Using AI to Model Laser Fusion Implosions | Machine Learning for Fusion

How can artificial intelligence be used to simulate implosions in laser fusion, where capsules of fuel are compressed to create miniature man-made stars?

Laser fusion is a method of confining a fusion plasma where high power lasers are used to compress capsules of fuel to the width of a human hair, and heat them to temperatures comparable to the sun.

In this video we describe the process of surrogate modelling, where a machine learnt model is used as a cheap and actionable version of expensive simulations. One way to build surrogate models is through neural networks, though these methods often need vast amounts of data to perform effectively.

In a recent study from the OMEGA laser fusion facility in the United States, scientists used a method known as transfer learning to train machine learning surrogate models: first on many low fidelity simulations, then on high fidelity simulations and experiments.

This transfer learning approach (an example of the broader method of multi fidelity machine learning) has led to the development of effective surrogate models in laser fusion. These models can be used to optimise laser fusion experiments and improve simulations, bringing us one step closer to fusion energy.

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📌 Timestamps
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00:00 - Intro & recap
01:28 - Laser fusion
02:11 - Radiation hydrodynamics
03:03 - Surrogate modelling
03:42 - Neural networks
04:51 - Deep learning
05:16 - Training models on experiments
06:21 - Transfer learning
07:02 - OMEGA laser transfer learning
07:40 - Study results
08:23 - Surrogates to optimise laser fusion
09:52 - Improving simulations with ML
10:59 - Conclusions

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📚 Resources
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The paper discussed in this video can be accessed here:

https://ieeexplore.ieee.org/abstract/...


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🏷️ Tags
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Fusion
Energy
Tech
Machine Learning
Artificial Intelligence

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