Evidence map›Paper›PMID 33602988›Full record

ArticleScientific reports2021

Reduction of the molecular hamiltonian matrix using quantum community detection.

Susan M Mniszewski, Pavel A Dub, Sergei Tretiak, Petr M Anisimov, Yu Zhang, Christian F A Negre

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Susan M MniszewskiComputer, Computational and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. smm@lanl.gov.
Pavel A DubChemistry Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Sergei TretiakTheoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Petr M AnisimovAccelerator Operations and Technology Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Yu ZhangTheoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Christian F A NegreTheoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA.
Los Alamos National Laboratory · US

Funding

Los Alamos National Laboratory 20200056DR
6 · The paper itself

Abstract

Quantum chemistry is interested in calculating ground and excited states of molecular systems by solving the electronic Schrödinger equation. The exact numerical solution of this equation, frequently represented as an eigenvalue problem, remains unfeasible for most molecules and requires approximate methods. In this paper we introduce the use of Quantum Community Detection performed using the D-Wave quantum annealer to reduce the molecular Hamiltonian matrix in Slater determinant basis without chemical knowledge. Given a molecule represented by a matrix of Slater determinants, the connectivity between Slater determinants (as off-diagonal elements) is viewed as a graph adjacency matrix for determining multiple communities based on modularity maximization. A gauge metric based on perturbation theory is used to determine the lowest energy cluster. This cluster or sub-matrix of Slater determinants is used to calculate approximate ground state and excited state energies within chemical accuracy. The details of this method are described along with demonstrating its performance across multiple molecules of interest and bond dissociation cases. These examples provide proof-of-principle results for approximate solution of the electronic structure problem using quantum computing. This approach is general and shows potential to reduce the computational complexity of post-Hartree-Fock methods as future advances in quantum hardware become available.

Identifiers

PMID33602988
PMCPMC7892829
OpenAlexW3129326732

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.