formation with black hole driven thermal and kinetic feedback , 2016, 1607.03486.

[37]  W. M. Wood-Vasey,et al.  The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample , 2016, 1607.03155.

[38]  Ashley J. Ross,et al.  The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Constraining modified gravity , 2016, 1612.00812.

[39]  W. Percival,et al.  The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological implications of the configuration-space clustering wedges , 2016, 1607.03147.

[40]  P. Schneider,et al.  KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing , 2016, 1606.05338.

[41]  Francisco-Shu Kitaura,et al.  The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: RSD measurement from the power spectrum and bispectrum of the DR12 BOSS galaxies , 2016, 1606.00439.

[42]  F. Schmidt,et al.  Large-Scale Galaxy Bias , 2016, 1611.09787.

[43]  D. Bertolini,et al.  Principal shapes and squeezed limits in the effective field theory of large scale structure , 2016, 1608.01310.

[44]  C. Frenk,et al.  The effect of baryons on redshift space distortions and cosmic density and velocity fields in the EAGLE simulation , 2016, 1603.03328.

[45]  M. Takada,et al.  Separate universe consistency relation and calibration of halo bias , 2015, 1511.01454.

[46]  Volker Springel,et al.  Improving the convergence properties of the moving-mesh code AREPO , 2015, 1503.00562.

[47]  C. Wagner,et al.  Precision measurement of the local bias of dark matter halos , 2015, 1511.01096.

[48]  R. Teyssier,et al.  A new method to quantify the effects of baryons on the matter power spectrum , 2015, 1510.06034.

[49]  Hal Finkel,et al.  THE MIRA–TITAN UNIVERSE: PRECISION PREDICTIONS FOR DARK ENERGY SURVEYS , 2015, 1508.02654.

[50]  Shahab Joudaki,et al.  An accurate halo model for fitting non-linear cosmological power spectra and baryonic feedback models , 2015, 1505.07833.

[51]  Ariel G. S'anchez,et al.  Position-dependent correlation function from the SDSS-III Baryon Oscillation Spectroscopic Survey Data Release 10 CMASS sample , 2015, 1504.03322.

[52]  E. Pajer,et al.  On separate universes , 2015, 1504.00351.

[53]  E. Komatsu,et al.  The angle-averaged squeezed limit of nonlinear matter N-point functions , 2015, 1503.03487.

[54]  V. Springel N-GenIC: Cosmological structure initial conditions , 2015 .

[55]  Naoki Yoshida,et al.  IMPACT OF BARYONIC PROCESSES ON WEAK-LENSING COSMOLOGY: POWER SPECTRUM, NONLOCAL STATISTICS, AND PARAMETER BIAS , 2015, 1501.02055.

[56]  Martin Kilbinger,et al.  Cosmology with cosmic shear observations: a review , 2014, Reports on progress in physics. Physical Society.

[57]  E. Komatsu,et al.  Separate universe simulations , 2014, 1409.6294.

[58]  C. Heymans,et al.  Baryons, neutrinos, feedback and weak gravitational lensing , 2014, 1407.4301.

[59]  Scott Dodelson,et al.  Accounting for baryonic effects in cosmic shear tomography: determining a minimal set of nuisance parameters using PCA , 2014, 1405.7423.

[60]  Changbom Park,et al.  Primordial non-Gaussian signatures in CMB polarization , 2014, 1411.5256.

[61]  M. Takada,et al.  Super-Sample Signal , 2014, 1408.1081.

[62]  V. Springel,et al.  Introducing the Illustris Project: the evolution of galaxy populations across cosmic time , 2014, 1405.3749.

[63]  V. Springel,et al.  Introducing the Illustris Project: simulating the coevolution of dark and visible matter in the Universe , 2014, 1405.2921.

[64]  H. Hoekstra,et al.  CFHTLenS: cosmological constraints from a combination of cosmic shear two-point and three-point correlations , 2014, 1404.5469.

[65]  E. Komatsu,et al.  Position-dependent power spectrum of the large-scale structure: a novel method to measure the squeezed-limit bispectrum , 2014, 1403.3411.

[66]  M. Takada,et al.  Super-Sample Covariance in Simulations , 2014, 1401.0385.

