Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Potential energy surface interpolation with neural networks for
  instanton rate calculations   Artificial neural networks are used to fit a potential energy surface. We
demonstrate the benefits of using not only energies, but also their first and
second derivatives as training data for the neural network. This ensures smooth
and accurate Hessian surfaces, which are required for rate constant
calculations using instanton theory. Our aim was a local, accurate fit rather
than a global PES, because instanton theory requires information on the
potential only in the close vicinity of the main tunneling path. Elongations
along vibrational normal modes at the transition state are used as coordinates
for the neural network. The method is applied to the hydrogen abstraction
reaction from methanol, calculated on a coupled-cluster level of theory. The
reaction is essential in astrochemistry to explain the deuteration of methanol
in the interstellar medium.

26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio