Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An efficient solver for large structured eigenvalue problems in
  relativistic quantum chemistry   We report an efficient program for computing the eigenvalues and
symmetry-adapted eigenvectors of very large quaternionic (or Hermitian
skew-Hamiltonian) matrices, using which structure-preserving diagonalization of
matrices of dimension N > 10000 is now routine on a single computer node. Such
matrices appear frequently in relativistic quantum chemistry owing to the
time-reversal symmetry. The implementation is based on a blocked version of the
Paige-Van Loan algorithm [D. Kressner, BIT 43, 775 (2003)], which allows us to
use the Level 3 BLAS subroutines for most of the computations. Taking advantage
of the symmetry, the program is faster by up to a factor of two than
state-of-the-art implementations of complex Hermitian diagonalization;
diagonalizing a 12800 x 12800 matrix took 42.8 (9.5) and 85.6 (12.6) minutes
with 1 CPU core (16 CPU cores) using our symmetry-adapted solver and Intel
MKL's ZHEEV that is not structure-preserving, respectively. The source code is
publicly available under the FreeBSD license.

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The categories of this paper are: bayes-an
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The categories of this paper are: nlin
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The categories of this paper are: cmp-lg
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The categories of this paper are: patt-sol
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The categories of this paper are: stat
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The categories of this paper are: math-ph
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The categories of this paper are: q-bio
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The categories of this paper are: math
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The categories of this paper are: econ
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The categories of this paper are: dg-ga
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
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The categories of this paper are: solv-int
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The categories of this paper are: hep-th
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The categories of this paper are: atom-ph
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The categories of this paper are: cs