Sparse-QITE: Discovering Compact Generators for Quantum Imaginary-Time Evolution via Regularization Methods

Quantum Physics arXiv:2610.20791 (quant-ph) [Submitted on 14 Oct 2026] Title:Sparse-QITE: Discovering Compact Generators for Quantum Imaginary-Time Evolution via Regularization Methods Authors:Rafael Gómez-Lurbe, Luca Ion, Alberto Acevedo, Andreu Anglés-Castillo View a PDF of the paper titled Sparse-QITE: Discovering Compact Generators for Quantum Imaginary-Time Evolution via Regularization Methods, by Rafael G\'omez-Lurbe and 2 other authors View PDF HTML (experimental) Abstract:Quantum imaginary-time evolution (QITE) provides a systematic route to ground-state preparation, but its cost grows rapidly with the locality $D$ of the unitary approximation, for which the local Pauli basis scales as $4^D$. We introduce Sparse-QITE, a regularized formulation that promotes compact generators, reducing the number of quantum operations and yielding circuits with fewer gates and lower depth. We derive rigorous bounds on the sparsification error and benchmark the method in one-dimensional transverse-field Ising and antiferromagnetic Heisenberg models. Sparse-QITE exhibits a controllable sparsity--accuracy trade-off while retaining strong compression even in the high-accuracy regime. In scalability experiments with respect to $D$, the active support grows much more slowly than in standard QITE and, in several regimes, approximately saturates over the domain sizes studied. After circuit construction and transpilation, some of the largest-domain cases require only about $1\%$ of the standard-QITE gate count while maintaining high accuracy. We further introduce adaptive and active-discovery variants: the former selects the regularization strength dynamically during the evolution, while the latter reduces the number of Pauli expectation values that need to be evaluated and, consequently, the measurement requirements. These results establish sparsity-promoting regularization as a route toward more resource-efficient QITE. More broadly, these results suggest that sparsity-promoting regularization may also benefit variational quantum algorithms. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2610.20791 [quant-ph] (or arXiv:2610.20791v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2610.20791 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Rafael Gomez Lurbe [view email] [v1] Wed, 14 Oct 2026 18:32:43 UTC (494 KB) Full-text links: Access Paper: View a PDF of the paper titled Sparse-QITE: Discovering Compact Generators for Quantum Imaginary-Time Evolution via Regularization Methods, by Rafael G\'omez-Lurbe and 2 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-10 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?) 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?)