Related papers: Integration of Machine Learning-Based Plasma Accel…
One of the most robust methods, demonstrated up to date, of accelerating electron beams by laser-plasma sources is the utilization of plasma channels generated by the capillary discharges. These channels, i.e., plasma columns with a minimum…
As ultracold atom experiments become highly controlled and scalable quantum simulators, they require sophisticated control over high-dimensional parameter spaces and generate increasingly complex measurement data that need to be analyzed…
A new electron injection scheme is proposed in sub-relativistic plasma wakefield accelerators. A transverse laser ionizes a dopant gas and ponderomotively accelerates the released electrons in the direction of wake propagation. This process…
We present a novel electron injection scheme for plasma wakefield acceleration. The method is based on recently proposed technique of fast electron generation via laser-solid interaction: a femtosecond laser pulse with the energy of tens of…
This pair of CAS lectures gives an introduction for accelerator physics students to the framework and terminology of machine learning (ML). We start by introducing the language of ML through a simple example of linear regression, including…
Plasma-based acceleration schemes have attracted sustained interest as a pathway toward compact particle accelerators, owing to the large electric fields supported by plasmas. Although recent studies have demonstrated the excitation of…
The "Advanced Proton Driven Plasma Wakefield Acceleration Experiment" (AWAKE) aims to accelerate leptons via proton-beam-driven wakefield acceleration. It comprises extensive numerical studies as well as experiments at the CERN laboratory.…
We propose and detail a multi-step analytical procedure, based on an improved fully relativistic plane model for Laser Wake Field Acceleration, to tailor the initial density of a cold diluted plasma to the laser pulse profile, so as to…
Plasma wakefield acceleration (PWFA) is a novel acceleration technique with promising prospects for both particle colliders and light sources. However, PWFA research has so far been limited to a few large-scale accelerator facilities…
The Generic Geant4 Simulation (GGS) is a package designed to speed-up the realization and deployment of Monte Carlo simulation software based on Geant4, for small- and medium-sized high-energy experiments. For many common use cases, the…
The intrinsic constraints in the amplitude of the accelerating fields sustainable by radio-frequency accelerators demand for the pursuit of alternative and more compact acceleration schemes. Among these, plasma-based accelerators are…
Plasma-Based Acceleration (PBA) has been demonstrated using laser, electron, and proton drivers. However, significant challenges remain in achieving high efficiency, stable acceleration, and scalable energy gain. Heavy ion beam drivers,…
A new generation of laser wakefield accelerators, supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances…
Detector simulation and reconstruction are a significant computational bottleneck in particle physics. We develop Particle-flow Neural Assisted Simulations (Parnassus) to address this challenge. Our deep learning model takes as input a…
Plasma wakefield acceleration studies currently rely considerably on simulating this effect numerically using highly specialized software. Exorbitant computational difficulty of the problem requires simplifying models and methods,limiting…
Exploring new target schemes for laser wakefield accelerators is essential to meet the challenge of increasing repetition rates while ensuring stability and quality of the produced electron beams. The prototyping of a two-chamber gas cell…
Currently, machine learning (ML) methods are widely used to process the results of physical experiments. In some cases, due to the limited amount of experimental data, ML-models can be pre-trained on synthetic data simulated based on the…
Machine learning (ML) offers a promising solution to pathloss prediction. However, its effectiveness can be degraded by the limited availability of data. To alleviate these challenges, this paper introduces a novel simulation-enhanced data…
A plasma beam dump uses the collective oscillations of plasma electrons to absorb the kinetic energy of a particle beam. In this paper, a modified passive plasma beam dump scheme is proposed using either a gradient or stepped plasma profile…
In the design of laser plasma electron injectors for multi-stage laser driven wakefield accelerators, the control of plasma density is a key element to stabilize the acceleration process. A cell with variable parameters is used to confine…