Sparse power-of-two circuit connectivity provides task-dependent advantages for variational quantum learning, and a Monna-map qubit reordering enables short-range circuits to solve long-range problems.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
quant-ph 2years
2026 2roles
background 1polarities
background 1representative citing papers
Hadamard states exhibit higher average multipartite entanglement than Haar-typical states via purity of balanced bipartitions, with hypergraph states (real alternating-sign coefficients) being especially promising for maximal entanglement due to simplicity and sampling likelihood.
citing papers explorer
-
Variational Learning with Sparse Long-range Entangling Gates
Sparse power-of-two circuit connectivity provides task-dependent advantages for variational quantum learning, and a Monna-map qubit reordering enables short-range circuits to solve long-range problems.
-
Multipartite entanglement of random states of qubits
Hadamard states exhibit higher average multipartite entanglement than Haar-typical states via purity of balanced bipartitions, with hypergraph states (real alternating-sign coefficients) being especially promising for maximal entanglement due to simplicity and sampling likelihood.