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We present particle-in-cell simulations, using the VORPAL framework, of 10 GeV laser plasma wakefield accelerator stages. Scaling of the physical parameters with the plasma density allows us to perform these simulations at reasonable cost and to design high performance stages. In particular we show that, by choosing to operate in the quasi-linear regime, we can use higher order laser modes to tailor the focusing forces. This makes it possible to increase the matched electron beam radius and hence the total charge in the bunch while preserving the low bunch emittance required for applications.

Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies —such as efficient data management— supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.

Laser plasma accelerators are able to produce high quality electron beams from 1 MeV to 1 GeV. The next generation of plasma accelerator experiments will likely use a multi-stage approach where a high quality electron bunch is first produced and then injected into an accelerating structure. In this paper we present scaled particle-in-cell simulations of a 10 GeV stage in the quasi-linear regime. We show that physical parameters can be scaled to be able to perform these simulations at reasonable computational cost. Beam loading properties and electron bunch energy gain are calculated. A range of parameter regimes are studied to optimize the quality of the electron bunch at the output of the stage.

One of the central challenges in modern science is the need to quickly derive knowledge and understanding from large, complex collections of data. We present a new approach that deals with this challenge by combining and extending techniques from high performance visual data analysis and scientific data management. This approach is demonstrated within the context of gaining insight from complex, time-varying datasets produced by a laser wakefield accelerator simulation. Our approach leverages histogram-based parallel coordinates for both visual information display as well as a vehicle for guiding a data mining operation. Data extraction and subsetting are implemented with state-of-the-art index/query technology. This approach, while applied here to accelerator science, is generally applicable to a broad set of science applications, and is implemented in a production-quality visual data analysis infrastructure. We conduct a detailed performance analysis and demonstrate good scalability on a distributed memory Cray XT4 system. © 2008 IEEE.

Plasma-based particle accelerators can produce and sustain thousands of times stronger acceleration fields than conventional particle accelerators, providing a potential solution to the problem of the growing size and cost of conventional particle accelerators. To facilitate scientific knowledge discovery from the ever growing collections of accelerator simulation data generated by accelerator physicists to investigate next-generation plasma-based particle accelerator designs, we describe a novel approach for automatic detection and classification of particle beams and beam substructures due to temporal differences in the acceleration process, here called acceleration features. The automatic feature detection in combination with a novel visualization tool for fast, intuitive, query-based exploration of acceleration features enables an effective top-down data exploration process, starting from a high-level, feature-based view down to the level of individual particles. We describe the application of our analysis in practice to analyze simulations of single pulse and dual and triple colliding pulse accelerator designs, and to study the formation and evolution of particle beams, to compare substructures of a beam, and to investigate transverse particle loss. [ABSTRACT FROM AUTHOR]