L. Blot, Pier Stefano Corasaniti, Y. Rasera, S. Agarwal
Future galaxy surveys will provide accurate measurements of the matter power spectrum across an unprecedented range of scales and redshifts. The analysis of these data will require to accurately model the imprint of non-linearities on the matter density field, which induces a non-Gaussian contribution to the data covariance. As the imprint of non-linearities is cosmology dependent, a further complication arises from accounting for the cosmological dependence of the non-Gaussian part of the covariance. Here, we study this using a dedicated suite of N-body simulations, the Dark Energy Universe Simulation - Parallel Universe Runs (DEUS-PUR) $Cosmo$. These consist of 512 realizations for 10 different cosmologies where we vary the matter density $Omega_m$, the amplitude of density fluctuations $sigma_8$, the reduced Hubble parameter $h$ and a constant dark energy equation of state $w$ by approximately $10%$. We use these data to evaluate the first and second derivatives of the power spectrum covariance with respect to a fiducial $Lambda$CDM cosmology. We find that the variations can be as large as $150%$ depending on the scale, redshift and model parameter considered. Using a Fisher matrix approach, we evaluate the impact of using a covariance estimated at a fiducial model rather than the true underlying cosmology. We find that the estimated $1sigma$ errors are affected at approximately $5%$, $20%$, $50%$ and $120%$ level when assuming non-fiducial values of $h$, $w$, $Omega_m$ and $sigma_8$ respectively. These results suggest that the use of cosmology-dependent covariances is key for precision cosmology.
{"title":"Cosmological model parameter dependence of the matter power spectrum covariance from the DEUS-PUR Cosmo simulations","authors":"L. Blot, Pier Stefano Corasaniti, Y. Rasera, S. Agarwal","doi":"10.1093/mnras/staa3444","DOIUrl":"https://doi.org/10.1093/mnras/staa3444","url":null,"abstract":"Future galaxy surveys will provide accurate measurements of the matter power spectrum across an unprecedented range of scales and redshifts. The analysis of these data will require to accurately model the imprint of non-linearities on the matter density field, which induces a non-Gaussian contribution to the data covariance. As the imprint of non-linearities is cosmology dependent, a further complication arises from accounting for the cosmological dependence of the non-Gaussian part of the covariance. Here, we study this using a dedicated suite of N-body simulations, the Dark Energy Universe Simulation - Parallel Universe Runs (DEUS-PUR) $Cosmo$. These consist of 512 realizations for 10 different cosmologies where we vary the matter density $Omega_m$, the amplitude of density fluctuations $sigma_8$, the reduced Hubble parameter $h$ and a constant dark energy equation of state $w$ by approximately $10%$. We use these data to evaluate the first and second derivatives of the power spectrum covariance with respect to a fiducial $Lambda$CDM cosmology. We find that the variations can be as large as $150%$ depending on the scale, redshift and model parameter considered. Using a Fisher matrix approach, we evaluate the impact of using a covariance estimated at a fiducial model rather than the true underlying cosmology. We find that the estimated $1sigma$ errors are affected at approximately $5%$, $20%$, $50%$ and $120%$ level when assuming non-fiducial values of $h$, $w$, $Omega_m$ and $sigma_8$ respectively. These results suggest that the use of cosmology-dependent covariances is key for precision cosmology.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73047442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Ishiyama, F. Prada, A. Klypin, Manodeep Sinha, R. Metcalf, E. Jullo, B. Altieri, S. Cora, D. Croton, S. de la Torre, David E. Mill'an-Calero, T. Oogi, J. Ruedas, C. Vega-Martínez
We introduce the Uchuu suite of large high-resolution cosmological $N$-body simulations. The largest simulation, named Uchuu, consists of 2.1 trillion ($12800^3$) dark matter particles in a box of 2.0 Gpc/h, and the mass of each particle is $3.27 times 10^{8}$ Msun/h. The highest resolution simulation, called Shin-Uchuu, consists of 262 billion ($6400^3$) particles in a box of 140 Mpc/h, with a particle mass of $8.97 times 10^{5}$ Msun/h. Combining these simulations we can follow the evolution of dark matter haloes (and subhaloes) spanning from dwarf galaxies to massive galaxy cluster hosts. We present basic statistics, dark matter power spectra and halo (subhalo) mass function, to demonstrate the huge dynamic range and superb statistics of the Uchuu simulations. From the analysis of the evolution of the power spectra we conclude that our simulations are accurate enough from the Baryon Acoustic Oscillations up to very small scales. We also provide parameters of a mass-concentration model, which describes the evolution of halo concentrations, that reproduces our simulation data within 5% error. We make publicly available various $N$-body products, as part of Uchuu Data Release 1, on the Skies & Universes site. We also plan to release gravitational lensing maps, mock galaxy, X-ray cluster and active galactic nuclei catalogues in the near future.
