Recent Developments in VQE: Survey and Benchmarking
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Quantum Physics arXiv:2602.11384 (quant-ph) [Submitted on 11 Feb 2026] Title:Recent Developments in VQE: Survey and Benchmarking Authors:Taylor Harville, Rishu Khurana, Vitor F. Grizzi, Cong Liu View a PDF of the paper titled Recent Developments in VQE: Survey and Benchmarking, by Taylor Harville and 3 other authors View PDF HTML (experimental) Abstract:The Variational Quantum Eigensolver (VQE) algorithm has been developed to target near term Noisy Intermediate Scale Quantum (NISQ) computers as a method to find the eigenvalues of Hamiltonians. Unlike fully quantum algorithms such as Quantum Phase Estimation (QPE), VQE based methods are hybrid algorithms that utilize both quantum and classical hardware to combat issues with the near term quantum hardware such as small numbers of available qubits and the decoherence of qubits. Different adaptations (flavors) of VQE have been implemented to combat these scalability issues on NISQ devices compared to standard VQE. These different flavors are modifications of the underlying VQE ansatz to reduce the computational workload on the quantum hardware. In this review we focus on 3 main areas related to VQE. The first focus is on flavors of VQE that fall under the categories of circuit complexity reduction, chemistry inspired ansatz, and extensions of VQE to excited states. The remaining portion of the review focuses on benchmarking the accuracy of VQE methods and an overview of the current state of quantum simulators. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2602.11384 [quant-ph] (or arXiv:2602.11384v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2602.11384 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Taylor Harville [view email] [v1] Wed, 11 Feb 2026 21:24:32 UTC (2,272 KB) Full-text links: Access Paper: View a PDF of the paper titled Recent Developments in VQE: Survey and Benchmarking, by Taylor Harville and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-02 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) Links to Code Toggle Papers with Code (What is Papers with Code?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)