Logarithmic grids combined with implicit ODE stepping reduce the number of time steps exponentially for MPS imaginary time evolution while maintaining stability via standard matrix operations.
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Z_N cluster and dipolar-cluster SPT wavefunctions admit closed-form projector, neural, and tensor-product representations that generalize Z_2 constructions and yield a TPS benchmarked against MPS via DMRG.
The paper proposes variational decision diagrams (VDDs) for quantum state representation in QML and reports successful training without barren plateaus on transverse-field Ising and Heisenberg Hamiltonians.
A comprehensive review of scaling paths for superconducting quantum computers, with resource and sensitivity analyses for utility-scale applications under realistic error distributions.
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Projector, Neural, and Tensor-Network Representations of $\mathbb{Z}_N$ Cluster and Dipolar-cluster SPT States
Z_N cluster and dipolar-cluster SPT wavefunctions admit closed-form projector, neural, and tensor-product representations that generalize Z_2 constructions and yield a TPS benchmarked against MPS via DMRG.