activity
20212025
most citedStable and high quality electron beams from staged laser and plasma wakefield accelerators

34 citations · 53 across the 6 of their papers we have counts for

collaborators

6 papers

physics.optics2025

Information-Optimal Sensing and Control in High-Intensity Laser Experiments

A. Döpp, C. Eberle, J. Esslinger +5

High-intensity laser systems present unique measurement and optimization challenges due to their high complexity, low repetition rates, and shot-to-shot variations. We discuss rece…

physics.acc-ph2023

Pareto Optimization of a Laser Wakefield Accelerator

F. Irshad, C. Eberle, F. M. Foerster +6

Optimization of accelerator performance parameters is limited by numerous trade-offs and finding the appropriate balance between optimization goals for an unknown system is challen…

cs.LG2022★ 8 cited

Data-driven Science and Machine Learning Methods in Laser-Plasma Physics

Andreas Döpp, Christoph Eberle, Sunny Howard +3

Laser-plasma physics has developed rapidly over the past few decades as high-power lasers have become both increasingly powerful and more widely available. Early experimental and n…

physics.acc-ph2022

Multi-objective and multi-fidelity Bayesian optimization of laser-plasma acceleration

Faran Irshad, Stefan Karsch, Andreas Döpp

Beam parameter optimization in accelerators involves multiple, sometimes competing objectives. Condensing these individual objectives into a single figure of merit unavoidably resu…

physics.acc-ph2022★ 34 cited

Stable and high quality electron beams from staged laser and plasma wakefield accelerators

F. M. Foerster, A. Döpp, F. Haberstroh +24

We present experimental results on a plasma wakefield accelerator (PWFA) driven by high-current electron beams from a laser wakefield accelerator (LWFA). In this staged setup stabl…

cs.LG2021★ 11 cited

Leveraging Trust for Joint Multi-Objective and Multi-Fidelity Optimization

Faran Irshad, Stefan Karsch, Andreas Döpp

In the pursuit of efficient optimization of expensive-to-evaluate systems, this paper investigates a novel approach to Bayesian multi-objective and multi-fidelity (MOMF) optimizati…