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Register a new userWarp-X: a new exascale computing platform for beam-plasma simulations
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Turning the current experimental plasma accelerator state-of-the-art from a promising technology into mainstream scientific tools depends critically on high-performance, high-fidelity modeling of complex processes that develop over a wide range of space and time scales. As part of the U.S. Department of Energys Exascale Computing Project, a team from Lawrence Berkeley National Laboratory, in collaboration with teams from SLAC National Accelerator Laboratory and Lawrence Livermore National Laboratory, is developing a new plasma accelerator simulation tool that will harness the power of future exascale supercomputers for high-performance modeling of plasma accelerators. We present the various components of the codes such as the new Particle-In-Cell Scalable Application Resource (PICSAR) and the redesigned adaptive mesh refinement library AMReX, which are combined with redesigned elements of the Warp code, in the new WarpX software. The code structure, status, early examples of applications and plans are discussed.
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An active plasma lens focuses the beam in both the horizontal and vertical planes simultaneously using a magnetic field generated by a discharge current through the plasma. A beam size of 5--10 $mu$m can be achieved using an focusing gradient on the order of 100 T/m. The active plasma lens is therefore an attractive element for plasma wakefield acceleration, because an ultra-small size of the witness electron beam is required for injection into the plasma wakefield to minimize emittance growth and to enhance the capturing efficiency. When the driving beam and witness electron beam co-propagate through the active plasma lens, interactions between the driving and witness beams and the plasma must be considered. In this paper, through particle-in-cell simulations, we discuss the possibility of using an active plasma lens for the final focusing of the electron beam in the presence of driving proton bunches. The beam parameters for AWAKE Run 2 are taken as an example for this type of application. It is confirmed that the amplitude of the plasma wakefield excited by proton bunches remains the same even after propagation through the active plasma lens. The emittance of the witness electron beam increases rapidly in the plasma density ramp regions of the lens. Nevertheless, when the witness electron beam has a charge of 100 pC, emittance of 10 mm mrad, and bunch length of 60 $mu$m, its emittance growth is not significant along the active plasma lens. For small emittance, such as 2 mm mrad, the emittance growth is found to be strongly dependent on the plasma density.
A new modular code called BOUT++ is presented, which simulates 3D fluid equations in curvilinear coordinates. Although aimed at simulating Edge Localised Modes (ELMs) in tokamak X-point geometry, the code is able to simulate a wide range of fluid models (magnetised and unmagnetised) involving an arbitrary number of scalar and vector fields, in a wide range of geometries. Time evolution is fully implicit, and 3rd-order WENO schemes are implemented. Benchmarks are presented for linear and non-linear problems (the Orszag-Tang vortex) showing good agreement. Performance of the code is tested by scaling with problem size and processor number, showing efficient scaling to thousands of processors. Linear initial-value simulations of ELMs using reduced ideal MHD are presented, and the results compared to the ELITE linear MHD eigenvalue code. The resulting mode-structures and growth-rate are found to be in good agreement (BOUT++ = 0.245, ELITE = 0.239). To our knowledge, this is the first time dissipationless, initial-value simulations of ELMs have been successfully demonstrated.
A large multitude of scientific computing tools is available today. This article gives an overview of available tools and explains the main application fields. In addition basic principles of number representations in computing and the resulting truncation errors are treated. The selection of tools is for those students, who work in the field of accelerator beam dynamics.
The CERN IT provides a set of Hadoop clusters featuring more than 5 PBytes of raw storage with different open-source, user-level tools available for analytical purposes. The CMS experiment started collecting a large set of computing meta-data, e.g. dataset, file access logs, since 2015. These records represent a valuable, yet scarcely investigated, set of information that needs to be cleaned, categorized and analyzed. CMS can use this information to discover useful patterns and enhance the overall efficiency of the distributed data, improve CPU and site utilization as well as tasks completion time. Here we present evaluation of Apache Spark platform for CMS needs. We discuss two main use-cases CMS analytics and ML studies where efficient process billions of records stored on HDFS plays an important role. We demonstrate that both Scala and Python (PySpark) APIs can be successfully used to execute extremely I/O intensive queries and provide valuable data insight from collected meta-data.
The proposal of generating high quality electron bunches via ionization injection triggered by an counter propagating laser pulse inside a beam driven plasma wake is examined via two-dimensional particle-in-cell simulations. It is shown that electron bunches obtained using this technique can have extremely small slice energy spread, because each slice is mainly composed of electrons ionized at the same time. Another remarkable advantage is that the injection distance is changeable. A bunch with normalized emittance of 3.3 nm, slice energy spread of 15 keV and brightness of $7.2times 10^{18}$ A m$^{-2}$ rad$^{-2}$ is obtained with an optimal injection length which is achieved by adjusting the launch time of the drive beam or by changing the laser focal position. This makes the scheme a promising approach to generate high quality electron bunches for the fifth generation light source.
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