Big3
September 19-21, 2012
Laboratoire Astroparticule et Cosmologie, 10 rue A. Domon et L. Duquet, 75205 Paris 13, France
published December 24, 2013
Conference website: http://www.apc.univ-paris7.fr/APC/Conferences/Workshop_Big3/Home.html Observations of the Cosmic Microwave Background (CMB) radiation have transformed modern cosmology propelling it into high-precision, data-driven science it is today. CMB data analysis has been a cornerstone of this transformation and it continues in this role preparing currently to meet its possibly ultimate challenge as posed by ever-growing in size and complexity forthcoming data sets required by new science goals posed for the field. These include providing key pieces of information about the very early Universe: Gaussianity of the initial conditions, the presence of the primordial gravity waves, as well as constraints on the large-scale structure formation and possibly properties of dark energy. The sophistication of the involved data models is matched by precision levels, which have to be attained to deliver robust detections and result in firm conclusions. The overall challenge is indeed breathtaking and, without a doubt, the success will be only possible if the data analysis effort becomes truly interdisciplinary and capitalizes on the latest advances in statistics, applied mathematics, and computer science - all of which constitute veritable foundations of the contemporary data analysis work.
conference main image
Sessions
Keynotes
Invited
Contributed
Keynotes
statistical methods
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D. Hand
future of the supercomputing
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H.D. Simon
Cosmic Microwave Background
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G. Smoot
Invited
From mean Euler characteristics to the Gaussian kinematic formula
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R. Adler
Shrinking the quadratic estimator
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E. Anderes
Compressed sensing in astrophysics and beyond
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J. Bobin
High level programming languages and hybrid programming in the context of high performance scientific applications
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G. Bosilca
Secondary CMB anisotropies and their simulations
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C. Carbone
Component separation techniques for CMB maps
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J.F. Cardoso
CMB power spectrum estimation techniques
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J. Dunkley
sampling algorithms, Markov and non-Markov chains
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G. Fort
Making maps for CMB experiments
R. Keskitalo, E. Keihanen, H. Kurki-Suonio, T. Poutanen, A.S. Suur-Uski, J. Borrill and T.S. Kisner
needlets/wavelets nonGaussianity estimators
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D. Marinucci
Hunting for relics from the early universe in the CMB
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H. Peiris
Discrete Aspects of High-Performance Iterative Linear Solvers
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S. Toledo
non-Gaussianity tests
B. Wandelt and F. Elsner
on recent developments in numerical linear algebra
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L. Grigori
Contributed
Sparse component separation for accurate CMB map estimation
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S. Basak
CMB lensing reconstruction in the presence of diffuse polarized foregrounds
Y. Fantaye, C. Baccigalupi, S. Leach and A. Yadav
A robust constraint on cosmic textures from the cosmic microwave background
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S. Feeney
Deriving bounds for trispectrum estimators for Planck
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D. Galliano
Power spectrum estimation on the sphere using wavelets
F. Guilloux
Nets and nests: accelerated Bayesian inference in astrophysics
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M. Hobson
Restoration of a whole-sky CMB map
J. Kim, P. Naselsky and N. Mandolesi
Searching for the Unexpected
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L. Knox
Simple foreground cleaning algorithm for detecting primordial B-mode polarization of the cosmic microwave background
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E. Komatsu
Spherical wavelet-Bayesian cosmic string tension estimation
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J. McEwen
Methodology and lessons from the QUIET Maximum Likelihood map-maker
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S. Næss
True CMB Power Spectrum Estimation
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P. Pavkari
Removal of two large scale Cosmic Microwave Background anomalies after subtraction of the Integrated Sachs Wolfe effect
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A. Rassat
Reconstruction of high-resolution SZ maps from heterogeneous datasets using needlets
M. Remazeilles
Primordial non-Gaussianity and diffuse Galactic emissions
A. Renzi
Detection of Point Sources Using Internal Templates and Needlets
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S. Scodeller
Avoiding Communication in Generalized Least Square Problems
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M. Sharify
Accelerating convolutions on the sphere with hybid GPU/CPU kernel splitting
P. Sutter, B.D. Wandelt and F. Elsner
Component Separation for Full-Sky Cosmic Microwave Background Recovery using Sparsity
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F. Sureau
Accelerating maximum likelihood Cosmic Microwave Background map-making
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M. Szydlarski