Filter-assisted SQD uses a quantum filter to engineer sparser ground-state wavefunctions, yielding orders-of-magnitude lower energy errors and reduced sampling overhead versus standard SQD on the transverse-longitudinal Ising model.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Filter-assisted quantum subspace diagonalization via wavefunction sparsity engineering
Filter-assisted SQD uses a quantum filter to engineer sparser ground-state wavefunctions, yielding orders-of-magnitude lower energy errors and reduced sampling overhead versus standard SQD on the transverse-longitudinal Ising model.