Variational Quantum‐Neural Hybrid Error Mitigation

Zhang, Shi‐Xin; Wan, Zhou‐Quan; Hsieh, Chang‐Yu; Yao, Hong; Zhang, Shengyu

doi:10.1002/qute.202300147

Cited by 6 publications

(1 citation statement)

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“…Here, we describe our approach to construct the re-entangling circuit M (τ) as in eq , carried out as a virtual Heisenberg circuit in the spirit of refs , , . We first start by taking a closer look at folding typical circuit building blocks, not necessarily Clifford, in a generator formalism before introducing a procedure to build M (τ).…”

Section: Methodsmentioning

confidence: 99%

Partitioning Quantum Chemistry Simulations with Clifford Circuits

Schleich

Boen

Cincio

et al. 2023

J. Chem. Theory Comput.

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Current quantum computing hardware is restricted by the availability of only few, noisy qubits which limits the investigation of larger, more complex molecules in quantum chemistry calculations on quantum computers in the near term. In this work, we investigate the limits of their classical and near-classical treatment while staying within the framework of quantum circuits and the variational quantum eigensolver. To this end, we consider naive and physically motivated, classically efficient product ansatz for the parametrized wavefunction adapting the separable-pair ansatz form. We combine it with post-treatment to account for interactions between subsystems originating from this ansatz. The classical treatment is given by another quantum circuit that has support between the enforced subsystems and is folded into the Hamiltonian. To avoid an exponential increase in the number of Hamiltonian terms, the entangling operations are constructed from purely Clifford or near-Clifford circuits. While Clifford circuits can be simulated efficiently classically, they are not universal. In order to account for missing expressibility, near-Clifford circuits with only few, selected non-Clifford gates are employed. The exact circuit structure to achieve this objective is molecule-dependent and is constructed using simulated annealing and genetic algorithms. We demonstrate our approach on a set of molecules of interest and investigate the extent of our methodology’s reach.

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Section: Methodsmentioning

confidence: 99%

Partitioning Quantum Chemistry Simulations with Clifford Circuits

Schleich

Boen

Cincio

et al. 2023

J. Chem. Theory Comput.

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Variational post-selection for ground states and thermal states simulation

Zhang,

Miao,

Hsieh

2024

Quantum Sci. Technol.

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Variational quantum algorithms (VQAs), as one of the most promising routes in the noisy intermediate-scale quantum (NISQ) era, offer various potential applications while also confront severe challenges due to near-term quantum hardware restrictions. In this work, we propose a framework to enhance the expressiveness of variational quantum ansatz by incorporating variational post-selection techniques. These techniques apply variational modules and neural network post-processing on ancilla qubits, which are compatible with the current generation of quantum devices. Equipped with variational post-selection, we demonstrate that the accuracy of the variational ground state and thermal state preparation for both quantum spin and molecule systems is substantially improved. Notably, in the case of estimating the local properties of a thermalized quantum system, we present a scalable approach that outperforms previous methods through the combination of neural post-selection and a new optimization objective.

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