We present a real-time, interactive visualization platform for quantum mechanical tunneling that achieves unprecedented computational performance through definitive computing methods. Using the Neural-Matrix Synaptic Resonance Network (NM-SRN v2.0 AGI QSC) architecture, we demonstrate O(1) constant-time calculation of tunneling probabilities independent of particle count, enabling visualization of 500,000 particles at interactive frame rates with 128-bit precision. The system maintains zero numerical drift through continuous mathematical integrity verification, providing both rigorous quantum mechanical accuracy and intuitive educational accessibility. We validate our results against analytical Wentzel-Kramers-Brillouin (WKB) approximation solutions, achieving agreement to four significant figures. This work establishes a new paradigm for computational physics visualization where real-time interactivity does not compromise mathematical rigor.
\nKeywords: Quantum tunneling, real-time visualization, definitive computing, computational physics, quantum mechanics education, GPU acceleration
", "publication_date": "2026-02-14", "publisher": "Zenodo", "related_identifiers": [ { "identifier": "10.5281/zenodo.15169311", "relation_type": { "id": "issupplementto", "title": { "de": "Erg\u00e4nzt", "en": "Is supplement to" } }, "resource_type": { "id": "publication-workingpaper", "title": { "de": "Arbeitspapier", "en": "Working paper" } }, "scheme": "doi" }, { "identifier": "10.5281/zenodo.15645648", "relation_type": { "id": "issupplementto", "title": { "de": "Erg\u00e4nzt", "en": "Is supplement to" } }, "resource_type": { "id": "publication-workingpaper", "title": { "de": "Arbeitspapier", "en": "Working paper" } }, "scheme": "doi" }, { "identifier": "10.5281/zenodo.15686190", "relation_type": { "id": "issupplementto", "title": { "de": "Erg\u00e4nzt", "en": "Is supplement to" } }, "resource_type": { "id": "publication-workingpaper", "title": { "de": "Arbeitspapier", "en": "Working paper" } }, "scheme": "doi" }, { "identifier": "10.5281/zenodo.18357930", "relation_type": { "id": "issupplementto", "title": { "de": "Erg\u00e4nzt", "en": "Is supplement to" } }, "resource_type": { "id": "publication-workingpaper", "title": { "de": "Arbeitspapier", "en": "Working paper" } }, "scheme": "doi" } ], "resource_type": { "id": "publication-workingpaper", "title": { "de": "Arbeitspapier", "en": "Working paper" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "subjects": [ { "id": "euroscivoc:297", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/4c8f4b46-6f5c-41d9-9079-7de85c16431d", "scheme": "url" } ], "props": { "parents": "euroscivoc:23,euroscivoc:47" }, "scheme": "EuroSciVoc", "subject": "Artificial intelligence" }, { "id": "mesh:D001185", "scheme": "MeSH", "subject": "Artificial Intelligence" }, { "id": "mesh:D001185Q000592", "scheme": "MeSH", "subject": "Artificial Intelligence/standards" }, { "id": "mesh:D001185Q000266", "scheme": "MeSH", "subject": "Artificial Intelligence/history" }, { "id": "euroscivoc:933", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/527ab165-56f2-4020-8975-e7cd3f21d01d", "scheme": "url" } ], "props": { "parents": "euroscivoc:23,euroscivoc:47,euroscivoc:297" }, "scheme": "EuroSciVoc", "subject": "Machine learning" }, { "id": "mesh:D000069550", "scheme": "MeSH", "subject": "Machine Learning" }, { "id": "mesh:D000069550Q000266", "scheme": "MeSH", "subject": "Machine Learning/history" }, { "id": "mesh:D000069558", "scheme": "MeSH", "subject": "Unsupervised Machine Learning" }, { "id": "mesh:D000069550Q000145", "scheme": "MeSH", "subject": "Machine Learning/classification" }, { "id": "mesh:D000069550Q000592", "scheme": "MeSH", "subject": "Machine Learning/standards" }, { "id": "euroscivoc:1207", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/1de32ce8-df3d-4ba6-b298-eb425e87c67b", "scheme": "url" } ], "props": { "parents": "euroscivoc:25,euroscivoc:73,euroscivoc:453,euroscivoc:449" }, "scheme": "EuroSciVoc", "subject": "Quantum computers" }, { "id": "euroscivoc:793", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/bfd5c444-49dd-4da9-9ad8-d242f724f036", "scheme": "url" } ], "props": { "parents": "euroscivoc:23,euroscivoc:43" }, "scheme": "EuroSciVoc", "subject": "Quantum physics" }, { "id": "mesh:D011789", "scheme": "MeSH", "subject": "Quantum Theory" }, { "id": "gemet:concept/6235", "identifiers": [ { "identifier": "http://www.eionet.europa.eu/gemet/concept/6235", "scheme": "url" } ], "props": { "groups": [ "http://www.eionet.europa.eu/gemet/group/7136" ], "parents": "gemet:concept/7472,gemet:concept/6230", "themes": [ "http://www.eionet.europa.eu/gemet/theme/25", "http://www.eionet.europa.eu/gemet/theme/30" ] }, "scheme": "GEMET", "subject": "Physics" }, { "id": "mesh:D010825", "scheme": "MeSH", "subject": "Physics" }, { "id": "euroscivoc:1053", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/2ba1c7ad-2532-4cd7-8c5c-60f090a8700a", "scheme": "url" } ], "props": { "parents": "euroscivoc:23,euroscivoc:51,euroscivoc:355" }, "scheme": "EuroSciVoc", "subject": "Mathematical physics" }, { "id": "euroscivoc:745", "identifiers": [ { "identifier": "http://data.europa.eu/8mn/euroscivoc/e39eb923-d810-425b-a740-954a93eaf8d9", "scheme": "url" } ], "props": { "parents": "euroscivoc:23,euroscivoc:43,euroscivoc:251" }, "scheme": "EuroSciVoc", "subject": "Laser physics" }, { "id": "mesh:D010825Q000295", "scheme": "MeSH", "subject": "Physics/instrumentation" }, { "id": "mesh:D010825Q000379", "scheme": "MeSH", "subject": "Physics/methods" }, { "id": "mesh:D010825Q000592", "scheme": "MeSH", "subject": "Physics/standards" } ], "title": "Real-Time Interactive Visualization of Quantum Tunneling: A Definitive Computational Approach" }, "parent": { "access": { "owned_by": { "user": "1046579" }, "settings": { "accept_conditions_text": null, "allow_guest_requests": false, "allow_user_requests": false, "secret_link_expiration": 0 } }, "communities": {}, "id": "18644042", "pids": { "doi": { "client": "datacite", "identifier": "10.5281/zenodo.18644042", "provider": "datacite" } } }, "pids": { "doi": { "client": "datacite", "identifier": "10.5281/zenodo.18644373", "provider": "datacite" }, "oai": { "identifier": "oai:zenodo.org:18644373", "provider": "oai" } }, "revision_id": 4, "stats": { "all_versions": { "data_volume": 1299660817.0, "downloads": 197, "unique_downloads": 176, "unique_views": 112, "views": 128 }, "this_version": { "data_volume": 1297491199.0, "downloads": 174, "unique_downloads": 161, "unique_views": 82, "views": 91 } }, "status": "published", "swh": {}, "updated": "2026-02-14T20:46:26.433779+00:00", "versions": { "index": 2, "is_latest": true } }