{"title":"The Uchuu simulations: Data Release 1 and dark matter halo concentrations","authors":"T. Ishiyama, F. Prada, A. Klypin, Manodeep Sinha, R. Metcalf, E. Jullo, B. Altieri, S. Cora, D. Croton, S. de la Torre, David E. Mill'an-Calero, T. Oogi, J. Ruedas, C. Vega-Martínez","doi":"10.1093/mnras/stab1755","DOIUrl":"https://doi.org/10.1093/mnras/stab1755","url":null,"abstract":"We introduce the Uchuu suite of large high-resolution cosmological $N$-body simulations. The largest simulation, named Uchuu, consists of 2.1 trillion ($12800^3$) dark matter particles in a box of 2.0 Gpc/h, and the mass of each particle is $3.27 times 10^{8}$ Msun/h. The highest resolution simulation, called Shin-Uchuu, consists of 262 billion ($6400^3$) particles in a box of 140 Mpc/h, with a particle mass of $8.97 times 10^{5}$ Msun/h. Combining these simulations we can follow the evolution of dark matter haloes (and subhaloes) spanning from dwarf galaxies to massive galaxy cluster hosts. We present basic statistics, dark matter power spectra and halo (subhalo) mass function, to demonstrate the huge dynamic range and superb statistics of the Uchuu simulations. From the analysis of the evolution of the power spectra we conclude that our simulations are accurate enough from the Baryon Acoustic Oscillations up to very small scales. We also provide parameters of a mass-concentration model, which describes the evolution of halo concentrations, that reproduces our simulation data within 5% error. We make publicly available various $N$-body products, as part of Uchuu Data Release 1, on the Skies & Universes site. We also plan to release gravitational lensing maps, mock galaxy, X-ray cluster and active galactic nuclei catalogues in the near future.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80138013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-28DOI: 10.1051/0004-6361/202039049
L. Legrand, C. Hern'andez-Monteagudo, M. Douspis, N. Aghanim, R. Angulo
In the context of next generation spectroscopic galaxy surveys, new observables of the distribution of matter are currently being developed. Among these we investigate the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We test both the standard $Lambda$CDM model and the wCDM extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties, by a factor of at least two on most parameters for the $Lambda$CDM and wCDM model. We find that the ARF combined with angular galaxy clustering are a great probe of dark energy by increasing the figure of merit of the $w_0$-$w_{rm a}$ parameter set by a factor of more than 10 compared to angular galaxy clustering alone. Finally we compare ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by $sim 40%$ on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing.
