{"id":17263141,"url":"https://github.com/caitaozhan/quantumlocalization","last_synced_at":"2025-04-14T07:33:54.872Z","repository":{"id":63931563,"uuid":"524201713","full_name":"caitaozhan/QuantumLocalization","owner":"caitaozhan","description":"Quantum Sensor Network Algorithms for Transmitter Localization","archived":false,"fork":false,"pushed_at":"2023-11-02T14:27:19.000Z","size":12641,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-27T21:11:09.597Z","etag":null,"topics":["localization","quantum","quantum-sensing","transmitter"],"latest_commit_sha":null,"homepage":"https://arxiv.org/abs/2211.02260","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/caitaozhan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2022-08-12T19:24:11.000Z","updated_at":"2023-10-20T02:07:57.000Z","dependencies_parsed_at":"2023-02-09T22:50:16.676Z","dependency_job_id":"966b11fe-0708-4c3d-8124-96ba5bbc30c8","html_url":"https://github.com/caitaozhan/QuantumLocalization","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caitaozhan%2FQuantumLocalization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caitaozhan%2FQuantumLocalization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caitaozhan%2FQuantumLocalization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/caitaozhan%2FQuantumLocalization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/caitaozhan","download_url":"https://codeload.github.com/caitaozhan/QuantumLocalization/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248839725,"owners_count":21169857,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["localization","quantum","quantum-sensing","transmitter"],"created_at":"2024-10-15T07:55:44.949Z","updated_at":"2025-04-14T07:33:54.815Z","avatar_url":"https://github.com/caitaozhan.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Quantum Sensor Network Algorithms for Transmitter Localization\n\nA quantum sensor (QS) is able to measure various physical phenomena with extreme sensitivity. QSs have been used in several applications such as atomic interferometers, but few applications of a quantum sensor network (QSN) have been proposed or developed. We look at a natural application of QSN -- localization of an event (in particular, of a wireless signal transmitter). In this paper, we develop effective quantum-based techniques for the localization of a transmitter using a QSN. Our approaches pose the localization problem as a well-studied quantum state discrimination (QSD) problem and address the challenges in its application to the localization problem. In particular, a quantum state discrimination solution can suffer from a high probability of error, especially when the number of states (i.e., the number of potential transmitter locations in our case) can be high. We address this challenge by developing a two-level localization approach, which localizes the transmitter at a coarser granularity in the first level, and then, in a finer granularity in the second level. We address the additional challenge of the impracticality of general measurements by developing new schemes that replace the QSD's measurement operator with a trained parameterized hybrid quantum-classical circuit. Our evaluation results using a custom-built simulator show that our best scheme is able to achieve meter-level (1-5m) localization accuracy; in the case of discrete locations, it achieves near-perfect (99-100\\%) classification accuracy.\n\nPaper: https://arxiv.org/abs/2211.02260\n\nIEEE QCE 2023 Presentation: [YouTube](https://www.youtube.com/watch?v=Mq49DCdVdIs)\n```\n@misc{zhan2023optimizing,\n      title={Optimizing Initial State of Detector Sensors in Quantum Sensor Networks}, \n      author={Caitao Zhan and Himanshu Gupta and Mark Hillery},\n      year={2023},\n      eprint={2306.17401},\n      archivePrefix={arXiv},\n      primaryClass={quant-ph}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaitaozhan%2Fquantumlocalization","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcaitaozhan%2Fquantumlocalization","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcaitaozhan%2Fquantumlocalization/lists"}