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Research PaperResearchia:202603.27083

Weighted Nested Commutators for Scalable Counterdiabatic State Preparation

Jialiang Tang

Abstract

Counterdiabatic (CD) driving enables efficient quantum state preparation, but it requires implementing highly nonlocal adiabatic gauge potentials (AGP) that are impractical to compute and realize in large many-body systems. We introduce a \textit{weighted nested-commutator} (WNC) ansatz to approximate AGP using local operators. The WNC ansatz generalizes the standard nested-commutator ansatz by assigning independent variational weights to commutators of local Hamiltonian terms, thereby enlarging...

Submitted: March 27, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Counterdiabatic (CD) driving enables efficient quantum state preparation, but it requires implementing highly nonlocal adiabatic gauge potentials (AGP) that are impractical to compute and realize in large many-body systems. We introduce a \textit{weighted nested-commutator} (WNC) ansatz to approximate AGP using local operators. The WNC ansatz generalizes the standard nested-commutator ansatz by assigning independent variational weights to commutators of local Hamiltonian terms, thereby enlarging the variational space while preserving a fixed operator range. We show that the WNC ansatz can be efficiently optimized using a local optimization scheme. Moreover, it systematically outperforms the nested-commutator ansatz in preparing one-dimensional matrix product states (MPS) and the ground state of a nonintegrable quantum Ising model. We then numerically demonstrate that CD driving based on the WNC ansatz significantly accelerates the preparation of 1D MPS for system sizes up to N=1000N = 1000 qubits, as well as the two-dimensional Affleck-Kennedy-Lieb-Tasaki state on a hexagonal lattice with up to N=3×10N = 3 \times 10 sites.


Source: arXiv:2603.25625v1 - http://arxiv.org/abs/2603.25625v1 PDF: https://arxiv.org/pdf/2603.25625v1 Original Link: http://arxiv.org/abs/2603.25625v1

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Date:
Mar 27, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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