{"title":"High-resolution tomography for galaxy spectroscopic surveys with angular redshift fluctuations","authors":"L. Legrand, C. Hern'andez-Monteagudo, M. Douspis, N. Aghanim, R. Angulo","doi":"10.1051/0004-6361/202039049","DOIUrl":"https://doi.org/10.1051/0004-6361/202039049","url":null,"abstract":"In the context of next generation spectroscopic galaxy surveys, new observables of the distribution of matter are currently being developed. Among these we investigate the angular redshift fluctuations (ARF), which probe the information contained in the projected redshift distribution of galaxies. Relying on the Fisher formalism, we show how ARF will provide complementary cosmological information compared to traditional angular galaxy clustering. We test both the standard $Lambda$CDM model and the wCDM extension. We find that the cosmological and galaxy bias parameters express different degeneracies when inferred from ARF or from angular galaxy clustering. As such, combining both observables breaks these degeneracies and greatly decreases the marginalised uncertainties, by a factor of at least two on most parameters for the $Lambda$CDM and wCDM model. We find that the ARF combined with angular galaxy clustering are a great probe of dark energy by increasing the figure of merit of the $w_0$-$w_{rm a}$ parameter set by a factor of more than 10 compared to angular galaxy clustering alone. Finally we compare ARF to the CMB lensing constraints on the galaxy bias parameters. We show that a joint analysis of ARF and angular galaxy clustering improves constraints by $sim 40%$ on galaxy bias compared to a joint analysis of angular galaxy clustering and CMB lensing.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81058573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Future large scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogs will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-$C_ell$ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.
{"title":"Mitigating contamination in LSS surveys: a comparison of methods","authors":"N. Weaverdyck, D. Huterer","doi":"10.1093/MNRAS/STAB709","DOIUrl":"https://doi.org/10.1093/MNRAS/STAB709","url":null,"abstract":"Future large scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogs will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-$C_ell$ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80971514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-27DOI: 10.1103/PHYSREVD.103.043526
K. K. Rogers, H. Peiris
We present a general framework for obtaining robust bounds on the nature of dark matter using cosmological $N$-body simulations and Lyman-alpha forest data. We construct an emulator of hydrodynamical simulations, which is a flexible, accurate and computationally-cheap model for predicting the response of the Lyman-alpha forest flux power spectrum to different dark matter models, the state of the intergalactic medium (IGM) and the primordial power spectrum. The emulator combines a flexible parameterization for the small-scale suppression in the matter power spectrum arising in "non-cold" dark matter models, with an improved IGM model. We then demonstrate how to optimize the emulator for the case of ultra-light axion dark matter, presenting tests of convergence. We also carry out cross-validation tests of the accuracy of flux power spectrum prediction. This framework can be optimized for the analysis of many other dark matter candidates, e.g., warm or interacting dark matter. Our work demonstrates that a combination of an optimized emulator and cosmological "effective theories," where many models are described by a single set of equations, is a powerful approach for robust and computationally-efficient inference from the cosmic large-scale structure.
{"title":"General framework for cosmological dark matter bounds using \u0000N\u0000-body simulations","authors":"K. K. Rogers, H. Peiris","doi":"10.1103/PHYSREVD.103.043526","DOIUrl":"https://doi.org/10.1103/PHYSREVD.103.043526","url":null,"abstract":"We present a general framework for obtaining robust bounds on the nature of dark matter using cosmological $N$-body simulations and Lyman-alpha forest data. We construct an emulator of hydrodynamical simulations, which is a flexible, accurate and computationally-cheap model for predicting the response of the Lyman-alpha forest flux power spectrum to different dark matter models, the state of the intergalactic medium (IGM) and the primordial power spectrum. The emulator combines a flexible parameterization for the small-scale suppression in the matter power spectrum arising in \"non-cold\" dark matter models, with an improved IGM model. We then demonstrate how to optimize the emulator for the case of ultra-light axion dark matter, presenting tests of convergence. We also carry out cross-validation tests of the accuracy of flux power spectrum prediction. This framework can be optimized for the analysis of many other dark matter candidates, e.g., warm or interacting dark matter. Our work demonstrates that a combination of an optimized emulator and cosmological \"effective theories,\" where many models are described by a single set of equations, is a powerful approach for robust and computationally-efficient inference from the cosmic large-scale structure.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82879573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The use of summary statistics beyond the two-point correlation function to analyze the non-Gaussian clustering on small scales is an active field of research in cosmology. In this paper, we explore a set of new summary statistics -- the $k$-Nearest Neighbor Cumulative Distribution Functions ($k{rm NN}$-${rm CDF}$). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the $k$--nearest data points, and is sensitive to all connected $N$--point correlations in the data. The $k{rm NN}$-${rm CDF}$ can be used to measure counts in cell, void probability distributions and higher $N$--point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets - both discrete points, and the generalization for continuous fields. We use data from a large suite of $N$-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of $k{rm NN}$-${rm CDF}$ improves the constraints on the cosmological parameters by more than a factor of $2$ when applied to the clustering of dark matter in the range of scales between $10h^{-1}{rm Mpc}$ and $40h^{-1}{rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of halos in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the $k{rm NN}$-${rm CDF}$ are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data.
