Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimization of Quantum Algorithm Protocols without Barren Plateaus   Quantum machine learning has emerged as a promising method to improve
near-term quantum computation devices. However, algorithmic classes such as
variational quantum algorithms have been shown to suffer from barren plateaus
due to vanishing gradients in their parameter spaces. We present an approach to
quantum algorithm optimization that is based on trainable Fourier coefficients
of Hamiltonian system parameters. Our ansatz applies to the extension of
discrete quantum variational algorithms to analogue quantum optimal control
schemes and is non-local in time. We demonstrate the viability of our ansatz on
several objective functions using quantum natural gradient descent. In
comparison to the temporally local discretization ans\"atze in quantum optimal
control and parametrized circuits, our ansatz exhibits faster and more
consistent convergence with a distinct lack of barren plateaus. We propose our
ansatz as a viable parametrization candidate for near-term quantum machine
learning.

19
The categories of this paper are: eess
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol