We present the BACCO project, a simulation framework specially designed to provide highly-accurate predictions for the distribution of mass, galaxies, and gas as a function of cosmological parameters. In this paper, we describe our main suite of simulations (L $\sim2$ Gpc and $4320^3$ particles) and present various validation tests. Using a cosmology-rescaling technique, we predict the nonlinear mass power spectrum over the redshift range $0<z<1.5$ and over scales $10^{-2} < k/(h Mpc^{-1} ) < 5$ for 800 points in an 8-dimensional cosmological parameter space. For an efficient interpolation of the results, we build an emulator and compare its predictions against several widely-used methods. Over the whole range of scales considered, we expect our predictions to be accurate at the 2\% level for parameters in the minimal $Λ$ CDM model and to 3\% when extended to dynamical dark energy and massive neutrinos. We make our emulator publicly available under http://www.dipc.org/bacco
We present a neural-network emulator for baryonic effects in the non-linear matter power spectrum. We calibrate this emulator using more than 50,000 measurements in a 15-dimensional parameters space, varying cosmology and baryonic physics. Baryonic physics is described through a baryonification algorithm, that has been shown to accurately capture the relevant effects on the power spectrum and bispectrum in state-of-the-art hydrodynamical simulations. Cosmological parameters are sampled using a cosmology-rescaling approach including massive neutrinos and dynamical dark energy. The specific quan…
We compare and validate COLA (COmoving Lagrangian Acceleration) simulations against existing emulators in the literature, namely Bacco and Euclid Emulator 2. Our analysis focuses on the non-linear response function, i.e., the ratio between the non-linear dark matter power spectrum in a given cosmology with respect to a pre-defined reference cosmology, which is chosen to be the Euclid Emulator 2 reference cosmology in this paper. We vary three cosmological parameters, the total matter density, the amplitude of the primordial scalar perturbations and the spectral index. By comparing the COLA non…
We analyse the BOSS DR12 galaxy power spectrum data jointly with BAO data for three models of dark energy. We use recent measurements using a windowless estimator, and an independent and fast pipeline based on EFTofLSS implemented via the FAST-PT algorithm to compute the redshift-space loop corrections. We accelerate our analysis by using the BACCO linear emulator instead of a Boltzmann solver. We perform two sets of analyses: one with $3σ$ Planck priors on $A_s$ and $n_s$, and another that is CMB-free, without such priors. Firstly, we study $Λ$CDM, reproducing previous results obtained with t…
A joint fit of the mass and redshift distributions of the population of Binary Black Holes detected with Gravitational-Wave observations can be used to obtain constraints on the Hubble parameter and on deviations from General Relativity in the propagation of Gravitational Waves. We first present applications of this technique to the latest catalog of Gravitational-Wave events, focusing on the comparison of different parametrizations for the source-frame mass distribution of Black Hole Binaries. We find that models with more than one feature are favourite by the data, as suggested by population…
Gravitational waves can provide an accurate measurement of the luminosity distance to the source, but cannot provide the source redshift unless the degeneracy between mass and redshift can be broken. This makes it essential to infer the redshift of the source independently to measure the expansion history of the Universe. We show that by exploiting the clustering scale of the gravitational wave sources with galaxies of known redshift, we can infer the expansion history from redshift unknown gravitational wave sources. By using gravitational wave sources of unknown redshift that are detectable …
Towards end-to-end Bayesian forward models in global 21-cm cosmology: surrogate modelling and marginalisation of beam uncertainty
Astrophysics Group, Cavendish Laboratory(卡文迪许实验室天体物理组);Kavli Institute for Cosmology(卡弗里宇宙学研究所);Antenna Group, Université Catholique de Louvain(天主教鲁汶大学天线研究组)
Cosmology with the lights off: Standard sirens in the Einstein Telescope era
我们探索约束宇宙学的前景,利用引力波(GW)观测的中子星双星的建议爱因斯坦望远镜(ET),利用狭窄的中子星质量函数。双中子星(DNS)双星预计将成为先进LIGO“第一束光”后探测到的第一批源之一,预计在先进时代每年将以几十个的速度被探测到。然而,拟议中的ET每年可以编目数万人。将测得的源红移分布与GW网络距离测定相结合,不仅可以精确测量背景宇宙学参数,而且可以深入了解这些DNS系统的天体物理性质。特别感兴趣的将是探测DNS-二进制创建和随后的合并之间的延迟时间的分布,以及ET的探测范围内的恒星形成率密度的演变。在保持H_0、Ω_{m,0}和Ω_{Λ,0}不变的情况下,我们研究了暗能量状态方程参数恢复的精度,发现只要检测到10^5个DNS双星,我们就可以将这些参数限制到与未来CMB+BAO+SNIa测量的预测限制相似的精度。此外,建模合并延迟时间分布的幂律,和恒星形成率(SFR)密度的参数化版本的Porciani和Madau SF 2模型,我们发现,相关的天体物理参数被限制在10%以内。所有参数精密度均按1/sqrt(N)缩放,其中N是编目检测的数量。我们还研究了精度如何随着宇宙的内在基本属性和网络的距离(可能受到探测器低频截止的影响)而变化。
Pushing spectral siren cosmology into the third-generation era: a blinded mock data challenge
Università di Bologna(博洛尼亚大学);INFN - Sezione di Bologna(意大利国家核物理研究所博洛尼分部);INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna(意大利国家天体物理研究所博洛尼亚天文与空间科学观测站);Aix-Marseille Université(艾克斯-马赛大学);Université de Toulon(土伦大学);CNRS, CPT(法国国家科学研究中心, cpt 中心);INFN, Sezione di Roma(意大利国家核物理研究所罗马分部);“Sapienza” Universitá di Roma(罗马大学);CNRS/IN2P3, CPPM(法国国家科学研究中心/法国粒子与核物理研究所,马赛质子与核物理中心)
Simulation-Based Inference for Cluster Cosmology with Set-Based Neural Network Architectures
Max-Planck-Institut für extraterrestrische Physik(马克斯·普朗克地外物理研究所);Fakultät für Physik, LMU München(慕尼黑大学物理学院);Universitäts-Sternwarte München, Fakultät für Physik, LMU München(慕尼黑大学天文台,慕尼黑大学物理学院);Center for Computational Astrophysics, Flatiron Institute(平顿研究所计算天体物理学中心);Excellence Cluster ORIGINS(ORIGINS卓越集群);University of Cambridge, DAMTP and Cavendish Laboratory(剑桥大学应用数学与理论物理系和卡文迪许实验室);Universität Innsbruck, Institut für Astro- und Teilchenphysik(因斯布鲁克大学天体与粒子物理研究所);Univ Toulouse, CNES, CNRS, IRAP(图卢兹大学,法国国家空间研究中心,法国国家科学研究中心,图卢兹天体物理研究所);INAF, Osservatorio di Astrofisica e Scienza dello Spazio(意大利国家天体物理研究所,空间天文与科学观测站)
The 21-cm power spectrum of reionization is a promising probe for cosmology and fundamental physics. Exploiting this new observable, however, requires fast predictors capable of efficiently scanning the very large parameter space of cosmological and astrophysical uncertainties. In this paper, we introduce the halo model of reionization (HMreio), a new analytical tool that combines the halo model of the cosmic dawn with the excursion-set bubble model for reionization, assuming an empirical correction factor to deal with overlapping ionization bubbles. First, HMreio is validated against results …