Asset Details
Do you wish to reserve the book?
Multi-parameter Bayesian optimisation of laser-driven ion acceleration in particle-in-cell simulations
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Multi-parameter Bayesian optimisation of laser-driven ion acceleration in particle-in-cell simulations
Do you wish to request the book?
Multi-parameter Bayesian optimisation of laser-driven ion acceleration in particle-in-cell simulations
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Multi-parameter Bayesian optimisation of laser-driven ion acceleration in particle-in-cell simulations
2022
Overview
High power laser-driven ion acceleration produces bright beams of energetic ions that have the potential to be applied in a wide range of sectors. The routine generation of optimised and stable ion beam properties is a key challenge for the exploitation of these novel sources. We demonstrate the optimisation of laser-driven proton acceleration in a programme of particle-in-cell simulations controlled by a Bayesian algorithm. Optimal laser and plasma conditions are identified four times faster for two input parameters, and approximately one thousand times faster for four input parameters, when compared to systematic, linear parametric variation. In addition, a non-trivial optimal condition for the front surface density scale length is discovered, which would have been difficult to identify by single variable scans. This approach enables rapid identification of optimal laser and target parameters in simulations, for use in guiding experiments, and has the potential to significantly accelerate the development and application of laser–plasma-based ion sources.
Publisher
IOP Publishing
Subject
