16–18 nov. 2026
LPSC
Fuseau horaire Europe/Paris

Physics-informed impedance-model-agnostic reconstruction of point-charge wakefields from finite bunch electromagnetic simulations

17 nov. 2026, 12:30
5m
Amphitheatre (LPSC)

Amphitheatre

LPSC

53 Avenue des Martyrs 38000 Grenoble
Lightning talks AI for Physics Analysis, Inference and Discovery AI for Physics Analysis, Inference and Discovery

Orateur

Keon Hee Kim (CNRS/GANIL)

Description

Electromagnetic wakefield simulations generally provide wake potentials excited by finite length bunches, whereas beam dynamics studies require the underlying point-charge wake and broadband impedance. Direct access to the THz impedance regime in full 3D electromagnetic simulations typically requires extremely short drive bunches and very fine numerical resolution. The resulting simulations can be computationally expensive and, at sufficiently short bunch lengths, may also become numerically fragile in ways that are not always resolved by further mesh refinement. This motivates reconstructing the point-charge response from simulations performed with longer, computationally more tractable bunches.

We develop a impedance-model-agnostic reconstruction method, PCWR, which infers the point-charge wake directly from finite bunch electromagnetic simulations data without assuming an analytical impedance model. The method combines Golub–Kahan Krylov inversion, regularized solution ensembles, uncertainty based spectral trust estimation, and physics-informed reconstruction of poorly constrained frequency regions. Causality and consistency with the simulated finite bunch wake are enforced throughout the reconstruction. The method is tested on three qualitatively different structures: a single-layer resistive wall chamber, and a two-layer NEG/Cu resistive wall chamber, and a corrugated dechirper. The PCWR provides a route to extracting short-range wake and high frequency impedance information that is inaccessible or unstable under straightforward deconvolution.

Auteur

Keon Hee Kim (CNRS/GANIL)

Co-auteur

Dr Adnan Ghribi (CNRS/GANIL)

Documents de présentation

Aucun document.