Determining the Ensemble <i>N</i> -Representability of Reduced Density Matrices

The <i>N</i>-representability problem for reduced density matrices remains a fundamental challenge in electronic structure theory. Following our previous work that employs a unitary-evolution algorithm based on an adaptive derivative-assembled pseudo-Trotter variational quantum algorithm to probe <i>pure-state N</i>-representability of reduced density matrices [J. Chem. Theory Comput. 2024, 20, 9968], in this work we propose a practical framework for determining the <i>ensemble N</i>-representability of a <i>p</i>-body matrix. This is accomplished using a purification strategy that embeds an ensemble state into a pure state defined on an extended Hilbert space, such that the reduced density matrices of the purified state reproduce those of the original ensemble. By iteratively applying variational unitaries to an initial purified state, the proposed algorithm minimizes the Hilbert-Schmidt distance between its <i>p</i>-body reduced density matrix and a specified target <i>p</i>-body matrix, which serves as a measure of the <i>N</i>-representability of the target. This methodology facilitates both error correction of defective ensemble reduced density matrices and quantum-state reconstruction on a quantum computer, offering a route for density-matrix refinement. We validate the algorithm with numerical simulations on systems of two, three, and four electrons in both simple models as well as molecular systems at finite temperature, demonstrating its robustness.

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Journal
Journal of Chemical Theory and Computation
Published
2025-12-26
DOI
https://doi.org/10.1021/acs.jctc.5c01788
Primary Topic
Quantum Computing Algorithms and Architecture
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article
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article

Determining the Ensemble N -Representability of Reduced Density Matrices

Gustavo E. Scuseria, Juan E. Peralta, Luis Laín, Gustavo E. Massaccesi et al.
Journal of Chemical Theory and Computation
Quantum Computing Algorithms and Architecture
article

Determining the Ensemble N -Representability of Reduced Density Matrices

Gustavo E. Scuseria, Juan E. Peralta, Luis Laín, Gustavo E. Massaccesi, Ofelia B. Oña, Diego R. Alcoba, P. Capuzzi, Alicia Torre
article en

Abstract

The <i>N</i>-representability problem for reduced density matrices remains a fundamental challenge in electronic structure theory. Following our previous work that employs a unitary-evolution algorithm based on an adaptive derivative-assembled pseudo-Trotter variational quantum algorithm to probe <i>pure-state N</i>-representability of reduced density matrices [J. Chem. Theory Comput. 2024, 20, 9968], in this work we propose a practical framework for determining the <i>ensemble N</i>-representability of a <i>p</i>-body matrix. This is accomplished using a purification strategy that embeds an ensemble state into a pure state defined on an extended Hilbert space, such that the reduced density matrices of the purified state reproduce those of the original ensemble. By iteratively applying variational unitaries to an initial purified state, the proposed algorithm minimizes the Hilbert-Schmidt distance between its <i>p</i>-body reduced density matrix and a specified target <i>p</i>-body matrix, which serves as a measure of the <i>N</i>-representability of the target. This methodology facilitates both error correction of defective ensemble reduced density matrices and quantum-state reconstruction on a quantum computer, offering a route for density-matrix refinement. We validate the algorithm with numerical simulations on systems of two, three, and four electrons in both simple models as well as molecular systems at finite temperature, demonstrating its robustness.

Journal of Chemical Theory and ComputationVol. 22(1)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Central Michigan University (US), University of the Basque Country (ES), Universidad de Buenos Aires (AR), Centro Científico Tecnológico - San Juan (AR), Instituto de Física La Plata (AR), Department of Physics, Mathematics and Informatics (BY), Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (AR), Institute of Mathematical Sciences (ES), Instituto de Física de Buenos Aires (AR), Fundación Ciencias Exactas y Naturales (AR), Rice University (US)
Openalex Percentile: Top 18%
Quantum Computing Algorithms and Architecture
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