Optimizing the dynamical preparation of quantum spin lakes on the ruby lattice

[2512.09040] Optimizing the dynamical preparation of quantum spin lakes on the ruby lattice Skip to main content Search Submit Donate Log in Quantum Physics arXiv:2512.09040 (quant-ph) [Submitted on 9 Dec 2025 ( v1 ), last revised 25 Aug 2026 (this version, v2)] Title: Optimizing the dynamical preparation of quantum spin lakes on the ruby lattice Authors: DinhDuy Vu , Dominik S. Kufel , Jack Kemp , Lode Pollet , Chris R. Laumann , Norman Y. Yao View PDF HTML (experimental) Abstract: Quantum spin liquids are elusive long-range entangled states. Motivated by experiments in Rydberg quantum simulators, recent excitement has centered on the possibility of dynamically preparing a state with quantum spin liquid correlation even when the ground state phase diagram does not exhibit such a topological phase. Understanding the microscopic nature of such quantum spin "lake" states and their relationship to equilibrium spin liquid order remains an essential question. Here, we extend the use of approximately symmetric neural quantum states for real-time evolution and directly simulate the dynamical preparation in systems of up to $N=384$ atoms. We analyze a variety of spin liquid diagnostics as a function of the preparation protocol and optimize the extent of the quantum spin lake thus obtained. In the optimal case, the prepared state shows spin-liquid properties extending over half the system size, with a topological entanglement entropy plateauing close to $\gamma = \ln 2$. We extract two physical length scales $\lambda$ and $\xi$ which constrain the extent of the quantum spin lake $\ell$ from above and below. Subjects: Quantum Physics (quant-ph) ; Disordered Systems and Neural Networks (cond-mat.dis-nn) Cite as: arXiv:2512.09040 [quant-ph] (or arXiv:2512.09040v2 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2512.09040 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Physical Review Letters 137, 093402 (2026) Related DOI : https://doi.org/10.1103/7dnl-6kg2 Focus to learn more DOI(s) linking to related resources Submission history From: DinhDuy Vu [ view email ] [v1] Tue, 9 Dec 2025 19:00:12 UTC (897 KB) [v2] Tue, 25 Aug 2026 05:19:18 UTC (885 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: quant-ph < prev | next > new | recent | 2025-12 Change to browse by: cond-mat cond-mat.dis-nn References & Citations INSPIRE HEP SciX Google Scholar Semantic Scholar export BibTeX citation 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)

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