Related papers: Implementation and Deployment of an Injection Tuni…
We propose a new and simple strategy for controlled ionization-induced trapping of electrons in a beam-driven plasma accelerator. The presented method directly exploits electric wakefields to ionize electrons from a dopant gas and capture…
While laser wakefield acceleration (LWFA) in the bubble regime demands ultra-short, high-peak-power laser pulses, operation in the self-modulated regime (SM-LWFA) works with more relaxed pulse conditions, albeit at the cost of lower beam…
All-optical controlled injection and acceleration of electrons in a laser wakefield has recently been achieved (Faure et al, Nature v. 444 p. 737, 2006). Injection was made using a second counterpropagating laser pulse with the same…
Machine learning methods usually depend on internal parameters -- so called hyperparameters -- that need to be optimized for best performance. Such optimization poses a burden on machine learning practitioners, requiring expert knowledge,…
The European Spallation Source linear proton accelerator will have a uniquely high power of 5 MW. The modifications and additions to the accelerator that are required to enable the generation of a uniquely intense neutrino Super Beam…
KEK-ATF is studying the low-emittance multi-bunch electron beam for the future linear collider. In ATF, thermionic gun is used to generate 20 bunches electron beam with the bunch spacing of 2.8 ns. Due to a distortion of the gun emission…
Future $e^+e^-$ colliders at the Z pole place strong demands of $\frac{\delta L}{L}<10^{-4}$ on the integrated luminosity measurement. Small angle Bhabha scattering (SABS) remains the standard channel, while diphoton ($\gamma\gamma$) events…
Bayesian optimization is an advanced tool to perform ecient global optimization It consists on enriching iteratively surrogate Kriging models of the objective and the constraints both supposed to be computationally expensive of the targeted…
The beam parameters of complete prototype of the bERLinPro injector that consisted of a lead cathode in an 1.6 cell superconducting cavity were measured. The measurements are discussed in chapter 2 and indicate that the beam emittance is…
Decarbonization of the transport sector sets increasingly strict demands to maximize thermal efficiency and minimize greenhouse gas emissions of Internal Combustion Engines. This has led to complex engines with a surge in the number of…
A major LHCb detector upgrade will be installed during long shutdown~4 (LS4) of the CERN Large Hadron Collider. The experiment will operate at a maximum luminosity of up to $1.5\times 10^{34}\mathrm{cm}^{-2}\mathrm{s}^{-1}$, with acceptance…
Bayesian optimization (BO) is a sample efficient approach to automatically tune the hyperparameters of machine learning models. In practice, one frequently has to solve similar hyperparameter tuning problems sequentially. For example, one…
Shot-to-shot fluctuations in electron beams from laser wakefield accelerators present a significant challenge for applications. Here, we show that instead of using such fluctuating beams directly, employing them to drive a plasma…
We present a seeded topology optimization methodology for integrated photonic devices fabricated on foundry platforms that yields improved performance compared to traditional topology optimization. We employ blurring filters and a design…
Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks. Despite its success, for large datasets, training and validating a…
Efficient transport of high-current negative ion beams is critical for accurate plasma potential diagnostics using heavy-ion beam probe (HIBP) systems in magnetically confined fusion plasmas. However, strong space-charge effects often…
Tunable lasers are essential for optical communication, spectroscopy, and precision sensing, where flexible and fast control of the laser wavelength is needed. However, conventional tunable laser systems often rely on mechanical actuation,…
Information-based Bayesian optimization (BO) algorithms have achieved state-of-the-art performance in optimizing a black-box objective function. However, they usually require several approximations or simplifying assumptions (without…
This study investigates the application of Bayesian Optimization (BO) for the hyperparameter tuning of neural networks, specifically targeting the enhancement of Convolutional Neural Networks (CNN) for image classification tasks. Bayesian…
In this paper, beam diagnostic and monitoring tools developed by the MAX IV Operations Group are discussed. In particular, new beam position monitoring and accelerator tunes visualization software tools, as well as tools that directly…