svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm

[2605.07559] svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Quantum Physics arXiv:2605.07559 (quant-ph) [Submitted on 8 May 2026 ( v1 ), last revised 15 Sep 2026 (this version, v4)] Title: svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm Authors: Pascal Sievers , Satoshi Ejima View a PDF of the paper titled svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm, by Pascal Sievers and Satoshi Ejima View PDF HTML (experimental) Abstract: We present a Python package for ground-state preparation based on the probabilistic imaginary-time evolution algorithm, with particular focus on its state-vector-based implementation. A standard shot-based simulation is also supported, and results can be benchmarked against exact diagonalisation via a dedicated wrapper. The package enables efficient tuning of initial parameters, facilitating systematic exploration and optimisation of the method's performance. Starting from the prepared ground state, the strong interoperability with other packages further enables real-time evolution and the computation of spectral functions, such as the spin-spin dynamical structure factor. Comments: 35 pages, 11 figures, final version. Package available at this https URL Subjects: Quantum Physics (quant-ph) ; Strongly Correlated Electrons (cond-mat.str-el) Cite as: arXiv:2605.07559 [quant-ph] (or arXiv:2605.07559v4 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2605.07559 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Pascal Sievers [ view email ] [v1] Fri, 8 May 2026 10:34:02 UTC (1,928 KB) [v2] Mon, 18 May 2026 17:36:58 UTC (1,928 KB) [v3] Sat, 15 Aug 2026 11:11:27 UTC (2,181 KB) [v4] Tue, 15 Sep 2026 13:39:03 UTC (2,181 KB) Full-text links: Access Paper: View a PDF of the paper titled svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm, by Pascal Sievers and Satoshi Ejima View PDF HTML (experimental) TeX Source view license Current browse context: quant-ph < prev | next > new | recent | 2026-05 Change to browse by: cond-mat cond-mat.str-el References & Citations INSPIRE HEP NASA ADS Google 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? ) 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? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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