Implementation of the Density-functional Theory on Quantum Computers with Linear Scaling with respect to the Number of Atoms

TL;DR

This paper introduces a quantum algorithm for density-functional theory that scales linearly with the number of atoms, significantly improving computational efficiency for large-scale chemical and material simulations.

Contribution

It presents a novel quantum algorithm using QSVT for encoding the density matrix and a randomized method to accelerate self-consistent field calculations, with rigorous error analysis.

Findings

Achieves linear scaling with respect to the number of atoms

Provides a quantum circuit for density matrix encoding

Includes error analysis accounting for measurement noise

Abstract

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing the Hamiltonian, for which a classical algorithm typically requires a computational complexity that scales cubically with respect to the number of electrons. This limits DFT's applicability to large-scale problems with complex chemical environments and microstructures. This article presents a quantum algorithm that has a linear scaling with respect to the number of atoms, which is much smaller than the number of electrons. Our algorithm leverages the quantum singular value transformation (QSVT) to generate a quantum circuit to encode the density-matrix, and an estimation method for computing the output electron density. In addition, we present a randomized block coordinate fixed-point method to accelerate the self-consistent field calculations by reducing the number of components of the electron density that needs to be estimated. The proposed framework is accompanied by a rigorous error analysis that quantifies the function approximation error, the statistical fluctuation, and the iteration complexity. In particular, the analysis of our self-consistent iterations takes into account the measurement noise from the quantum circuit. These advancements offer a promising avenue for tackling large-scale DFT problems, enabling simulations of complex systems that were previously computationally infeasible.