Fast Quantum Simulation of Electronic Structure by Spectral Amplification

The most advanced techniques using fault-tolerant quantum computers to estimate the ground-state energy of a chemical Hamiltonian involve compression of the Coulomb operator through tensor factorizations, enabling efficient block encodings of the Hamiltonian. A natural challenge of these methods is the degree to which block-encoding costs can be reduced. We address this challenge through the technique of spectral amplification, which magnifies the spectrum of the low-energy states of Hamiltonians that can be expressed as sums of squares. Spectral amplification enables estimating ground-state energies with significantly improved cost scaling in the block encoding normalization factor <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi mathvariant="normal">Λ</a:mi> </a:math> to just <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" display="inline"> <d:msqrt> <d:mrow> <d:mn>2</d:mn> <d:mi mathvariant="normal">Λ</d:mi> <d:msub> <d:mi>E</d:mi> <d:mi>gap</d:mi> </d:msub> </d:mrow> </d:msqrt> </d:math> , where <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"> <g:msub> <g:mi>E</g:mi> <g:mi>gap</g:mi> </g:msub> <g:mo>≪</g:mo> <g:mi mathvariant="normal">Λ</g:mi> </g:math> is the lowest energy of the sum-of-squares Hamiltonian. To achieve this, we show that sum-of-squares representations of the electronic structure Hamiltonian are efficiently computable by a family of classical simulation techniques that approximate the ground-state energy from below. In order to further optimize, we also develop a novel factorization that provides a trade-off between the two leading Coulomb integral factorization schemes—namely, double factorization and tensor hypercontraction—that when combined with spectral amplification yields a factor of 4 to 195 speedup over the state of the art in ground-state energy estimation for models of iron-sulfur complexes and a <j:math xmlns:j="http://www.w3.org/1998/Math/MathML" display="inline"> <j:mrow> <j:msub> <j:mrow> <j:mi>CO</j:mi> </j:mrow> <j:mrow> <j:mn>2</j:mn> </j:mrow> </j:msub> </j:mrow> </j:math> -fixation catalyst.

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Publication Details

Journal
Physical Review X
Published
2025-09-09
DOI
https://doi.org/10.1103/pb2g-j9cw
Citations
3
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
7.44
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article

Fast Quantum Simulation of Electronic Structure by Spectral Amplification

Qianqian Han, Guang Hao Low, Nicholas C. Rubin, Ryan Babbush et al.
3 citations
Physical Review X
Quantum Computing Algorithms and Architecture
7.44
article

Fast Quantum Simulation of Electronic Structure by Spectral Amplification

Qianqian Han, Guang Hao Low, Nicholas C. Rubin, Ryan Babbush, A. Eugene DePrince, Alec F. White, Rolando D. Somma, Dominic W. Berry, Robbie King
article en
3 citations

Abstract

The most advanced techniques using fault-tolerant quantum computers to estimate the ground-state energy of a chemical Hamiltonian involve compression of the Coulomb operator through tensor factorizations, enabling efficient block encodings of the Hamiltonian. A natural challenge of these methods is the degree to which block-encoding costs can be reduced. We address this challenge through the technique of spectral amplification, which magnifies the spectrum of the low-energy states of Hamiltonians that can be expressed as sums of squares. Spectral amplification enables estimating ground-state energies with significantly improved cost scaling in the block encoding normalization factor <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"> <a:mi mathvariant="normal">Λ</a:mi> </a:math> to just <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" display="inline"> <d:msqrt> <d:mrow> <d:mn>2</d:mn> <d:mi mathvariant="normal">Λ</d:mi> <d:msub> <d:mi>E</d:mi> <d:mi>gap</d:mi> </d:msub> </d:mrow> </d:msqrt> </d:math> , where <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"> <g:msub> <g:mi>E</g:mi> <g:mi>gap</g:mi> </g:msub> <g:mo>≪</g:mo> <g:mi mathvariant="normal">Λ</g:mi> </g:math> is the lowest energy of the sum-of-squares Hamiltonian. To achieve this, we show that sum-of-squares representations of the electronic structure Hamiltonian are efficiently computable by a family of classical simulation techniques that approximate the ground-state energy from below. In order to further optimize, we also develop a novel factorization that provides a trade-off between the two leading Coulomb integral factorization schemes—namely, double factorization and tensor hypercontraction—that when combined with spectral amplification yields a factor of 4 to 195 speedup over the state of the art in ground-state energy estimation for models of iron-sulfur complexes and a <j:math xmlns:j="http://www.w3.org/1998/Math/MathML" display="inline"> <j:mrow> <j:msub> <j:mrow> <j:mi>CO</j:mi> </j:mrow> <j:mrow> <j:mn>2</j:mn> </j:mrow> </j:msub> </j:mrow> </j:math> -fixation catalyst.

Physical Review XVol. 15(4)
Florida State University (US), California Institute of Technology (US), Google (United States) (US), University of Illinois Urbana-Champaign (US), Quantum Simulations (United States) (US), Simulation Technologies (United States) (US), Macquarie University (AU)
Openalex Percentile: Top 3%
Quantum Computing Algorithms and Architecture
7.44
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