CosmoSIS: modular cosmological parameter estimation

Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly dened. We present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including camb, Planck, cosmic shear cal

[1]  Richard Kessler,et al.  Improved cosmological constraints from a joint analysis of the SNLS and SDSS surveys , 2014 .

[2]  Scott Croom,et al.  The WiggleZ Dark Energy Survey: Final data release and cosmological results , 2012, 1210.2130.

[3]  C. A. Oxborrow,et al.  Planck 2013 results. XVI. Cosmological parameters , 2013, 1303.5076.

[4]  Daniel Foreman-Mackey,et al.  emcee: The MCMC Hammer , 2012, 1202.3665.

[5]  Alexander S. Szalay,et al.  Cosmological constraints from the clustering of the Sloan Digital Sky Survey DR7 luminous red galaxies (vol 404, pg 60, 2010) , 2009, 0907.1659.

[6]  Jonathan R Goodman,et al.  Ensemble samplers with affine invariance , 2010 .

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

[8]  Adam Amara,et al.  iCosmo: an interactive cosmology package , 2008, 0810.1285.

[9]  Adam Amara,et al.  CosmoHammer: Cosmological parameter estimation with the MCMC Hammer , 2012, Astron. Comput..

[10]  Lloyd Knox,et al.  Rapid Calculation of Theoretical Cosmic Microwave Background Angular Power Spectra , 2002 .

[11]  Mark Trodden,et al.  Beyond the Cosmological Standard Model , 2014, 1407.0059.

[12]  CMBFIT: Rapid WMAP likelihood calculations with normal parameters , 2004, astro-ph/0311544.

[13]  Tarun Souradeep,et al.  SCoPE: an efficient method of Cosmological Parameter Estimation , 2014, 1403.1271.

[14]  W. A. Fendt,et al.  Pico: Parameters for the Impatient Cosmologist , 2006, astro-ph/0606709.

[15]  Tim Eifler,et al.  Combining probes of large-scale structure with COSMOLIKE , 2013, 1302.2401.

[16]  Yannick Mellier,et al.  CFHTLenS tomographic weak lensing cosmological parameter constraints: Mitigating the impact of intrinsic galaxy alignments , 2013, 1303.1808.

[17]  J. Dunkley,et al.  Comparison of sampling techniques for Bayesian parameter estimation , 2013, 1308.2675.

[18]  G. W. Pratt,et al.  Planck 2013 results. XV. CMB power spectra and likelihood , 2013, 1303.5075.

[19]  Michael Doran,et al.  Analyse this! A cosmological constraint package for CMBEASY , 2004 .

[20]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[21]  F. Feroz,et al.  MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics , 2008, 0809.3437.

[22]  Gersende Fort,et al.  CosmoPMC: Cosmology Population Monte Carlo , 2011, 1101.0950.

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

[24]  Wendy L. Freedman,et al.  Report of the Dark Energy Task Force , 2006, astro-ph/0609591.

[25]  N. Christensen,et al.  Bayesian methods for cosmological parameter estimation from cosmic microwave background measurements , 2000, astro-ph/0103134.

[26]  Jon Brinkmann,et al.  The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: single-probe measurements and the strong power of f(z)σ8(z) on constraining dark energy , 2013, 1303.4486.

[27]  R. W. Ogburn,et al.  Detection of B-mode polarization at degree angular scales by BICEP2. , 2014, Physical review letters.

[28]  Andrew R. Liddle,et al.  CosmoNest: Cosmological Nested Sampling , 2011 .

[29]  J. Lesgourgues,et al.  The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview , 2011, 1104.2932.

[30]  Farhan Feroz,et al.  BAMBI: blind accelerated multimodal Bayesian inference , 2011, 1110.2997.

[31]  Yabebal Fantaye,et al.  FISHER MATRIX PRELOADED — FISHER4CAST , 2009, 0906.0993.

[32]  A. Lewis,et al.  Cosmological parameters from CMB and other data: A Monte Carlo approach , 2002, astro-ph/0205436.

[33]  Michael Doran CMBEASY: an object oriented code for the cosmic microwave background , 2005 .

[34]  Arthur Kosowsky,et al.  Fast cosmological parameter estimation from microwave background temperature and polarization power spectra , 2004 .