Scientists use the LCLS X-Ray free electron laser to take crisp pictures of atomic motions, watch chemical reactions unfold, probe the properties of materials and explore fundamental processes in living things. In the fall of 2022 the LCLS-II superconducting linac will be commissioned and the X-Ray shot rate will increase from 120Hz to 1MHz. Correspondingly, the raw data volume will increase...
The PALLAS project aims to develop an laser-plasma injector (LPI) prototype delivering 150-200 MeV, 10-50 pC, 1 mm.mrad, at 10 Hz with reliability and control performance at the level of conventional RF accelerator. The LPI is driven by the 40 TW laser of the Université Paris-Saclay [LaseriX...
The control, management and analysis of data arising from laser-plasma experiments are key issues that, when well addressed, enable rapid insights into underlying physics and time-critical decision making for a given investigation. This issue now demands more attention if we are to take full advantage of developments in high-repetition rate, high-power laser technology.
Over the past...
Gemini, at the Central Laser Facility, provides access for academic and industrial users to perform a variety of cutting-edge experiments. As well as two beams, each with 12 J in 40 fs, we provide mechanical and electrical services to support experiments. These now include systems to support data acquisition, analysis, and storage, as well as experiment control. This has allowed us to conduct...
Open and standardized data formats have numerous advantages, including streamlining collaboration, improving software interoperability, and lowering access barriers. However, most data in high energy density physics (HEDP) are currently stored in idiosyncratic instrument or laboratory-specific formats. Analysis software is likewise often written for use by a single author (often duplicating...
Tango Controls has been adopted as main system for supervisory control and data acquisition at the Center for Advanced Laser Applications (CALA) in recent years. As an open-source, free and software independent toolkit it is highly customizable and applicable for almost any measurement device. In its current implementation at CALA the main laser system, as well as each experimental cave, has...
As high-intensity ultra-short PW-class laser systems, operating at high repetition rates, become a reality, laser-driven ion sources will become more suited for a variety of their potential applications. For many applications, shot-to-shot reproducibility and tuning of the beam parameters for a desirable proton source is crucial. The laser-driven ion beam depends on both laser and target...
Laser Wakefield Acceleration (LWFA) is a process by which high gradient plasma waves are excited by a laser leading to the acceleration of electrons. The process is highly nonlinear leading to difficulties in developing 3 dimensional models for a priori, and/or ab initio prediction.
Recent experiments at the Rutherford Appleton Laboratory’s (RAL) Central Laser Facility (CLF) in the United...
In recent research, reinforcement learning algorithms have been shown capable of solving complex control tasks, also showing potential for beam control, and in the optimization and automation of tasks in accelerator operation.
As part of the Helmholtz AI project "Machine Learning Toward Autonomous Accelerators" -- a collaboration between DESY and KIT -- reinforcement learning applications...
Deep learning can be used to replace time-consuming diagnostic analysis. With further development, experimental data from high-rep-rate capable laser facilities can be analyzed accurately and at rates fast enough to enable self-driving experiments. The general process for developing neural networks for analyzing data from a proton beam diagnostic will be discussed.
Abstract: While the latest technologies have enabled unprecedented laser intensities, the highest energy laser facilities usually operate in single-shot mode, namely firing a few shots a day. On the other side, the development of laser systems with higher repetition rates but lower peak power is always of fundamental interest, particularly for applications. Applications of the particle beams...
Flexible data structures are critical when designing control systems and data storage for high-repetition-rate experiments, and they must take into account the full lifetime of the experiment from facility preparation to data analysis. We present lessons learned from our experience creating software to control high-rep-rate laser experiments at UCLA. We overview the main motivations and key...
We show a cloud-based platform for experimental data storage, management, and sharing. The platform has a UI that runs on a containerized Pythonic web application hosted by a container service. It is fronted by a lightweight authentication portal for a username and password. The experimental data is stored on a database service and object storage service. The container server, database, object...
Experiments have per definition an unknown outcome and need adaption and improvement during their runtime. Especially user experiments are frequently changed or even just temporarily set up. On the other hand, policies develop towards open science what is undeniably useful in our field since drive lasers/facilities and experiments are cutting-edge but always have their peculiarities, hence...
Numerical simulations of complex systems such as Laser-Plasma acceleration are computationally very expensive and have to be run on large-scale HPC systems. Offline analysis of experimental data is typically carried out by expensive grid scans or optimisation of particle-in-cell code like PIConGPU modelling the corresponding physical processes. Neural Network based surrogate models of this...
We present a novel method to efficiently implement Machine Learning methods within Particle-in-Cell (PIC) simulation codes. Such codes are vital to fully understand the kinetic processes involved in Laser Wakefield acceleration and constitute a key tool to comprehend experimental setups and their diagnostics data. However, their computational cost prevents large parameter scans in 3D...
Laser wakefield acceleration (LWFA) has demonstrated to be a small-scale alternative for accelerating electrons. With the discovery and experimental realization of the so-called blowout regime, quasi-monoenergetic electron bunches could be produced. Progress in LWFA beam quality and stability has always been tied to improvements in machine control and experimental diagnostics. One such...
A key problem in experimental diagnostics of laser-plasma interactions is identifying the interaction scenario using only limited measurement data. Using numerical simulations for training ML models to recognize interactions via measurements has the potential to become a powerful paradigm for complex experimental arrangements. This is because such ML-based diagnostics does not require either...
In this talk, I'd like to present modern machine learning tools for estimating the posterior of the inverse problem exposed in a beam control setting. That is, given an experimental beam profile, I'd like to demonstrate tools that help to estimate which simulation parameters might have produced a similar beam profile with high likelihood.
We summarize preliminary findings bound to optimize...
We will be reviewing recent machine learning techniques from the perspective of compact Laser-particle accelerators (electron and ions). High-fidelity simulations of the involved physical phenomena are carried out by computationally-expensive particle-in-cell simulations which are used for planning of experiments as well as subsequent analysis. We will be discussing methods for surrogate...
Radiation reaction, the recoil of a charge upon emitting radiation, is the subject of ongoing theoretical and experimental research, particularly in highly intense electromagnetic fields in which quantum effects become significant. In such environments, a QED treatment of radiation reaction is required. Various suitable theories have been proposed but have yet to be validated...
Bayesian optimization has proven to be an efficient method to optimize expensive-to-evaluate systems such as a Laser Wakefield Accelerator (LWFA). However, depending on the cost of single observations, multi-dimensional optimizations of one or more objectives (Pareto optimization) may still be prohibitively expensive. Multi-fidelity optimization remedies this issue by including multiple,...