{"title":"Nearest neighbour distributions: New statistical measures for cosmological clustering","authors":"Arka Banerjee, T. Abel","doi":"10.1093/mnras/staa3604","DOIUrl":"https://doi.org/10.1093/mnras/staa3604","url":null,"abstract":"The use of summary statistics beyond the two-point correlation function to analyze the non-Gaussian clustering on small scales is an active field of research in cosmology. In this paper, we explore a set of new summary statistics -- the $k$-Nearest Neighbor Cumulative Distribution Functions ($k{rm NN}$-${rm CDF}$). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the $k$--nearest data points, and is sensitive to all connected $N$--point correlations in the data. The $k{rm NN}$-${rm CDF}$ can be used to measure counts in cell, void probability distributions and higher $N$--point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets - both discrete points, and the generalization for continuous fields. We use data from a large suite of $N$-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of $k{rm NN}$-${rm CDF}$ improves the constraints on the cosmological parameters by more than a factor of $2$ when applied to the clustering of dark matter in the range of scales between $10h^{-1}{rm Mpc}$ and $40h^{-1}{rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of halos in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the $k{rm NN}$-${rm CDF}$ are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79446709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuchen Zhang, A. Pullen, S. Alam, Sukhdeep Singh, É. Burtin, C. Chuang, Jiamin Hou, B. Lyke, A. Myers, R. Neveux, A. Ross, G. Rossi, Cheng Zhao
We test general relativity (GR) at the effective redshift $bar{z} sim 1.5$ by estimating the statistic $E_G$, a probe of gravity, on cosmological scales $19 - 190,h^{-1}{rm Mpc}$. This is the highest-redshift and largest-scale estimation of $E_G$ so far. We use the quasar sample with redshifts $0.8 < z < 2.2$ from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_ell^{qq}$ and the redshift-space distortion (RSD) parameter $beta$ are estimated. By cross correlating with the $textit{Planck}$ 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_ell^{kappa q}$ signal at $12,sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of $E_G$ at $5$ bins covering different scales, with the later preferred for its better constraints on the covariances. We find $E_G$ estimates agree with the GR prediction at $1,sigma$ level over all these scales. With the CM estimated with $300$ simulations, we report a best-fit scale-averaged estimate of $E_G(bar{z})=0.30pm 0.05$, which is in line with the GR prediction $E_G^{rm GR}(bar{z})=0.33$ with $textit{Planck}$ 2018 CMB+BAO matter density fraction $Omega_{rm m}=0.31$. The statistical errors of $E_G$ with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.
