Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Classifying global state preparation via deep reinforcement learning   Quantum information processing often requires the preparation of arbitrary
quantum states, such as all the states on the Bloch sphere for two-level
systems. While numerical optimization can prepare individual target states,
they lack the ability to find general solutions that work for a large class of
states in more complicated quantum systems. Here, we demonstrate global quantum
control by preparing a continuous set of states with deep reinforcement
learning. The protocols are represented using neural networks, which
automatically groups the protocols into similar types, which could be useful
for finding classes of protocols and extracting physical insights. As
application, we generate arbitrary superposition states for the electron spin
in complex multi-level nitrogen-vacancy centers, revealing classes of protocols
characterized by specific preparation timescales. Our method could help improve
control of near-term quantum computers, quantum sensing devices and quantum
simulations.

26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
1
The categories of this paper are: cs