[67]  J. Sainte-Marie,et al.  Phytoplankton growth formulation in marine ecosystem models: should we take into account photo-acclimation and variable stoichiometry in oligotrophic areas? , 2013 .

[68]  M. Takada,et al.  Cosmological parameters from weak lensing power spectrum and bispectrum tomography: including the non-Gaussian errors , 2013, 1306.4684.

[69]  Earl Lawrence,et al.  THE COYOTE UNIVERSE EXTENDED: PRECISION EMULATION OF THE MATTER POWER SPECTRUM , 2013, 1304.7849.

[70]  M. Takada,et al.  Power spectrum super-sample covariance , 2013, 1302.6994.

[71]  Masanori Sato,et al.  Impact of the non-Gaussian covariance of the weak lensing power spectrum and bispectrum on cosmological parameter estimation , 2013, 1301.3588.

[72]  Adam D. Myers,et al.  Measurement of baryon acoustic oscillations in the Lyman-α forest fluctuations in BOSS data release 9 , 2013, 1301.3459.

[73]  H. Hoekstra,et al.  CFHTLenS: higher order galaxy–mass correlations probed by galaxy–galaxy–galaxy lensing , 2013, 1301.1863.

[74]  Joop Schaye,et al.  Effect of baryonic feedback on two- and three-point shear statistics: prospects for detection and improved modelling , 2012, 1210.7303.

[75]  M. May,et al.  Baryon impact on weak lensing peaks and power spectrum: Low-bias statistics and self-calibration in future surveys , 2012, 1210.0608.

[76]  Abraham Loeb,et al.  21 cm cosmology in the 21st century , 2011, Reports on progress in physics. Physical Society.

[77]  H. Hoekstra,et al.  Quantifying the effect of baryon physics on weak lensing tomography , 2011, 1105.1075.

[78]  Joop Schaye,et al.  The effects of galaxy formation on the matter power spectrum: a challenge for precision cosmology , 2011, 1104.1174.

[79]  Anthony Challinor,et al.  CAMB: Code for Anisotropies in the Microwave Background , 2011 .

[80]  T. Schrabback,et al.  Weak lensing from space: first cosmological constraints from three-point shear statistics★ , 2010, 1005.4941.

[81]  J. Schaye,et al.  The physics driving the cosmic star formation history , 2009, 0909.5196.

[82]  V. Springel E pur si muove: Galilean-invariant cosmological hydrodynamical simulations on a moving mesh , 2009, 0901.4107.

[83]  H. Hoekstra,et al.  Weak Gravitational Lensing and Its Cosmological Applications , 2008, 0805.0139.

[84]  S. Furlanetto,et al.  Cosmology at low frequencies: The 21 cm transition and the high-redshift Universe , 2006, astro-ph/0608032.

[85]  M. Crocce,et al.  Cosmology and the Bispectrum , 2006, astro-ph/0604505.

[86]  V. Springel The Cosmological simulation code GADGET-2 , 2005, astro-ph/0505010.

[87]  Northwestern,et al.  Weak lensing bispectrum , 2005, astro-ph/0501063.

[88]  M. Lombardi,et al.  The three-point correlation function of cosmic shear II. Relation to the bispectrum of the projected mass density and generalized third-order aperture measures , 2003, astro-ph/0308328.

[89]  J. Brinkmann,et al.  The Lyα Forest Power Spectrum from the Sloan Digital Sky Survey , 2004, astro-ph/0405013.

[90]  G. Bernstein,et al.  The skewness of the aperture mass statistic , 2003, astro-ph/0307393.

[91]  Y. Mellier,et al.  Detection of Dark Matter Skewness in the VIRMOS-DESCART Survey: Implications for Ω0 , 2003, astro-ph/0302031.

[92]  S. Colombi,et al.  Large scale structure of the universe and cosmological perturbation theory , 2001, astro-ph/0112551.

[93]  A. Cooray,et al.  Weak Gravitational Lensing Bispectrum , 2000, astro-ph/0004151.

[94]  A. Lewis,et al.  Efficient computation of CMB anisotropies in closed FRW models , 1999, astro-ph/9911177.

[95]  M. Zaldarriaga,et al.  Power Spectrum Correlations Induced by Nonlinear Clustering , 1999, astro-ph/9901099.

[96]  H. Gove,et al.  Annual Review Of Nuclear And Particle Science , 1984 .