Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Large-scale all-electron density functional theory calculations using an
  enriched finite element basis   We present a computationally efficient approach to perform large-scale
all-electron density functional theory calculations by enriching the classical
finite element basis with compactly supported atom-centered numerical basis
functions that are constructed from the solution of the Kohn-Sham (KS) problem
for single atoms. We term these numerical basis functions as enrichment
functions, and the resultant basis as the enriched finite element basis. The
enrichment functions are compactly supported through the use of smooth cutoff
functions, which enhances the conditioning and maintains the locality of the
basis. The integrals involved in the evaluation of the discrete KS Hamiltonian
and overlap matrix in the enriched finite element basis are computed using an
adaptive quadrature grid based on the characteristics of enrichment functions.
Further, we propose an efficient scheme to invert the overlap matrix by using a
block-wise matrix inversion in conjunction with special reduced-order
quadrature rules to transform the discrete Kohn-Sham problem to a standard
eigenvalue problem. Finally, we solve the resulting standard eigenvalue problem
by using a Chebyshev polynomial based filtering technique to compute the
relevant eigenspectrum. We demonstrate the accuracy, efficiency and parallel
scalability of the proposed method on semiconducting and heavy-metallic systems
of various sizes, with the largest system containing 8694 electrons. We obtain
accuracies in the ground-state energies that are within $\sim 1$mHa with
ground-state energies obtained from classical finite element as well as
gaussian basis sets. We observe a $50-300$ and $\sim 8$ fold reduction in the
overall computational time when compared to classical finite element and
gaussian basis, respectively. We also observe good parallel scalability up to
384 processors for a benchmark system comprising of 280-atom silicon
nano-cluster.

14
The categories of this paper are: math-ph
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
1
The categories of this paper are: cs
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph