Decoding Sources of Energy Variability in a Laser-Plasma Accelerator

Open Access

Decoding Sources of Energy Variability in a Laser-Plasma Accelerator

Andreas R. Maier, Niels M. Delbos, Timo Eichner, Lars Hübner, Sören Jalas, Laurids Jeppe, Spencer W. Jolly, Manuel Kirchen, Vincent Leroux, Philipp Messner, Matthias Schnepp, Maximilian Trunk, Paul A. Walker, Christian Werle, and Paul Winkler

Phys. Rev. X 10, 031039 – Published 18 August 2020

An article within the collection: Special Collection on Laser-Plasma Particle Acceleration

Abstract

Laser-plasma acceleration promises compact sources of high-brightness relativistic electron beams. However, the limited stability often associated with laser-plasma acceleration has previously prevented a detailed mapping of the drive laser and electron performance and represents a major obstacle towards advancing laser-plasma acceleration for applications. Here, we correlate drive laser and electron-beam parameters with high statistics to identify and quantify sources of electron energy drift and jitter. Based on our findings, we provide a parametrization to predict the electron energy drift with subpercent accuracy for many hours from measured laser parameters, which opens a path for performance improvements by active stabilization. Our results are enabled by the first stable 24-h operation of a laser-plasma accelerator and the statistics from 100 000 consecutive electron beams, which, by itself, marks an important milestone.

Received 7 April 2020
Accepted 23 July 2020

DOI:https://doi.org/10.1103/PhysRevX.10.031039

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Laser driven electron acceleration Laser wakefield acceleration Plasma acceleration & new acceleration techniques

Plasma PhysicsAccelerators & Beams

Collections

This article appears in the following collection:

Special Collection on Laser-Plasma Particle Acceleration

Physical Review X showcases the scientific vitality and diversity of the field of laser-plasma particle acceleration with a carefully curated collection of articles.

Authors & Affiliations

Andreas R. Maier ^1,2,*, Niels M. Delbos¹, Timo Eichner¹, Lars Hübner^1,2, Sören Jalas¹, Laurids Jeppe¹, Spencer W. Jolly ^1,3, Manuel Kirchen ¹, Vincent Leroux ^2,1,3, Philipp Messner^4,1, Matthias Schnepp¹, Maximilian Trunk¹, Paul A. Walker^2,1, Christian Werle¹, and Paul Winkler^2,1

¹Center for Free-Electron Laser Science and Department of Physics Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany
²Deutsches Elektronen Synchrotron (DESY), Notkestraße 85, 22607 Hamburg, Germany
³Institute of Physics of the ASCR, ELI-Beamlines Project, Na Slovance 2, 18221 Prague, Czech Republic
⁴International Max Planck Research School for Ultrafast Imaging & Structural Dynamics, Luruper Chaussee 149, 22761 Hamburg, Germany

^*andreas.maier@desy.de

Popular Summary

High-energy electron beams are an important resource for fundamental research and high-brightness x-ray sources. Compact next-generation sources of highly relativistic electron beams rely on laser-plasma accelerators, in which an intense laser pulse creates a trailing plasma wave that traps and accelerates electrons from the plasma background. The community has shown rapid progress in demonstrating beams of increasingly competitive quality. However, laser-plasma accelerators are very sensitive to subtle irregularities in the drive laser pulse, which makes providing reproducible electron beams a major challenge. Here, we investigate sources of residual variations in electron-beam energy and link them to properties of the drive laser.

Our setup combines modern accelerator technology and diagnostics with laser-plasma concepts to support continuous day-long accelerator operation. We thereby acquire a large number of events, which enables us to map electron-beam and drive laser parameters with high statistics. Based on these correlations, we can study the detailed mechanics of the underlying laser-plasma interaction and predictively model the drift in electron-beam energy from measured laser data.

Such a parametrization of the electron beam by drive laser properties is a powerful tool. It enables the implementation of feedback loops and active stabilization, as deployed in every modern high-performance accelerator worldwide.

Key Image

Article Text

Click to Expand

Supplemental Material

Click to Expand

References

Click to Expand

Issue

Vol. 10, Iss. 3 — July - September 2020

Subject Areas

Reuse & Permissions

Author publication services for translation and copyediting assistance advertisement

Images

Figure 1
The drive laser (red) is focused into a plasma-cell target, where it ionizes a nitrogen-doped hydrogen gas to form a plasma and then traps and accelerates electrons to an energy of 368 MeV. After the target, the laser is extracted from the beam axis for diagnostics. The electron beam (blue) is captured using a pair of electromagnetic quadrupoles and focused into a permanent magnet dipole spectrometer. The electron beam is adjusted to the accelerator design axis using steering dipoles. Retractable scintillating screens and cavity-type beam position monitors provide electron-beam profile, charge, and position information. For clarity, only a few of the installed laser diagnostics are shown. The whole setup is integrated into a controls system to enable live monitoring, tuning, and processing of the acquired data.
Reuse & Permissions
Figure 2
Panel (a) shows the energy spectra of 100 000 consecutive laser-plasma generated electron beams. Here, each line represents one single shot. The camera images of the electron spectrometer screen are background corrected, projected onto the dispersive axis, and calibrated to a linear energy scale. The peak energy of each spectrum (dots) is shown in panel (b), together with the energy drift (solid line) calculated as the rolling average over a 6-min window, i.e., 360 shots. The percent-level energy drift can be attributed to a drift in drive laser parameters (compare Figs. 3 and 4).
Reuse & Permissions
Figure 3
(a) Electron peak energy correlated with the laser energy $E$ , measured from a mirror leakage after the main amplifier. (b) Longitudinal laser focus position, measured with a wavefront sensor after the compressor. (c,d) Laser angle of incidence $θ$ (pointing), derived from the far field behind the parabola. The correlations are based on a 2-h data subset, as indicated in Fig. 4. The orange line is a linear fit to the correlation. The positions of the wavefront and far-field measurement are shown in Fig. 1.
Reuse & Permissions
Figure 4
To model the measured electron energy drift (blue), we used Eq. (1), the correlations presented in Fig. 3, and the drift of the measured laser energy, laser focus shift, and laser direction. As before, we calculated the drift as the 6-min rolling average (360 shots) of the single-event data. Only four noninvasively measured laser parameters are sufficient to predict (orange) the evolution of the electron energy with subpercent accuracy. The modeled electron energy is accurate for a 6-h (22 000 shots) time span, which significantly exceeds the 2-h time window (7000 shots) we used to correlate the laser and electron data.
Reuse & Permissions
Figure 5
Gray shaded areas mark the events used to derive the correlations $\partial_{E} E$ , $\partial_{Z} E$ , and $\partial_{θ} E$ . By regularly updating the correlations, the parametrization of the electron energy drift can be extended to the full data set.
Reuse & Permissions

Physical Review X