Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Derivative-free optimization for parameter estimation in computational
  nuclear physics   We consider optimization problems that arise when estimating a set of unknown
parameters from experimental data, particularly in the context of nuclear
density functional theory. We examine the cost of not having derivatives of
these functionals with respect to the parameters. We show that the POUNDERS
code for local derivative-free optimization obtains consistent solutions on a
variety of computationally expensive energy density functional calibration
problems. We also provide a primer on the operation of the POUNDERS software in
the Toolkit for Advanced Optimization.

20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
7
The categories of this paper are: hep-th