Concentration of Data Encoding in Parameterized Quantum Circuits. (arXiv:2206.08273v1 [quant-ph])

Web: http://arxiv.org/abs/2206.08273

Variational quantum algorithms have been acknowledged as a leading strategy
to realize near-term quantum advantages in meaningful tasks, including machine
learning and combinatorial optimization. When applied to tasks involving
classical data, such algorithms generally begin with quantum circuits for data
encoding and then train quantum neural networks (QNNs) to minimize target
functions. Although QNNs have been widely studied to improve these algorithms'
performance on practical tasks, there is a gap in systematically understanding
the influence of data encoding on the …

arxiv data encoding quantum