Conveners
PS7: Beam diagnostics, instrumentation, Machine Learning: Diagnostics
- Alessio Del Dotto (Istituto Nazionale di Fisica Nucleare)
- Brigitte Cros (CNRS - LPGP - Universite Paris Saclay)
PS7: Beam diagnostics, instrumentation, Machine Learning
- Alessio Del Dotto (Istituto Nazionale di Fisica Nucleare)
- Brigitte Cros (CNRS - LPGP - Universite Paris Saclay)
Accurate, non-invasive diagnostics of laser-interacted plasma targets are essential for optimizing high-intensity laser experiments, including laser plasma acceleration (LPA). We present a novel approach based on computational X-ray holography to image targets such as hydrogen gas jets. This technique captures single-shot X-ray diffraction patterns in an in-line geometry, where phase contrast...
Next-generation accelerators, such as those employing plasma or laser wakefield acceleration techniques, demand precise characterization of the beam's properties, making accurate measurement of the five-dimensional (5D) phase space distribution essential. To meet this need, a novel transverse deflecting structure with adjustable polarization, known as the Polarizable X-band Transverse...
The [HELPMI project][1] was a 2-year initiative to start the development of a F.A.I.R. data standard for laser-plasma experimental data. It was conducted by GSI, HI Jena and HZDR and subsidized by the Helmholtz Metadata Collaboration. The original aim was two-fold: building upon the extensible NeXus standard – being used for many experimental techniques in Photon and Neutron science – while...
We report preliminary data from a prototype Electro-Optic Sampling Beam Position Monitor (EOS-BPM) at the FACET-II Facility at SLAC National Accelerator Laboratory. In EOS-BPM, a birefringence is induced in two electro-optic crystals on either side of the electron beam's trajectory as it passes by. Laser pulses traveling through each crystal pick up a spacially encoded polarization which is...
Plasma accelerators made huge advancements in recent years and with increasing repetition rate and average power start to become feasible for use in applications. This increase in power also requires more thinking in terms of radiation safety, especially since both photon and electron beams produced in plasma accelerators have very unique features compared to other beam sources. Here we...
The driving laser's spectrum evolves during laser-wakefield acceleration due to the density and intensity gradients in the driven plasma wave. These density gradients also determine the accelerating fields experienced by injected electrons, and so the post-acceleration laser spectrum may be correlated with the electron spectrum, potentially allowing for its use as a non-disruptive diagnostic...
Recent advances in high-power lasers approaching kilohertz repetition rates are pushing laser-plasma accelerators (LPAs) into the watt-level average-power regime, offering unprecedented statistical access to their intrinsic properties. In this talk, we outline how the Kaldera project at DESY employs fast diagnostic measurements to explore key performance aspects of high-average-power LPAs. We...
This work explores the application of Bayesian methods to enhance measurement and optimization in experimental physics, with a focus on laser-plasma interactions. Bayesian updates enable the integration of prior knowledge with new data, facilitating refined parameter estimation and uncertainty quantification. These methods have been employed to achieve the first single-shot measurement of...
Bayesian Optimisation (BO) has shown great promise in optimising Laser Plasma Acceleration (LPA) experiments, even in the presence of substantial measurement noise. Notably, BO has demonstrated its ability to identify user-specified optima and generate tuning curves, effectively mapping an input space trajectory to a smooth variation of an observation parameter, such as mean energy. However,...
Laser-electron accelerators emerge as novel, compact sources of high-quality relativistic electron beams. Their extremely high peak currents make them ideal for applications in fields such as material science, healthcare, and particle physics.
Each experimental application requires unique electron parameters. Additionally, all the input parameters are interconnected, resulting in a highly...
Plasma accelerators often constitute a high-noise environment with multiple, non-linear dependencies that make the setup and operation of such devices a difficult task. To address these challenges, Machine Learning methods have gained popularity in the field of plasma acceleration. In this contribution, we summarise the application of such techniques to the beam-driven plasma acceleration...
Dielectric Laser Acceleration (DLA) is a promising technology for compact electron accelerators, capable of achieving accelerating gradients far beyond those of conventional radiofrequency cavities. Dielectric nanostructures are used to shape the near-fields of ultrashort laser pulses to accelerate electrons. However, introducing advanced laser shaping techniques, such as pulse front tilts or...
