| --- |
| license: mit |
| pretty_name: PhySimCode |
| language: |
| - en |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - video-text-to-text |
| tags: |
| - physics |
| - simulation |
| - video |
| - code-generation |
| - multimodal |
| - benchmark |
| --- |
| |
| # PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation |
|
|
| [**Website**](https://sourajakundu.github.io/PhySimCode/) · [**Paper**](https://arxiv.org/abs/2610.15722) · [**Code**](https://github.com/SourajaKundu/PhySimCode) |
|
|
| Can a multimodal LLM watch a 2D or 3D physics simulation, work out the involved physics laws and parameter values, and write code from scratch that regenerates it? |
|
|
| This dataset is the **PhySimCode evaluation set**: 2,430 physics simulation videos, each paired with the Python code that rendered it, its true parameter values, and a step-by-step physics explanation (chain-of-thought). It is the set on which all models in the paper are evaluated. |
|
|
| ## Overview |
|
|
| - **162 physics phenomena** across 9 physical domains (rigid body, spring / wave, articulated, constrained, pendulum, real-life mixed, rolling, rope / granular, gravitation / fluid) |
| - **15 samples per phenomenon**, each with randomly sampled physical parameters |
| - **Two engines**: analytic SciPy simulations (2D) and PyBullet rigid-body scenes (3D) |
| - Drawn from the full PhySimCode corpus of 160,614 procedurally generated samples |
|
|
| | Engine | Folder | Phenomena | Samples | Video | |
| |---|---|---|---|---| |
| | SciPy (2D) | `scipy/` | 87 | 1,305 | 360×180, 10 FPS | |
| | PyBullet (3D) | `kubric/` | 75 | 1,125 | 240×240, 10 FPS | |
| | **Total** | | **162** | **2,430** | | |
|
|
| ## Structure |
|
|
| ``` |
| scipy/<experiment>/<sample_id>/ |
| video.mp4 # input to the model |
| simulation_code.py # ground-truth code that renders video.mp4 |
| cot.json # ground-truth chain-of-thought |
| params.json # sampled parameter values |
| kubric/<experiment>/<sample_id>/ |
| ... # same four files |
| ``` |
|
|
| Every `cot.json` contains `simulation`, `physical_observation`, `physical_law` (name, statement, LaTeX formula), `ode_system`, `derivation_steps`, `numerical_method`, `code_validation`, `expected_behavior` and `parameters` (value, unit and description for every parameter). |
|
|
| - SciPy samples also include `physical_constants_derived` (quantities computed from the parameters). |
| - PyBullet samples also include `category`, `seed`, `modeling_assumptions`, `impulse_model`, `pybullet_numerical_model` and `visual_scene`. |
|
|
| ## Task |
|
|
| Given only `video.mp4` and the engine name (`scipy` or `kubric`), a model must output: |
|
|
| 1. a chain-of-thought JSON with `simulation`, `physical_observation`, `physical_law` and `parameters`, and |
| 2. a self-contained Python script that regenerates the video. |
|
|
| Models are scored on physical-law correctness and equivalence (three LLM judges), parameter recovery within ±20%, code compilation / execution / video output, CodeBLEU, and DINOv2 / VideoCLIP similarity between the regenerated and input videos. The prompt is given in Appendix A.4 of the paper, and the evaluation code is on [GitHub](https://github.com/SourajaKundu/PhySimCode). |
|
|
| ## Download |
|
|
| ```bash |
| pip install -U huggingface_hub |
| hf download SourajaKundu123/PhySimCode --repo-type dataset --local-dir benchmarking_data |
| ``` |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| snapshot_download("SourajaKundu123/PhySimCode", repo_type="dataset", local_dir="benchmarking_data") |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{kundu2026physimcode, |
| title = {PhySimCode: A Benchmark and Evaluation Method for |
| Physics Video to Code Generation}, |
| author = {Kundu, Souraja and Gupta, Aditya and Julin, Joel and |
| Zhao, Yizhou and Xie, Liuyue and Jeni, Laszlo A.}, |
| year = {2026}, |
| eprint = {2610.15722}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.CV}, |
| url = {https://arxiv.org/abs/2610.15722} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| Souraja Kundu, [sourajak@cs.cmu.edu](mailto:sourajak@cs.cmu.edu) |
|
|
