{"id":17312523,"url":"https://github.com/emilianog-byte/opentn","last_synced_at":"2025-09-01T04:33:54.979Z","repository":{"id":155655179,"uuid":"586583948","full_name":"EmilianoG-byte/opentn","owner":"EmilianoG-byte","description":"Code for my master thesis at the Scientific Computing chair @ TUM under the supervision of Prof. Christian Mendl","archived":false,"fork":false,"pushed_at":"2024-08-04T19:42:40.000Z","size":37741,"stargazers_count":4,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-14T14:59:02.082Z","etag":null,"topics":["automatic-differentiation","open-quantum-systems","riemannian-optimization","tensor-networks"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/EmilianoG-byte.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-01-08T16:44:42.000Z","updated_at":"2024-11-28T05:09:16.000Z","dependencies_parsed_at":"2025-04-14T14:55:59.082Z","dependency_job_id":null,"html_url":"https://github.com/EmilianoG-byte/opentn","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/EmilianoG-byte/opentn","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmilianoG-byte%2Fopentn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmilianoG-byte%2Fopentn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmilianoG-byte%2Fopentn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmilianoG-byte%2Fopentn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EmilianoG-byte","download_url":"https://codeload.github.com/EmilianoG-byte/opentn/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmilianoG-byte%2Fopentn/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273073387,"owners_count":25040714,"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","status":"online","status_checked_at":"2025-09-01T02:00:09.058Z","response_time":120,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["automatic-differentiation","open-quantum-systems","riemannian-optimization","tensor-networks"],"created_at":"2024-10-15T12:43:46.897Z","updated_at":"2025-09-01T04:33:54.947Z","avatar_url":"https://github.com/EmilianoG-byte.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# OpenTN [WIP]\n\n\u003cdiv align=\"center\"\u003e\n\n\u003cpicture\u003e\n  \u003csource media=\"(prefers-color-scheme: dark)\" width=\"650\"\u003e\n  \u003cimg alt=\"openTN\" src=\"./images/OpenTN.png\" width=\"650\"\u003e\n\u003c/picture\u003e\n\n\u003c/div\u003e\n\nEmploying Locally Purified Density Operator (LPDO) tensor networks to study open quantum systems under non-local CPTP maps.\n\nDecreasing approximation errors from the trotterization of CPTP maps on the kraus dimensions. Using Riemannian optimization on Sitefel Manifold.\n\n\n\u003e **Methods**: Tensor Networks, Automatic Differentiation, Convex Optimization, Riemannian Optimization, Open Quantum Systems.\n\n\n## Structure\n\u003c!-- \u003e * `tests` includes the first unittests\n\u003e * `experiments` includes some notebook examples with important comparisons and traits such as purification with MPS\n\u003e * `opentn` package for the testing and comparison of open quantum systems using either circuits, channels or tensor networks\n\u003e   - `entanglement.py` implementation of peres criteria for entanglement\n\u003e   - `channels.py`  implementation of a quantum channel in krauss representation: $\\rho^{out} = \\mathcal{E}(\\rho) = \\sum_k = E_k \\rho E^\\dagger_k$\n\u003e   - `circuits.py`  implementation of a 2-qubit quantum circuit with gates corresponding to the krauss operators \n\u003e   - `tensors.py` currently it is a simple MPS-MPO TN where the MPO correspond to the gates in quantum circuit --\u003e\n\n``` bash\n├── experiments\n│   ├── *ipynb notebooks with experiments to verify the theory and numerics*\n├── opentn\n│   ├── states\n│   │   ├── __init__.py\n│   │   ├── qubits.py\n│   │   ├── qudits.py\n│   ├── __init__.py\n│   ├── channels.py\n│   ├── circuits.py\n│   ├── entanglement.py\n│   ├── optimization.py\n│   ├── stiefel.py\n│   ├── transformations.py\n│   ├── trust_region_rcopt.py\n├── tests\n│   ├── test_optimization.py\n│   ├── test_transformations.py\n├── .gitignore\n└── README.md\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Femilianog-byte%2Fopentn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Femilianog-byte%2Fopentn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Femilianog-byte%2Fopentn/lists"}