Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A hybrid machine-learning algorithm for designing quantum experiments   We introduce a hybrid machine-learning algorithm for designing quantum optics
experiments that produce specific quantum states. Our algorithm successfully
found experimental schemes to produce all 5 states we asked it to, including
Schr\"odinger cat states and cubic phase states, all to a fidelity of over
$96\%$. Here we specifically focus on designing realistic experiments, and
hence all of the algorithm's designs only contain experimental elements that
are available with current technology. The core of our algorithm is a genetic
algorithm that searches for optimal arrangements of the experimental elements,
but to speed up the initial search we incorporate a neural network that
classifies quantum states. The latter is of independent interest, as it quickly
learned to accurately classify quantum states given their photon-number
distributions.

2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat