Preparation Circuits for Matrix Product States by Classical Variational Disentanglement

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Mansuroglu, Refik, Schuch, Norbert
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917404981854208
author Mansuroglu, Refik
Schuch, Norbert
author_facet Mansuroglu, Refik
Schuch, Norbert
contents We study the classical compilation of quantum circuits for the preparation of matrix product states (MPS), which are quantum states of low entanglement with an efficient classical description. Our algorithm represents a near-term alternative to previous sequential approaches by reverse application of a disentangler, which can be found by minimizing bipartite entanglement measures after the application of a layer of parameterized disentangling gates. Since a successful disentangler is expected to decrease the bond dimension on average, such a layer-by-layer optimization remains classically efficient even for deep circuits. Additionally, as the Schmidt coefficients of all bonds are locally accessible through the canonical $Γ$-$Λ$ form of an MPS, the optimization algorithm can be heavily parallelized. We discuss guarantees and limitations to trainability and show numerical results for ground states of one-dimensional, local Hamiltonians as well as artificially spread out entanglement among multiple qubits using error correcting codes.
format Preprint
id arxiv_https___arxiv_org_abs_2504_21298
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Preparation Circuits for Matrix Product States by Classical Variational Disentanglement
Mansuroglu, Refik
Schuch, Norbert
Quantum Physics
We study the classical compilation of quantum circuits for the preparation of matrix product states (MPS), which are quantum states of low entanglement with an efficient classical description. Our algorithm represents a near-term alternative to previous sequential approaches by reverse application of a disentangler, which can be found by minimizing bipartite entanglement measures after the application of a layer of parameterized disentangling gates. Since a successful disentangler is expected to decrease the bond dimension on average, such a layer-by-layer optimization remains classically efficient even for deep circuits. Additionally, as the Schmidt coefficients of all bonds are locally accessible through the canonical $Γ$-$Λ$ form of an MPS, the optimization algorithm can be heavily parallelized. We discuss guarantees and limitations to trainability and show numerical results for ground states of one-dimensional, local Hamiltonians as well as artificially spread out entanglement among multiple qubits using error correcting codes.
title Preparation Circuits for Matrix Product States by Classical Variational Disentanglement
topic Quantum Physics
url https://arxiv.org/abs/2504.21298