STI Publications - View Publication Form #21764
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Publication Information
Title | Solving the homogeneous Bethe-Salpeter equation with a quantum annealer | ||||
Abstract | The homogeneous Bethe-Salpeter equation (hBSE), describing a bound system in a genuinely relativistic quantum-field theory framework, was solved for the first time by using a D-Wave quantum annealer. After applying standard techniques of discretization, the hBSE, in ladder approximation, can be formally transformed in a generalized eigenvalue problem (GEVP), with two square matrices: one symmetric and the other non symmetric. The latter matrix poses the challenge of obtaining a suitable formal approach for investigating the non symmetric GEVP by means of a quantum annealer, i.e to recast it as a quadratic unconstrained binary optimization problem. A broad numerical analysis of the proposed algorithms, applied to matrices of dimension up to 64, was carried out by using both the proprietary simulated-anneaing package and the D-Wave Advantage 4.1 system. The numerical results very nicely compare with those obtained with standard classical algorithms, and also show interesting scalability | ||||
Author(s) | Filippo Fornetti, Alex Gnech, Francesco Pederiva, Matteo Rinaldi, Alessandro Roggero, Giovanni Salme', Sergio Scopetta, Michele Viviani | ||||
Publication Date | September 2024 | ||||
Document Type | Journal Article | ||||
Primary Institution | Old Dominion University | ||||
Affiliation | Theory & Comp Physics / THEORY CENTER / THEORY CENTER | ||||
Funding Source | Nuclear Physics (NP) | ||||
Proprietary? | No | ||||
This publication conveys | Technical Science Results | ||||
Document Numbers |
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Associated with an experiment | No | ||||
Associated with EIC | No | ||||
Supported by Jefferson Lab LDRD Funding | No |
Journal Article
Journal Name | Physical Review D |
Refereed | No |
Volume | 110 |
Issue | |
Page(s) | 056012 |
Attachments/Datasets/DOI Link
Document(s) |
QA_gevp1.pdf
(STI Document)
PhysRevD.110.056012.pdf
(Accepted Manuscript)
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DOI Link | |
Dataset(s) | (none) |
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