346 research outputs found
The introduction of new interventional procedures in the British National Health Service : A qualitative study
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.Peer reviewedPostprin
Shrinkage Estimation of the Power Spectrum Covariance Matrix
We seek to improve estimates of the power spectrum covariance matrix from a
limited number of simulations by employing a novel statistical technique known
as shrinkage estimation. The shrinkage technique optimally combines an
empirical estimate of the covariance with a model (the target) to minimize the
total mean squared error compared to the true underlying covariance. We test
this technique on N-body simulations and evaluate its performance by estimating
cosmological parameters. Using a simple diagonal target, we show that the
shrinkage estimator significantly outperforms both the empirical covariance and
the target individually when using a small number of simulations. We find that
reducing noise in the covariance estimate is essential for properly estimating
the values of cosmological parameters as well as their confidence intervals. We
extend our method to the jackknife covariance estimator and again find
significant improvement, though simulations give better results. Even for
thousands of simulations we still find evidence that our method improves
estimation of the covariance matrix. Because our method is simple, requires
negligible additional numerical effort, and produces superior results, we
always advocate shrinkage estimation for the covariance of the power spectrum
and other large-scale structure measurements when purely theoretical modeling
of the covariance is insufficient.Comment: 9 pages, 7 figures (1 new), MNRAS, accepted. Changes to match
accepted version, including an additional explanatory section with 1 figur
The Universe at Extreme Scale: Multi-Petaflop Sky Simulation on the BG/Q
Remarkable observational advances have established a compelling
cross-validated model of the Universe. Yet, two key pillars of this model --
dark matter and dark energy -- remain mysterious. Sky surveys that map billions
of galaxies to explore the `Dark Universe', demand a corresponding
extreme-scale simulation capability; the HACC (Hybrid/Hardware Accelerated
Cosmology Code) framework has been designed to deliver this level of
performance now, and into the future. With its novel algorithmic structure,
HACC allows flexible tuning across diverse architectures, including accelerated
and multi-core systems.
On the IBM BG/Q, HACC attains unprecedented scalable performance -- currently
13.94 PFlops at 69.2% of peak and 90% parallel efficiency on 1,572,864 cores
with an equal number of MPI ranks, and a concurrency of 6.3 million. This level
of performance was achieved at extreme problem sizes, including a benchmark run
with more than 3.6 trillion particles, significantly larger than any
cosmological simulation yet performed.Comment: 11 pages, 11 figures, final version of paper for talk presented at
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