{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/design-and-simulation-of-the-adaptive","title":"Design and Simulation of the Adaptive Continuous Entanglement Generation Protocol","arxiv_id":"2502.01964","date":"2025-02-04","proceeding":null,"authors":["Caitao Zhan","Joaquin Chung","Allen Zang","Alexander Kolar","Rajkumar Kettimuthu"],"abstract":"Generating and distributing remote entangled pairs (EPs) is a primary function of quantum networks, as entanglement is the fundamental resource for key quantum network applications. A critical performance metric for quantum networks is the time-to-serve (TTS) for users' EP requests, which is the time to distribute EPs between the requested nodes. Minimizing the TTS is essential given the limited qubit coherence time. In this paper, we study the Adaptive Continuous entanglement generation Protocol (ACP), which enables quantum network nodes to continuously generate EPs with their neighbors, while adaptively selecting the neighbors to optimize TTS. Meanwhile, entanglement purification is used to mitigate decoherence in pre-generated EPs prior to the arrival of user requests. We extend the SeQUeNCe simulator to fully implement ACP and conduct extensive simulations across various network scales. Our results show that ACP reduces TTS by up to 94% and increases entanglement fidelity by up to 0.05.","url_abs":"https://arxiv.org/abs/2502.01964v2","url_pdf":"https://arxiv.org/pdf/2502.01964v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"design-and-simulation-of-the-adaptive","repo_url":"https://github.com/caitaozhan/adaptive-continuous","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}