{"title":"Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing","authors":"Yuchen Zhang, A. Pullen, S. Alam, Sukhdeep Singh, É. Burtin, C. Chuang, Jiamin Hou, B. Lyke, A. Myers, R. Neveux, A. Ross, G. Rossi, Cheng Zhao","doi":"10.1093/mnras/staa3672","DOIUrl":"https://doi.org/10.1093/mnras/staa3672","url":null,"abstract":"We test general relativity (GR) at the effective redshift $bar{z} sim 1.5$ by estimating the statistic $E_G$, a probe of gravity, on cosmological scales $19 - 190,h^{-1}{rm Mpc}$. This is the highest-redshift and largest-scale estimation of $E_G$ so far. We use the quasar sample with redshifts $0.8 < z < 2.2$ from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_ell^{qq}$ and the redshift-space distortion (RSD) parameter $beta$ are estimated. By cross correlating with the $textit{Planck}$ 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_ell^{kappa q}$ signal at $12,sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of $E_G$ at $5$ bins covering different scales, with the later preferred for its better constraints on the covariances. We find $E_G$ estimates agree with the GR prediction at $1,sigma$ level over all these scales. With the CM estimated with $300$ simulations, we report a best-fit scale-averaged estimate of $E_G(bar{z})=0.30pm 0.05$, which is in line with the GR prediction $E_G^{rm GR}(bar{z})=0.33$ with $textit{Planck}$ 2018 CMB+BAO matter density fraction $Omega_{rm m}=0.31$. The statistical errors of $E_G$ with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79879063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-21DOI: 10.21105/ASTRO.2007.11100
A. Kim
Type Ia supernovae (SNe Ia) are used as distance indicators to infer the cosmological parameters that specify the expansion history of the universe. Parameter inference depends on the criteria by which the analysis SN sample is selected. Only for the simplest selection criteria and population models can the likelihood be calculated analytically, otherwise it needs to be determined numerically, a process that inherently has error. Numerical errors in the likelihood lead to errors in parameter inference. This article presents toy examples where the distance modulus is inferred given a set of SNe at a single redshift. Parameter estimators and their uncertainties are calculated using Monte Carlo techniques. The relationship between the number of Monte Carlo realizations and numerical errors is presented. The procedure can be applied to more realistic models and used to determine the computational and data management requirements of the transient analysis pipeline.
{"title":"Characterizing the Sample Selection for Supernova Cosmology","authors":"A. Kim","doi":"10.21105/ASTRO.2007.11100","DOIUrl":"https://doi.org/10.21105/ASTRO.2007.11100","url":null,"abstract":"Type Ia supernovae (SNe Ia) are used as distance indicators to infer the cosmological parameters that specify the expansion history of the universe. Parameter inference depends on the criteria by which the analysis SN sample is selected. Only for the simplest selection criteria and population models can the likelihood be calculated analytically, otherwise it needs to be determined numerically, a process that inherently has error. Numerical errors in the likelihood lead to errors in parameter inference. This article presents toy examples where the distance modulus is inferred given a set of SNe at a single redshift. Parameter estimators and their uncertainties are calculated using Monte Carlo techniques. The relationship between the number of Monte Carlo realizations and numerical errors is presented. The procedure can be applied to more realistic models and used to determine the computational and data management requirements of the transient analysis pipeline.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"412 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84884866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced LIGO and Advanced Virgo have recently published the upper limit measurement of persistent directional stochastic gravitational wave background (SGWB) based on data from their first and second observing runs (O1 and O2). In this paper we investigate whether a correlation exists between this maximal likelihood SGWB map and the electromagnetic tracers of matter structure in the universe, such as galaxy number counts. The method we develop will improve the sensitivity of future searches for anisotropy in the SGWB and expand the use of SGWB anisotropy to probe the formation of structure in the universe. In order to compute the cross-correlation, we used the spherical harmonic decomposition of SGWB in multiple frequency bands and converted them into pixel-based sky maps in HEALPix basis. For the electromagnetic (EM) part, we use the Sloan Digital Sky Survey (SDSS) galaxy catalog and form HEALPix sky maps of galaxy number counts at the same angular resolution as the SGWB maps. We compute the pixel-based coherence between these SGWB and galaxy count maps. After evaluating our results in different SGWB frequency bands and in different galaxy redshift bins, we conclude that the coherence between the SGWB and galaxy number count maps is dominated by the null measurement noise in the SGWB maps, and therefore not statistically significant. We expect the results of this analysis to be significantly improved by using the more sensitive upcoming SGWB measurements based on the third observing run (O3) of Advanced LIGO and Advanced Virgo.
