Optimizing electronic structure simulations on a trapped-ion quantum computer using problem decomposition

Kawashima, Yukio; Lloyd, Erika; Coons, Marc P.; Nam, Yoonsu; Matsuura, Shunji; Garza, Alejandro J.; Johri, Sonika; Huntington, Lee; Senicourt, Valentin; Maksymov, Andrii O.; Nguyen, Jason; Kim, Jungsang; Alidoust, Nima; Zaribafiyan, Arman; Yamazaki, Takeshi

doi:10.1038/s42005-021-00751-9

Cited by 34 publications

(40 citation statements)

References 43 publications

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“…al. 57 where chemical precision relative to FCI calculations was achieved for the H ring by exploiting the high level of rotational symmetry in the system. Chemical precision has also been reported for NaH 58 on 4 superconducting qubits using a frozen core approximation and a UCC inspired circuit, a problem of similar size to the H molecule simulated, reaching chemical precision relative to the FCI energy.…”

Section: Resultsmentioning

confidence: 99%

Chemistry beyond the Hartree–Fock energy via quantum computed moments

Jones

Vallury

Hill

et al. 2022

Sci Rep

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Quantum computers hold promise to circumvent the limitations of conventional computing for difficult molecular problems. However, the accumulation of quantum logic errors on real devices represents a major challenge, particularly in the pursuit of chemical accuracy requiring the inclusion of electronic correlation effects. In this work we implement the quantum computed moments (QCM) approach for hydrogen chain molecular systems up to H$$_6$$ 6 . On a superconducting quantum processor, Hamiltonian moments, $$\langle H^p\rangle$$ ⟨ H p ⟩ are computed with respect to the Hartree–Fock state, which are then employed in Lanczos expansion theory to determine an estimate for the ground-state energy which incorporates electronic correlations and manifestly improves on the direct energy measurement. Post-processing purification of the raw QCM data takes the estimate below the Hartree–Fock energy to within 99.9% of the exact electronic ground-state energy for the largest system studied, H$$_6$$ 6 . Calculated dissociation curves indicate precision at about 10mH for this system and as low as 0.1mH for molecular hydrogen, H$$_2$$ 2 , over a range of bond lengths. In the context of stringent precision requirements for chemical problems, these results provide strong evidence for the error suppression capability of the QCM method, particularly when coupled with post-processing error mitigation. While calculations based on the Hartree–Fock state are tractable to classical computation, these results represent a first step towards implementing the QCM method in a quantum chemical trial circuit. Greater emphasis on more efficient representations of the Hamiltonian and classical preprocessing steps may enable the solution of larger systems on near-term quantum processors.

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Section: Resultsmentioning

confidence: 99%

Chemistry beyond the Hartree–Fock energy via quantum computed moments

Jones

Vallury

Hill

et al. 2022

Sci Rep

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“…VQE is a hybrid quantum-classical algorithm in which the quantum device is used to prepare a circuit ansatz and the classical computer performs optimization to find the parameters for the quantum ansatz such that the parameterized state is close to the unknown ground state. There is dramatic progress in experimental and theoretical study of VQE recently [8,29,51,[54][55][56][57][58][59][60][61][62][63][64][65][66][67]. However, several problems exist which may limit the power of VQE.…”

Section: Appendix E: Comparison Of Vqe and Qite Variantsmentioning

confidence: 99%

Efficient quantum imaginary time evolution by drifting real time evolution: an approach with low gate and measurement complexity

Huang¹,

Shao²,

Ren³

et al. 2022

Preprint

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“…This section demonstrates how Tangelo's API works, through some examples used in previous works, including an end-to-end pipeline featured in reference [56]. We elaborate on the implementation and interface of the building blocks used for each step.…”

Section: Api Overview Through End-to-end Examplesmentioning

confidence: 99%

Tangelo: An Open-source Python Package for End-to-end Chemistry Workflows on Quantum Computers

Senicourt¹,

Brown²,

Fleury³

et al. 2022

Preprint

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Tangelo (https link) is an open-source Python software package for the development of end-to-end chemistry workflows on quantum computers, released under Apache 2.0 license. It aims to support the design of successful experiments on quantum hardware, and to facilitate advances in quantum algorithm development. The software enables quick exploration of different approaches by assembling reusable building blocks and algorithms, with the flexibility to let users introduce their own. Tangelo is backend-agnostic and enables switching between various backends (Braket, Qiskit, Qulacs, Azure Quantum, QDK, Cirq...) with minimal changes in the code. The package can be used to explore quantum computing applications such as open-shell systems, excited states, or more industrially-relevant systems by leveraging problem decomposition at scale. This paper outlines the design choices, philosophy, and main features of Tangelo.

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Optimizing electronic structure simulations on a trapped-ion quantum computer using problem decomposition

Cited by 34 publications

References 43 publications

Chemistry beyond the Hartree–Fock energy via quantum computed moments

Chemistry beyond the Hartree–Fock energy via quantum computed moments

Efficient quantum imaginary time evolution by drifting real time evolution: an approach with low gate and measurement complexity

Tangelo: An Open-source Python Package for End-to-end Chemistry Workflows on Quantum Computers

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