FreeGSNKE: A Python-based dynamic free-boundary toroidal plasma equilibrium solver We present a Python-based numerical solver for the two-dimensional dynamic plasma equilibrium problem. We model the time evolution of toroidally symmetric free-

Huge kudos to the team for their hard work in delivering this high-quality contribution to the community. Open-source fusion modelling just got a big boost!

Paper:
pubs.aip.org/aip/pop/arti...

GitHub - FusionComputingLab/freegsnke: FreeGSNKE: A Python code for evolutive free-boundary tokamak plasma equilibrium simulations FreeGSNKE: A Python code for evolutive free-boundary tokamak plasma equilibrium simulations - FusionComputingLab/freegsnke

FreeGSNKE is the UK Fusion Computing Lab's answer to this challenge!

↔️ Fully benchmarked against existing codes
🦾 Robust solvers
🖥️ Modern coding practices
📖 Excellent documentation and tutorials
🌐 Fully open source

github.com/FusionComput...

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🚀FreeGSNKE is now open-source! Big milestone, esp for those interested in ML/RL for fusion🚀

I've talked to many people who have been inspired by Deepmind's 2022 Nature paper on tokamak magnetic control, but struggled to get involved in ML-control for fusion problems...

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Interested in symmetries/GPs/BayesOpt/nuclear fusion? Come and check out our #NeurIPS poster!

📍West Ballroom #6003 @ 11am-2pm

🔍 Not sure if it's for you? Read the blog post to get a brief insight >>> theobrown.uk/blog/invaria...

w/ @ilijabogunovic.bsky.social
@uclofficial.bsky.social

Sample-efficient Bayesian Optimisation Using Known Invariances Bayesian optimisation (BO) is a powerful framework for global optimisation of costly functions, using predictions from Gaussian process models (GPs). In this work, we apply BO to functions that exhibi...

📝 In our paper, we back up our empirical findings with upper and lower regret bounds.

Check it out! arxiv.org/abs/2410.16972

#NeurIPS2024 #research #ml
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⚡ Invariant BO has a whole host of applications. We tackle a difficult design task from nuclear fusion: designing a heating system for STEP, the UK's flagship next-gen fusion reactor.

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#STEPtoFusion #fusionenergy

⬆️ Using an invariant kernel massively boosts sample efficiency (red line).

For a low-cost approximation, you can use a *subset* of symmetries without sacrificing improved performance (yellow + green lines).

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📣 If you've got an objective that exhibits symmetries, you should be using invariant kernel BO 📣

🚀 More sample efficient than constrained/naive BO!

🚀 More compute efficient than data augmentation!

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#NeurIPS2024 #BayesianOptimisation #ai