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Exploring variational quantum eigensolver ansatzes for the long-range XY model

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arxiv 2109.00288 v5 pith:7FSTCOCD submitted 2021-09-01 quant-ph

classification quant-ph
keywords ansatzesfull-entanglementquantumgategroundlong-rangemodelstate
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Finding the ground state energy and wavefunction of a quantum many-body system is a key problem in quantum physics and chemistry. We study this problem for the long-range XY model by using the variational quantum eigensolver (VQE) algorithm. We consider VQE ansatzes with full and linear entanglement structures consisting of different building gates: the CNOT gate, the controlled-rotation (CRX) gate, and the two-qubit rotation (TQR) gate. We find that the full-entanglement CRX and TQR ansatzes can sufficiently describe the ground state energy of the long-range XY model. In contrast, only the full-entanglement TQR ansatz can represent the ground state wavefunction with a fidelity close to one. In addition, we find that instead of using full-entanglement ansatzes, restricted-entanglement ansatzes where entangling gates are applied only between qubits that are a fixed distance from each other already suffice to give acceptable solutions. Using the entanglement entropy to characterize the expressive powers of the VQE ansatzes, we show that the full-entanglement TQR ansatz has the highest expressive power among them.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. OneAdapt: Adaptive Compilation for Resource-Constrained Photonic One-Way Quantum Computing

    quant-ph 2025-04 conditional novelty 6.0 of 10

    OneAdapt introduces a resource-adaptive compilation approach for photonic one-way quantum computing, using dynamic node refresh and skewed temporal edges to reduce hardware size and execution depth.

  2. QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning

    quant-ph 2024-12 conditional novelty 4.0 of 10

    QuLTSF, a linear model with a 10-qubit variational circuit inserted between two linear layers, reports improved MSE and MAE on the Weather dataset across horizons 96 to 720.

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