An Adjoint Formulation of Energetic Particle Confinement

Fuente: arXiv
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Autores principales: McDevitt, Christopher J., Arnaud, Jonathan S.
Formato: Preprint
Publicado: 2025
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author McDevitt, Christopher J.
Arnaud, Jonathan S.
author_facet McDevitt, Christopher J.
Arnaud, Jonathan S.
contents An adjoint formulation of energetic particle confinement in axisymmetric tokamak geometry is derived and evaluated using a physics-informed neural network (PINN). The PINN estimates the mean escape time of energetic ions by solving an inhomogeneous adjoint of the drift kinetic equation with a Lorentz collision operator, yielding predictions of fast ion loss in tokamak geometry due to direct ion orbit loss and collisional transport. To our knowledge, this is the first time a PINN has been used to solve the drift kinetic equation in tokamak geometry, a challenging problem due to the large time scale separation between the rapid transit time of energetic ions and their slow collisional time scale. It is shown that a careful and intentional design of a PINN is able to learn the mean escape time across the majority of the plasma volume, suggesting a path toward constructing a rapid surrogate for use within a broader optimization framework.
format Preprint
id arxiv_https___arxiv_org_abs_2511_11968
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An Adjoint Formulation of Energetic Particle Confinement
McDevitt, Christopher J.
Arnaud, Jonathan S.
Plasma Physics
An adjoint formulation of energetic particle confinement in axisymmetric tokamak geometry is derived and evaluated using a physics-informed neural network (PINN). The PINN estimates the mean escape time of energetic ions by solving an inhomogeneous adjoint of the drift kinetic equation with a Lorentz collision operator, yielding predictions of fast ion loss in tokamak geometry due to direct ion orbit loss and collisional transport. To our knowledge, this is the first time a PINN has been used to solve the drift kinetic equation in tokamak geometry, a challenging problem due to the large time scale separation between the rapid transit time of energetic ions and their slow collisional time scale. It is shown that a careful and intentional design of a PINN is able to learn the mean escape time across the majority of the plasma volume, suggesting a path toward constructing a rapid surrogate for use within a broader optimization framework.
title An Adjoint Formulation of Energetic Particle Confinement
topic Plasma Physics
url https://arxiv.org/abs/2511.11968