Preserving fermionic statistics for single-particle approximations in microscopic quantum master equations

Quantum Physics arXiv:2511.02160 (quant-ph) [Submitted on 4 Nov 2025] Title:Preserving fermionic statistics for single-particle approximations in microscopic quantum master equations Authors:Mikayla Z. Fahrenbruch, Anthony W. Schlimgen, Kade Head-Marsden View a PDF of the paper titled Preserving fermionic statistics for single-particle approximations in microscopic quantum master equations, by Mikayla Z. Fahrenbruch and 2 other authors View PDF HTML (experimental) Abstract:Microscopic master equations have gained traction for the dissipative treatment of molecular spin and solid-state systems for quantum technologies. Single particle approximations are often invoked to treat these systems, which can lead to unphysical evolution when combined with master equation approaches. We present a mathematical constraint on the system-environment parameters to ensure that microscopically-derived Markovian master equations preserve fermionic, $N$-representable statistics when applied to reduced systems. We demonstrate these constraints for the recently derived unified master equation and universal Lindblad equation, along with the Redfield master equation for cases when positivity issues are not present. For operators that break the constraint, we explore the addition of Pauli factors to recover $N$-representability. This work promotes feasible applications of novel microscopic master equations for realistic chemical systems. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2511.02160 [quant-ph] (or arXiv:2511.02160v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2511.02160 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Kade Head-Marsden [view email] [v1] Tue, 4 Nov 2025 01:00:17 UTC (1,021 KB) Full-text links: Access Paper: View a PDF of the paper titled Preserving fermionic statistics for single-particle approximations in microscopic quantum master equations, by Mikayla Z. Fahrenbruch and 2 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?)