Vorsitzende der Sitzung
Plenary: Introduction
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Plenary: Plenary
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Plenary: Bayesian Optimization
- Rob Shalloo (DESY)
Plenary: ML at Large Laser Labs
- Kevin Cassou (CNRS/IJClab)
Plenary: Plenary
- In diesem Block gibt es keine Vorsitzenden
Plenary: Plenary
- In diesem Block gibt es keine Vorsitzenden
Plenary: Plenary
- In diesem Block gibt es keine Vorsitzenden
The EU-funded THRILL project (Technology for High-Repetition-Rate Intense Laser Laboratories) [1] gathers the forces of several institutions within a consortium to develop technologies, which will enable the operation of high-energy lasers at increased repetition rates. The overall goal of the project is to identify the most appropriate architecture of the next generation high-energy-laser...
In this talk, we discuss a deep learning model approach that uses messy data to learn the mapping between experimental parameters -> electron spectra. Many laser facilities, e.g. ZEUS at University of Michigan, have pre-existing operational procedures that produce "real-world” datasets where data are recorded manually and with assumptions and omissions. These do not necessarily provide clean...
This talk reviews intelligent automation systems being developed for laser plasma accelerators (LPAs) at the Berkeley Lab Laser Accelerator (BELLA) center in collaboration with Berkeley Accelerator Controls and Instrumentation (BACI) program. For the next generation high average power fiber lasers we showed efficient and stable coherent laser combining in space and time with Field Programmable...
Plasma acceleration has seen tremendous progress over the past years demonstrating competitive beam quality from compact setups. However, plasma accelerators live on a very complex non-linear parameter space, which makes it very challening to, first, identify an optimum working point, and then, second, to operate the plasma accelerator reliably at this point with reproducible beams.
The...
Laser-Plasma Acceleration (LPA) is a highly non-linear process sensitively dependent on parameters of gas flow and laser which are hard to control or simultaneously measure in experiments. Understanding of such parameter dependencies can be driven by simulations which offer control and observability, but are more expensive the more physical details are included. In the case of LPA, full 3D...
The ISIS Neutron and Muon Source, located at Harwell Campus, is a pulsed neutron source used to study the structure and dynamics of materials. This talk will explore ongoing efforts to leverage machine learning to improve efficiency and reliability of the accelerator sections used to deliver high energy protons to the targets. Examples will demonstrate applications of machine learning...
In this presentation we will first go through an overview of the Apollon multi-PW laser facility, discussing in some detail the architecture and the current performances of the system. In the second part of this talk we will focus on the focal spot quality stability requirements of Apollon and present our first results on what is to our knowledge the first active wavefront stabilization...
Adaptive Optics (AO) have revolutionized astronomy and enabled optical imaging down to ~15 mas resolution on today's largest telescopes. The resulting image stability and contrast have, in turn, allowed us to probed the close-in environment of neighboring stars, peeking at dust and debris disks, and blossoming exoplanets. In this talk, I will present recent results and technical capabilities...
Laser beam alignment is a non-trivial and time-consuming problem native to a multitude of present-day experiments. We introduce a reinforcement learning-based laser beam alignment system that learns to align a Mach-Zehnder interferometer and an off-axis parabolic mirror with live optimization correcting for beam drift or externally introduced mirror misalignment. The algorithm manages to find...
