Benchmarking variational quantum circuits with permutation symmetry. (arXiv:2211.12711v1 [quant-ph])

We propose SnCQA, a set of hardware-efficient variational circuits of
equivariant quantum convolutional circuits respective to permutation symmetries
and spatial lattice symmetries with the number of qubits $n$. By exploiting
permutation symmetries of the system, such as lattice Hamiltonians common to
many quantum many-body and quantum chemistry problems, Our quantum neural
networks are suitable for solving machine learning problems where permutation
symmetries are present, which could lead to significant savings of
computational costs. Aside from its theoretical novelty, we find …

arxiv benchmarking quantum symmetry