Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Karhunen-Loeve eigenvalue problems in cosmology: how should we tackle
  large data sets?   Since cosmology is no longer "the data-starved science", the problem of how
to best analyze large data sets has recently received considerable attention,
and Karhunen-Loeve eigenvalue methods have been applied to both galaxy redshift
surveys and Cosmic Microwave Background (CMB) maps. We present a comprehensive
discussion of methods for estimating cosmological parameters from large data
sets, which includes the previously published techniques as special cases. We
show that both the problem of estimating several parameters jointly and the
problem of not knowing the parameters a priori can be readily solved by adding
an extra singular value decomposition step.
  It has recently been argued that the information content in a sky map from a
next generation CMB satellite is sufficient to measure key cosmological
parameters (h, Omega, Lambda, etc) to an accuracy of a few percent or better -
in principle. In practice, the data set is so large that both a brute force
likelihood analysis and a direct expansion in signal-to-noise eigenmodes will
be computationally unfeasible. We argue that it is likely that a Karhunen-Loeve
approach can nonetheless measure the parameters with close to maximal accuracy,
if preceded by an appropriate form of quadratic "pre-compression".
  We also discuss practical issues regarding parameter estimation from present
and future galaxy redshift surveys, and illustrate this with a generalized
eigenmode analysis of the IRAS 1.2 Jy survey optimized for measuring
beta=Omega^{0.6}/b using redshift space distortions.

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The categories of this paper are: physics
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The categories of this paper are: q-fin
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
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The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-th
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The categories of this paper are: cs
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
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The categories of this paper are: comp-gas
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The categories of this paper are: alg-geom