Quantum Embedding Method for the Simulation of Strongly Correlated Systems on Quantum Computers

• URL: http://arxiv.org/abs/2302.03052v1
• Date: Mon, 6 Feb 2023 19:00:03 GMT
• Title: Quantum Embedding Method for the Simulation of Strongly Correlated Systems on Quantum Computers
• Authors: Max Rossmannek, Fabijan Pavo\v{s}evi\'c, Angel Rubio, Ivano Tavernelli
• Abstract summary: We introduce the projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm with density functional theory (DFT) The developed VQE-in-DFT method is then implemented efficiently on a real quantum device and employed for simulating the triple bond breaking process in butyronitrile. The developments will benefit many different chemical areas including the computer aided drug design as well as the study of metalloenzymes with a strongly correlated fragment.
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• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum computing has emerged as a promising platform for simulating strongly correlated systems in chemistry, for which the standard quantum chemistry methods are either qualitatively inaccurate or too expensive. However, due to the hardware limitations of the available noisy near-term quantum devices, their application is currently limited only to small chemical systems. One way for extending the range of applicability can be achieved within the quantum embedding approach. Herein, we employ the projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm, although not limited to, with density functional theory (DFT). The developed VQE-in-DFT method is then implemented efficiently on a real quantum device and employed for simulating the triple bond breaking process in butyronitrile. The results presented herein show that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer. The developments as well as the accompanying implementation will benefit many different chemical areas including the computer aided drug design as well as the study of metalloenzymes with a strongly correlated fragment.

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