Constructs boundary-consistent weakly relativistic lattice Hamiltonians for 1D first-quantized simulation by reconstructing momentum moments from cyclic translations (PBC) or finite differences (DBC), validated on benchmark potentials.
arXiv preprint arXiv:2109.09216 , year =
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Conformalized Quantum DeepONet Ensembles reduce operator inference from quadratic to linear complexity using QOrthoNNs and SPQCs while delivering distribution-free uncertainty guarantees through ensemble conformal prediction.
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First-Quantized Relativistic Quantum Simulation with Periodic and Dirichlet Boundary Conditions
Constructs boundary-consistent weakly relativistic lattice Hamiltonians for 1D first-quantized simulation by reconstructing momentum moments from cyclic translations (PBC) or finite differences (DBC), validated on benchmark potentials.
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Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty
Conformalized Quantum DeepONet Ensembles reduce operator inference from quadratic to linear complexity using QOrthoNNs and SPQCs while delivering distribution-free uncertainty guarantees through ensemble conformal prediction.