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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Fast Tensor Network Imaginary Time Evolution by Implicit Stepping on Logarithmic Grids
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.