Abstract claims zero-shot 5-to-10-city EQC transfer beats target-size training only in exact simulation, degrading by 31.3% under sampling noise and 45.3% on hardware; the supplied body omits these experiments.
Joshi, Quentin Cappart, Louis-Martin Rousseau, and Thomas Laurent
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Diagnosing Simulation and Hardware Barriers to Cross-Size Transfer in Equivariant Quantum Reinforcement Learning
Abstract claims zero-shot 5-to-10-city EQC transfer beats target-size training only in exact simulation, degrading by 31.3% under sampling noise and 45.3% on hardware; the supplied body omits these experiments.