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Published November 28, 2023 | Published
Journal Article Open

Efficient Mean-Field Simulation of Quantum Circuits Inspired by Density Functional Theory

  • 1. ROR icon California Institute of Technology

Abstract

Exact simulations of quantum circuits (QCs) are currently limited to ∼50 qubits because the memory and computational cost required to store the QC wave function scale exponentially with qubit number. Therefore, developing efficient schemes for approximate QC simulations is a current research focus. Here, we show simulations of QCs with a method inspired by density functional theory (DFT), a widely used approach for studying many-electron systems. Our calculations can predict marginal single-qubit probabilities (SQPs) with over 90% accuracy in several classes of QCs with universal gate sets, using memory and computational resources linear in qubit number despite the formal exponential cost of the SQPs. This is achieved by developing a mean-field description of QCs and formulating optimal single- and two-qubit gate functionals─analogues of exchange-correlation functionals in DFT─to evolve the SQPs without computing the QC wave function. Current limitations and future extensions of this formalism are discussed.

Acknowledgement

© 2023 American Chemical Society.

Contributions

The author acknowledges fruitful discussions with Sijing Du, Sandeep Sharma, and Garnet Chan. This work was supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, and Office of Basic Energy Sciences, Scientific Discovery through Advanced Computing (SciDAC) program under award number DE-SC0022088.

Data Availability

The data sets generated and analyzed in this study, as well as the QC-DFT codes, will be made available in the CaltechDATA repository. Additional data and information are available upon reasonable request. The QuEST code (6) used for the exact QC simulations is an open source software, which can be downloaded at https://quest.qtechtheory.org. The QC drawings were prepared using the Quantikz LaTeX package, (36) which can be downloaded at https://ctan.org/pkg/quantikz. The QC-DFT Python code will be made available in the CaltechDATA repository.

Conflict of Interest

The author declares no competing financial interest.

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Additional details

Created:
December 13, 2023
Modified:
December 13, 2023