Pauli Correlation Encoding with a trained problem-aware decoder achieves 75-100% near-optimal recovery on mRNA QUBO instances up to 152 variables and matches or exceeds simulator performance on IBM Heron processors for 694-745 variable cases.
Available: https://link.aps.org/doi/10.1103/PhysRevA.105.032620 14
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
quant-ph 3years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
MCMit mitigates mid-circuit measurement errors via a new multi-control branch instruction, CNN and transformer discriminators, and software techniques, reporting up to 70% latency reduction and 80% lower logical error rates in QEC.
citing papers explorer
-
Pauli Correlation Encoding for mRNA Secondary Structure Prediction: Problem-Aware Decoding for Dense-Constraint QUBOs
Pauli Correlation Encoding with a trained problem-aware decoder achieves 75-100% near-optimal recovery on mRNA QUBO instances up to 152 variables and matches or exceeds simulator performance on IBM Heron processors for 694-745 variable cases.
-
Benchmarking quantum simulation with neutron-scattering experiments
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
-
MCMit: Mid-Circuit Measurement Error Mitigation
MCMit mitigates mid-circuit measurement errors via a new multi-control branch instruction, CNN and transformer discriminators, and software techniques, reporting up to 70% latency reduction and 80% lower logical error rates in QEC.