{"id":22753980,"url":"https://github.com/slaclab/neural-representation-sqw","last_synced_at":"2025-04-14T15:34:11.697Z","repository":{"id":164176233,"uuid":"542195449","full_name":"slaclab/neural-representation-sqw","owner":"slaclab","description":"Inelastic neutron scattering parameter estimation using implicit neural representations and automatic differentiation. ","archived":false,"fork":false,"pushed_at":"2023-12-01T15:20:48.000Z","size":41691,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":8,"default_branch":"main","last_synced_at":"2025-03-28T04:25:40.331Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/slaclab.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}},"created_at":"2022-09-27T16:56:50.000Z","updated_at":"2024-07-31T06:22:30.000Z","dependencies_parsed_at":"2023-12-01T16:43:10.331Z","dependency_job_id":null,"html_url":"https://github.com/slaclab/neural-representation-sqw","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slaclab%2Fneural-representation-sqw","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slaclab%2Fneural-representation-sqw/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slaclab%2Fneural-representation-sqw/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slaclab%2Fneural-representation-sqw/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/slaclab","download_url":"https://codeload.github.com/slaclab/neural-representation-sqw/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248906439,"owners_count":21181177,"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":[],"created_at":"2024-12-11T06:15:06.270Z","updated_at":"2025-04-14T15:34:11.676Z","avatar_url":"https://github.com/slaclab.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Capturing dynamical correlations using implicit neural representations\n\n\u003cimg width=\"1368\" alt=\"Screen Shot 2023-03-21 at 11 15 28 PM\" src=\"https://user-images.githubusercontent.com/39596225/226817874-f7c4009e-f892-4563-afff-4a8265b3639a.png\"\u003e\n\n---\n\n## Installation\n\n1) Make a new local folder and clone the repository\n\n```\ngit clone https://github.com/src47/neural-representation-sqw.git\n```\n\n2) Install requirements\n\n```\npip install -r requirements.txt\n```\n\n3) Make sure this repo directory is on the PYTHONPATH:\n\n```bash\n$ source shell/add_pwd_to_pythonpath.sh\n```\n\n## Directory Structure \n\n**data_experimental** \n\nThis directory contains experiment S(q,w) measurements for both paths reported in the manuscript (with and without background subtraction). It also contains the accompanying energy and momentum coordinates.\n\n**data_simulation_2023** \n\nDue to the size of the simulation dataset, it is not possible to inclue it directly on GitHub. Please download the simulation data which is publicly available at https://doi.org/10.5281/zenodo.7804447.\n\n**notebooks** \n\n1) test_experimental_data.ipynb: contains code neccesary to optimize the surrogate implict neural model to fit experimental inelastic scattering data.  \n\n2) test_low_counts.ipynb: contains code neccesary to fit experimental data as a function of count rate.\n\n**models/siren** \n\nThis directory contains a trained SIREN model which acts as a differentiable surrogate for linear spin wave simulations. \n\n## Training Model\n\nTo train the SIREN model on simulated excitations from a square lattice, please run:\n```bash\n$ python3 src/model_training.py --data_path data_simulation_2023/neural_dataset.npz\n```\n\n## Citation\n\nIf you found this repository useful in your research, please cite:\n\n```bash\n@article{chitturi2023capturing,\n  title={Capturing dynamical correlations using implicit neural representations},\n  author={Chitturi, Sathya R and Ji, Zhurun and Petsch, Alexander N and Peng, Cheng and Chen, Zhantao and Plumley, Rajan and Dunne, Mike and Mardanya, Sougata and Chowdhury, Sugata and Chen, Hongwei and others},\n  journal={Nature Communications},\n  volume={14},\n  number={1},\n  pages={5852},\n  year={2023},\n  publisher={Nature Publishing Group UK London}\n}\n```\n**Please direct any questions or comments to chitturi@stanford.edu, zhurun@stanford.edu, apetsch@stanford.edu, joshuat@slac.stanford.edu. \n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslaclab%2Fneural-representation-sqw","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fslaclab%2Fneural-representation-sqw","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslaclab%2Fneural-representation-sqw/lists"}