{"title":"Searching for cross-correlation between stochastic gravitational-wave background and galaxy number counts","authors":"Kate Z. Yang, V. Mandic, C. Scarlata, S. Banagiri","doi":"10.1093/mnras/staa3159","DOIUrl":"https://doi.org/10.1093/mnras/staa3159","url":null,"abstract":"Advanced LIGO and Advanced Virgo have recently published the upper limit measurement of persistent directional stochastic gravitational wave background (SGWB) based on data from their first and second observing runs (O1 and O2). In this paper we investigate whether a correlation exists between this maximal likelihood SGWB map and the electromagnetic tracers of matter structure in the universe, such as galaxy number counts. The method we develop will improve the sensitivity of future searches for anisotropy in the SGWB and expand the use of SGWB anisotropy to probe the formation of structure in the universe. In order to compute the cross-correlation, we used the spherical harmonic decomposition of SGWB in multiple frequency bands and converted them into pixel-based sky maps in HEALPix basis. For the electromagnetic (EM) part, we use the Sloan Digital Sky Survey (SDSS) galaxy catalog and form HEALPix sky maps of galaxy number counts at the same angular resolution as the SGWB maps. We compute the pixel-based coherence between these SGWB and galaxy count maps. After evaluating our results in different SGWB frequency bands and in different galaxy redshift bins, we conclude that the coherence between the SGWB and galaxy number count maps is dominated by the null measurement noise in the SGWB maps, and therefore not statistically significant. We expect the results of this analysis to be significantly improved by using the more sensitive upcoming SGWB measurements based on the third observing run (O3) of Advanced LIGO and Advanced Virgo.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76436852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To generate initial conditions for cosmological $N$-body simulations, one needs to prepare a uniform distribution of simulation particles, so-called the pre-initial condition (pre-IC). The standard method to construct the pre-IC is to place the particles on the lattice grids evenly spaced in the three-dimensional spatial coordinates. However, even after the initial displacement of each particle according to cosmological perturbations, the particle distribution remains to display an artificial anisotropy. Such an artifact causes systematic effects in simulations at later time until the evolved particle distribution sufficiently erases the initial anisotropy. In this paper, we study the impacts of the pre-IC on the anisotropic separate universe simulation, where the effect of large-scale tidal field on structure formation is taken into account using the anisotropic expansion in a local background (simulation volume). To quantify the impacts, we compare the simulations employing the standard grid pre-IC and the glass one, where the latter is supposed to suppress the initial anisotropy. We show that the artificial features in the grid pre-IC simulations are seen until $zsim 9$, while the glass pre-IC simulations appear to be stable and accurate over the range of scales we study. From these results we find that a coupling of the large-scale tidal field with matter clustering is enhanced compared to the leading-order prediction of perturbation theory in the quasi non-linear regime in the redshift range $5lesssim zlesssim 15$, indicating the importance of tidal field on structure formation at such high redshifts, e.g. during the epoch of reionization.
{"title":"Impacts of pre-initial conditions on anisotropic separate universe simulations: a boosted tidal response in the epoch of reionization","authors":"S. Masaki, T. Nishimichi, M. Takada","doi":"10.1093/mnras/staa3309","DOIUrl":"https://doi.org/10.1093/mnras/staa3309","url":null,"abstract":"To generate initial conditions for cosmological $N$-body simulations, one needs to prepare a uniform distribution of simulation particles, so-called the pre-initial condition (pre-IC). The standard method to construct the pre-IC is to place the particles on the lattice grids evenly spaced in the three-dimensional spatial coordinates. However, even after the initial displacement of each particle according to cosmological perturbations, the particle distribution remains to display an artificial anisotropy. Such an artifact causes systematic effects in simulations at later time until the evolved particle distribution sufficiently erases the initial anisotropy. In this paper, we study the impacts of the pre-IC on the anisotropic separate universe simulation, where the effect of large-scale tidal field on structure formation is taken into account using the anisotropic expansion in a local background (simulation volume). To quantify the impacts, we compare the simulations employing the standard grid pre-IC and the glass one, where the latter is supposed to suppress the initial anisotropy. We show that the artificial features in the grid pre-IC simulations are seen until $zsim 9$, while the glass pre-IC simulations appear to be stable and accurate over the range of scales we study. From these results we find that a coupling of the large-scale tidal field with matter clustering is enhanced compared to the leading-order prediction of perturbation theory in the quasi non-linear regime in the redshift range $5lesssim zlesssim 15$, indicating the importance of tidal field on structure formation at such high redshifts, e.g. during the epoch of reionization.","PeriodicalId":8431,"journal":{"name":"arXiv: Cosmology and Nongalactic Astrophysics","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86587449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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