LimberJack.jl: auto-differentiable methods for angular power spectra analyses

Abstract

We present LimberJack.jl, a fully auto-differentiable code for cosmological analyses of 2 point auto- and cross-correlation measurements from galaxy clustering, CMB lensing and weak lensing data written in Julia. Using Julia's auto-differentiation ecosystem, LimberJack.jl can obtain gradients for its outputs up to an order of magnitude faster than traditional finite difference methods. This makes LimberJack.jl greatly synergistic with gradient-based sampling methods, such as Hamiltonian Monte Carlo, capable of efficiently exploring parameter spaces with hundreds of dimensions. We first prove LimberJack.jl's reliability by reanalysing the DES Y1 3$\times$2-point data. We then showcase its capabilities by using a O(100) parameters Gaussian Process to reconstruct the cosmic growth from a combination of DES Y1 galaxy clustering and weak lensing data, eBOSS QSO's, CMB lensing and redshift-space distortions. Our Gaussian process reconstruction of the growth factor is statistically consistent with the $\Lambda$CDM Planck 2018 prediction at all redshifts. Moreover, we show that the addition of RSD data is extremely beneficial to this type of analysis, reducing the uncertainty in the reconstructed growth factor by $20\%$ on average across redshift. LimberJack.jl is a fully open-source project available on Julia's general repository of packages and GitHub.

arXiv commentAccepted to OJA, corrected bug displaying wrong Fig. 9

References in corpus (35)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Astropy: A Community Python Package for Astronomy
• The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample
• Baryonic Features in the Matter Transfer Function
• Stable clustering, the halo model and nonlinear cosmological power spectra
• The Simons Observatory: Science goals and forecasts
• The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory
• The DESI Experiment Part I: Science,Targeting, and Survey Design
• Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
• Revising the Halofit Model for the Nonlinear Matter Power Spectrum
• Wide-Field InfrarRed Survey Telescope-Astrophysics Focused Telescope Assets WFIRST-AFTA 2015 Report
• The WiggleZ Dark Energy Survey: Joint measurements of the expansion and growth history at z < 1
• Power Spectra for Cold Dark Matter and its Variants
• Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear
• Intrinsic alignment-lensing interference as a contaminant of cosmic shear
• The 6dF Galaxy Survey: z \approx 0 measurement of the growth rate and sigma_8
• Extended Limber Approximation
• HMcode-2020: Improved modelling of non-linear cosmological power spectra with baryonic feedback
• Core Cosmology Library: Precision Cosmological Predictions for LSST
• The VIMOS Public Extragalactic Redshift Survey (VIPERS): The growth of structures at $0.5<z<1.2$ from redshift-space distortions in the clustering of the PDR-2 final sample
• The BACCO Simulation Project: Exploiting the full power of large-scale structure for cosmology
• COSMOPOWER: emulating cosmological power spectra for accelerated Bayesian inference from next-generation surveys
• JAX-COSMO: An End-to-End Differentiable and GPU Accelerated Cosmology Library
• Model-independent constraints on ${\Omega }_m$ and $H(z)$ from the link between geometry and growth
• Kernel-Based Emulator for the 3D Matter Power Spectrum from CLASS
• Beware of Fake $\nu$s: The Effect of Massive Neutrinos on the Nonlinear Evolution of Cosmic Structure
• Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data
• $\text{matryoshka}$: Halo Model Emulator for the Galaxy Power Spectrum
• The N5K Challenge: Non-Limber Integration for LSST Cosmology
• Pathfinder: Parallel quasi-Newton variational inference
• The impact of the Universe's expansion rate on constraints on modified growth of structure
• Microcanonical Hamiltonian Monte Carlo
• The halo bias for number counts on the light cone from relativistic N-body simulations
• Efficient Automatic Differentiation of Implicit Functions
• Multiscale Flow for Robust and Optimal Cosmological Analysis

Cited by in corpus (5)

• The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics
• candl: Cosmic Microwave Background Analysis with a Differentiable Likelihood
• Reducing nuisance prior sensitivity via non-linear reparameterization, with application to EFT analyses of large-scale structure
• ${\text{SwiftC}}_{\ell }$: fast differentiable angular power spectra beyond Limber
• Constraining the primordial power spectrum using a differentiable likelihood