{"url":"/dataset/january-2-2024-v1-software-open-software-and","name":"January 2, 2024 (v1) Software Open Software and DataSet of \"A QA-SQP assisted FE for non-linear and history-dependent mechanics\"","full_name":null,"description_markdown":"Click to #Development of QA-SQP for non-linear and history-dependent mechanical problems\r\n\r\nThis directory contains the source code and numerical benchmarks published in [^1]\r\n\r\n## Dependencies and Prerequisites\r\n\r\n* Python, pandas, numpy, matplotlib are pre requisites.\r\n* For generating mesh and for vizualization, gmsh ([www.gmsh.info](www.gmsh.info)) is required.\r\n* Dwave Ocean Tools ([https://docs.ocean.dwavesys.com/en/stable/getting_started.html](https://docs.ocean.dwavesys.com/en/stable/getting_started.html))\r\n\r\n## Structure of Repository\r\n\r\n* [src](./src): Python source code\r\n* [examples](./examples): Some finite element tests \r\n* [paper](./paper): Python codes of the benchmarks in the paper [^1]\r\n\r\n## Run an analysis\r\n\r\nFor example, the example [examples/J2-SA](./examples/J2-SA) run a finite element simulation using Simulated Annealing\r\n``` bash\r\n python3 run.py\r\n```\r\n\r\n## Reproduce paper[^1] results and figures\r\n\r\n* The tests require access to the annealer. \r\n    * Token needs to be provided in sampler = EmbeddingComposite(DWaveSampler(connection_close=True)) -> sampler = EmbeddingComposite(DWaveSampler(token=\"\",connection_close=True))\r\n* To use the Simulated Annealing instead, one has to replace the three lines\r\n    * sampler = EmbeddingComposite(DWaveSampler(connection_close=True))\r\n    * SA = lambda J: sampler.sample_qubo(J, num_reads=100,label=\"twoDTest\")\r\n    * quboOptFunc = lambda J: QUBO.qubo_solve_sampler(J,sampler)\r\n    * by\r\n    * SA = lambda J: SimulatedAnnealingSampler().sample_qubo(J,num_reads=100)\r\n    * quboOptFunc =lambda J: QUBO.qubo_solve_sampler(J,SA)\r\n\r\n* Figures 2, 3, and 4: in the folder [paper/QA-SQP/1D-elastic](./paper/QA-SQP/1D-elastic)\r\n    * Run tests: ```python3 run.py```\r\n    * Extract figures: ```python3 plotData.py```\r\n* Figures 5, 6, and 7: in the folder [paper/QA-SQP/1D-elastoplastic](./paper/QA-SQP/1D-elastoplastic)\r\n    * Run tests: ```python3 run.py```\r\n    * Extract figures: ```python3 plotData.py```\r\n      \r\n* Figures 9, 11, 12: in the folder [paper/QA-SQP/2D-elastoplastic](./paper/QA-SQP/2D-elastoplastic)\r\n    * Run classical finite element simulation: ``` python3 runFEM.py```\r\n    * Run tests: ```python3 run.py```\r\n    * Extract figures: ```python3 plotData.py```     \r\n\r\n## Reproduce paper[^1] figures only\r\n* Figures 2, 3, and 4: in the folder [paper/QA-SQP-results/1D-elastic](./paper/QA-SQP-results/1D-elastic)\r\n    * Extract figures: ```python3 plotData.py```\r\n* Figures 5, 6, and 7: in the folder [paper/QA-SQP-results/1D-elastoplastic](./paper/QA-SQP-results/1D-elastoplastic)\r\n    * Extract figures: ```python3 plotData.py```\r\n      \r\n* Figures 9, 11, 12: in the folder [paper/QA-SQP-results/2D-elastoplastic](./paper/QA-SQP-results/2D-elastoplastic)\r\n    * Extract figures: ```python3 plotData.py```     \r\n\r\n \r\n\r\n[^1]: The work is described in:  \r\n\"_Nguyen V.-D., Wu L., Remacle F. and Noels L. (2024)._ A quantum annealing-sequential quadratic programming assisted finite element simulation for non-linear and history-dependent mechanical problems  European Journal of Mechanics; A/Solids. [doi:?????](https://dx.doi.org/10.1016/?????)\" which can be downloaded [here](https://hdl.handle.net/????). We would be grateful if you could cite this publication in case you use the files.add a brief description of the dataset (Markdown and LaTeX enabled).","description_withheld":null,"homepage":"http://dx.doi.org/10.5281/zenodo.10451584","introduced_date":"2023-10-10","introduced_date_note":null,"introduced_by":{"paper":null,"title":"A quantum annealing-sequential quadratic programming assisted finite element simulation for non-linear and history-dependent mechanical problems","first_author":null,"url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[],"tasks":[],"languages":[],"variants":["January 2, 2024 (v1) Software Open Software and DataSet of \"A QA-SQP assisted FE for non-linear and history-dependent mechanics\""],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}