Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convolutional restricted Boltzmann machine aided Monte Carlo: An
  application to Ising and Kitaev models   Machine learning is becoming widely used in analyzing the thermodynamics of
many-body condensed matter systems. Restricted Boltzmann Machine (RBM) aided
Monte Carlo simulations have sparked interest recently, as they manage to speed
up classical Monte Carlo simulations. Here we employ the Convolutional
Restricted Boltzmann Machine (CRBM) method and show that its use helps to
reduce the number of parameters to be learned drastically by taking advantage
of translation invariance. Furthermore, we show that it is possible to train
the CRBM at smaller lattice sizes, and apply it to larger lattice sizes. To
demonstrate the efficiency of CRBM we apply it to the paradigmatic Ising and
Kitaev models in two-dimensions.

27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
1
The categories of this paper are: cs
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