Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient method for accelerating line searches using a combined Schur
  complement domain decomposition and Born series expansions in photonic-based
  adjoint optimization   A line search in gradient-based optimization algorithm solves the problem of
determining the optimal learning rate for a given gradient or search direction
in a single iteration. For most problems, this is determined by evaluating
different candidate learning rates to find the optimum, which can be expensive.
Recent work has provided an efficient way to perform a line search with the use
of the Shanks transformation of a Born series derived from the
Lippman-Schwinger formalism. In this paper we show that the cost for performing
such a line search can be further reduced with the use of the method of the
Schur complement domain decomposition, which can lead to a 10-fold total
speed-up resulting from the reduced number of iterations to convergence and
reduced wall-clock time per iteration.

18
The categories of this paper are: econ
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
1
The categories of this paper are: cs
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph