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57 | 57 | "Once `miniconda` is installed run this command in your terminal:\n",
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58 | 58 | "\n",
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59 | 59 | "```bash\n",
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60 |
| - "conda env create -f environment.yml\n", |
| 60 | + "conda env create -f environment.yaml\n", |
61 | 61 | "```\n",
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62 | 62 | "\n",
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63 | 63 | "This should create a virtual environment named `malapa-cheetah-tutorial-2025` and install the necessary packages inside.\n",
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356 | 356 | "source": [
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357 | 357 | "<h2 style=\"color: #b51f2a\">Some achievements</h2>\n",
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358 | 358 | "\n",
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359 |
| - "To be filled @Jan\n", |
| 359 | + "### Timeline\n", |
360 | 360 | "\n",
|
361 |
| - "- When was it first launched\n", |
362 |
| - "- How many downloads up to date\n", |
363 |
| - "- 2024 PRAB highlight paper\n" |
| 361 | + "- In development since March 2021 (initially as _\"JOSS 🤯\"_, renamed to _Cheetah_ in July 2021)\n", |
| 362 | + "- First publicly released version 0.5.12 in June 2022\n", |
| 363 | + "- First fully differentiable release 0.6 in Septemeber 2023\n", |
| 364 | + "- Merged with Bmad-X beginning March 2024\n", |
| 365 | + "- Fully vectorised release 0.7 Decmeber 2024\n", |
| 366 | + "\n", |
| 367 | + "### Cheetah in numbers\n", |
| 368 | + "\n", |
| 369 | + "- Over 22,300 downloads as off April 2025 (just from PyPI)\n", |
| 370 | + "- Currently about 1,500 downloads per month (just from PyPI)\n", |
| 371 | + "\n", |
| 372 | + "### Papers\n", |
| 373 | + "\n", |
| 374 | + "- 2022 first paper on Cheetah developments at IPAC'22: [Accelerating Linear Beam Dynamics Simulations for Machine Learning Applications](https://accelconf.web.cern.ch/ipac2022/doi/JACoW-IPAC2022-WEPOMS036.html)\n", |
| 375 | + "- 2024 main Cheetah paper in PRAB: [Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations](https://doi.org/10.1103/PhysRevAccelBeams.27.054601)\n", |
| 376 | + "- 2024 paper on advancements in differentiable simulations at LINAC2024: [Advancements in Backwards Differentiable Beam Dynamics Simulations for Accelerator Design, Model Calibration, and Machine Learning](https://meow.elettra.eu/71/doi/jacow-linac2024-thpb068/index.html)\n" |
364 | 377 | ]
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365 | 378 | },
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366 | 379 | {
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