Homequant-pharXiv:2605.30141

Overcoming the Matrix-Product-State Encoding Barrier via DMRG-Guided Probabilistic Imaginary-Time Evolution

quant-ph2026-05v1license

Abstract

Ground-state preparation is a fundamental task in quantum simulation, because the overlap of the prepared state with the true ground state significantly affects the overall cost of subsequent quantum algorithms. We propose a three-stage framework in which a matrix product state (MPS) of an NN-site system obtained by the density-matrix renormalization group (DMRG) is loaded onto an NN-qubit quantum register through an optimization-free matrix product disentangler (MPD) encoding circuit, and the residual error is then reduced by probabilistic imaginary-time evolution (PITE). We demonstrate that the central-bond Schmidt rank of intermediate states during MPS encoding grows logistically with the number of layers. Its inflection point LL^{*} marks the boundary of the efficient encoding regime. Beyond this point, the gain in fidelity slows rapidly, and the number of additional MPD layers required to reach a target infidelity ε\varepsilon empirically scales as O(N5log(N/ε))\mathcal{O}(N^5\log(N/\varepsilon)). To avoid this encoding-only tail, we stop the encoder at LL^{*} and suppress the remaining excited-state components by PITE, with the linear PITE schedule fixed deterministically from the ground-state energy, the effective gap, and the reference overlap estimated by DMRG. Numerical experiments on the spin-1/21/2 staggered-field Heisenberg chain show that the framework avoids very deep encoding circuits and substantially suppresses the post-selection overhead intrinsic to PITE. Combining classical preprocessing by DMRG, optimization-free MPS encoding, and deterministically scheduled PITE, the present framework offers a practical hybrid route to ground-state preparation in quantum simulation.

Cite

@article{arxiv.2605.30141,
  title  = {Overcoming the Matrix-Product-State Encoding Barrier via DMRG-Guided Probabilistic Imaginary-Time Evolution},
  author = {Masari Watanabe and Hirofumi Nishi and Taichi Kosugi and Shinji Tsuneyuki and Yu-ichiro Matsushita},
  journal= {arXiv preprint arXiv:2605.30141},
  year   = {2026}
}