Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing

Quantum Physics arXiv:2511.15981 (quant-ph) [Submitted on 20 Nov 2025] Title:Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing Authors:Jingcheng Dai, Atharva Vidwans, Eric H. Wan, Alexander X. Miller, Micheline B. Soley View a PDF of the paper titled Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing, by Jingcheng Dai and 4 other authors View PDF HTML (experimental) Abstract:Recent advancements in quantum algorithms have reached a state where we can consider how to capitalize on quantum and classical computational resources to accelerate molecular resonance state identification. Here we identify molecular resonances with a method that combines quantum computing with classical high-throughput computing (HTC). This algorithm, which we term qDRIVE (the quantum deflation resonance identification variational eigensolver) exploits the complex absorbing potential formalism to distill the problem of molecular resonance identification into a network of hybrid quantum-classical variational quantum eigensolver tasks, and harnesses HTC resources to execute these interconnected but independent tasks both asynchronously and in parallel, a strategy that minimizes wall time to completion. We show qDRIVE successfully identifies resonance energies and wavefunctions in simulated quantum processors with current and planned specifications, which bodes well for qDRIVE's ultimate application in disciplines ranging from photocatalysis to quantum control and places a spotlight on the potential offered by integrated heterogenous quantum computing/HTC approaches in computational chemistry. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2511.15981 [quant-ph] (or arXiv:2511.15981v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2511.15981 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Micheline Soley [view email] [v1] Thu, 20 Nov 2025 02:28:05 UTC (3,459 KB) Full-text links: Access Paper: View a PDF of the paper titled Molecular resonance identification in complex absorbing potentials via integrated quantum computing and high-throughput computing, by Jingcheng Dai and 4 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2025-11 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?)