{"id":18522815,"url":"https://github.com/xanaduai/torontonian-sampling","last_synced_at":"2026-02-17T02:33:54.678Z","repository":{"id":95921035,"uuid":"150538030","full_name":"XanaduAI/torontonian-sampling","owner":"XanaduAI","description":" This repository contains the source code used to produce the results presented in the paper \"Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer\".","archived":false,"fork":false,"pushed_at":"2019-03-26T16:17:33.000Z","size":27,"stargazers_count":10,"open_issues_count":0,"forks_count":10,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-06-10T08:39:53.387Z","etag":null,"topics":["algorithm","graphs","graphs-theory","matrix","optimization","optimization-algorithms","physics","quantum","quantum-computing"],"latest_commit_sha":null,"homepage":"https://arxiv.org/abs/1810.00900","language":"Fortran","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/XanaduAI.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2018-09-27T06:17:48.000Z","updated_at":"2025-02-06T14:42:23.000Z","dependencies_parsed_at":"2023-03-13T16:41:40.156Z","dependency_job_id":null,"html_url":"https://github.com/XanaduAI/torontonian-sampling","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/XanaduAI/torontonian-sampling","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/XanaduAI%2Ftorontonian-sampling","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/XanaduAI%2Ftorontonian-sampling/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/XanaduAI%2Ftorontonian-sampling/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/XanaduAI%2Ftorontonian-sampling/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/XanaduAI","download_url":"https://codeload.github.com/XanaduAI/torontonian-sampling/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/XanaduAI%2Ftorontonian-sampling/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279016594,"owners_count":26085852,"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":"2025-10-13T02:00:06.723Z","response_time":61,"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":["algorithm","graphs","graphs-theory","matrix","optimization","optimization-algorithms","physics","quantum","quantum-computing"],"created_at":"2024-11-06T17:33:11.003Z","updated_at":"2025-10-13T18:33:50.254Z","avatar_url":"https://github.com/XanaduAI.png","language":"Fortran","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Torontonian Sampling\n\nThis repository contains the source code used to produce the results presented in *\"Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer\"* [arXiv:1810.00900](https://arxiv.org/abs/1810.00900).\n\n## Contents\n\nThis repository contains:\n\n* Fortran source code in the directory `src` which calculates samples from the Torontonian, given a Gaussian state vector of means and covariance matrix.\n* This Fortran source code can also be interfaced with Python\n* Two examples on how to use the Torontonian sampling module. A Fortran example in the `examples` folder, and an interactive Python Jupyter notebook `TorontonianSampling.ipynb`.\n\n## Installation\n\nThe Torontonian sampling Fortran module can be used either via Fortran, or via the Python interface.\n\n### Interfacing via Fortran\n\nIf using the module via Fortran, no external dependencies are required, just a Fortran compiler like `gfortran`. On Ubuntu based systems, this can be installed via apt:\n```bash\nsudo apt install gfortran\n```\nThen, simply run\n```bash\nmake fortran\n```\nin the top level directory. The Fortran modules will be compiled, and the modules stored in the directory `include`. To use the module with your own Fortran, simply include the `use torontonian_samples` at the top of the program, and compile the commands\n```bash\ngfortran -o program program.f90  /path/to/include/*.o -I/path/to/include/\n```\n\nSee the file `examples/fortran_example.f90` for an example program that uses the Torontonian sampling module. This can be compiled by running `make example` from the top level directory.\n\n### Interfacing via Python\n\nTo compile the module for use with Python, `NumPy` is required to be installed, as well as a Fortran compiler such as `gfortran`.\n`NumPy` can be installed via `pip`:\n```bash\npip install numpy\n```\nThen, simply run\n```bash\nmake python\n```\nin the top level directory to compile the Python module. The module `torontonian_samples.cpython-*-.so` will be created, which can then be imported in Python via `import torontonian_samples`.\n\n## Authors\n\nBrajesh Gupt.\n\nIf you are doing any research using this source code, please cite the following paper:\n\n\u003e Brajesh Gupt, Juan Miguel Arrazola, Nicolas Quesada, and Thomas R. Bromley.  Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer, [arXiv:1810.00900](https://arxiv.org/abs/1810.00900)\n\n## License\n\nThis source code is free and open source, released under the Apache License, Version 2.0.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxanaduai%2Ftorontonian-sampling","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxanaduai%2Ftorontonian-sampling","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxanaduai%2Ftorontonian-sampling/lists"}