8 Matching Results

Search Results

Advanced search parameters have been applied.

Automated analysis for detecting beams in laser wakefield simulations

Description: Laser wakefield particle accelerators have shown the potential to generate electric fields thousands of times higher than those of conventional accelerators. The resulting extremely short particle acceleration distance could yield a potential new compact source of energetic electrons and radiation, with wide applications from medicine to physics. Physicists investigate laser-plasma internal dynamics by running particle-in-cell simulations; however, this generates a large dataset that requires time-consuming, manual inspection by experts in order to detect key features such as beam formation. This paper describes a framework to automate the data analysis and classification of simulation data. First, we propose a new method to identify locations with high density of particles in the space-time domain, based on maximum extremum point detection on the particle distribution. We analyze high density electron regions using a lifetime diagram by organizing and pruning the maximum extrema as nodes in a minimum spanning tree. Second, we partition the multivariate data using fuzzy clustering to detect time steps in a experiment that may contain a high quality electron beam. Finally, we combine results from fuzzy clustering and bunch lifetime analysis to estimate spatially confined beams. We demonstrate our algorithms successfully on four different simulation datasets.
Date: July 3, 2008
Creator: Ushizima, Daniela M.; Rubel, Oliver; Prabhat, Mr.; Weber, Gunther H.; Bethel, E. Wes; Aragon, Cecilia R. et al.
Partner: UNT Libraries Government Documents Department

High Performance Multivariate Visual Data Exploration for Extremely Large Data

Description: 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.
Date: August 22, 2008
Creator: Rubel, Oliver; Wu, Kesheng; Childs, Hank; Meredith, Jeremy; Geddes, Cameron G.R.; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

Application of High-performance Visual Analysis Methods to Laser Wakefield Particle Acceleration Data

Description: Our work combines and extends techniques from high-performance scientific data management and visualization to enable scientific researchers to gain insight from extremely large, complex, time-varying laser wakefield particle accelerator simulation data. We extend histogram-based parallel coordinates for use in visual information display as well as an interface for guiding and performing data mining operations, which are based upon multi-dimensional and temporal thresholding and data subsetting operations. To achieve very high performance on parallel computing platforms, we leverage FastBit, a state-of-the-art index/query technology, to accelerate data mining and multi-dimensional histogram computation. We show how these techniques are used in practice by scientific researchers to identify, visualize and analyze a particle beam in a large, time-varying dataset.
Date: August 28, 2008
Creator: Rubel, Oliver; Prabhat, Mr.; Wu, Kesheng; Childs, Hank; Meredith, Jeremy; Geddes, Cameron G.R. et al.
Partner: UNT Libraries Government Documents Department

FastBit: Interactively Searching Massive Data

Description: As scientific instruments and computer simulations produce more and more data, the task of locating the essential information to gain insight becomes increasingly difficult. FastBit is an efficient software tool to address this challenge. In this article, we present a summary of the key underlying technologies, namely bitmap compression, encoding, and binning. Together these techniques enable FastBit to answer structured (SQL) queries orders of magnitude faster than popular database systems. To illustrate how FastBit is used in applications, we present three examples involving a high-energy physics experiment, a combustion simulation, and an accelerator simulation. In each case, FastBit significantly reduces the response time and enables interactive exploration on terabytes of data.
Date: June 23, 2009
Creator: Wu, Kesheng; Ahern, Sean; Bethel, E. Wes; Chen, Jacqueline; Childs, Hank; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

Laser Plasma Particle Accelerators: Large Fields for Smaller Facility Sources

Description: Compared to conventional particle accelerators, plasmas can sustain accelerating fields that are thousands of times higher. To exploit this ability, massively parallel SciDAC particle simulations provide physical insight into the development of next-generation accelerators that use laser-driven plasma waves. These plasma-based accelerators offer a path to more compact, ultra-fast particle and radiation sources for probing the subatomic world, for studying new materials and new technologies, and for medical applications.
Date: March 20, 2009
Creator: Geddes, Cameron G.R.; Cormier-Michel, Estelle; Esarey, Eric H.; Schroeder, Carl B.; Vay, Jean-Luc; Leemans, Wim P. et al.
Partner: UNT Libraries Government Documents Department

Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data

Description: 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.
Date: June 8, 2010
Creator: Rubel, Oliver; Ahern, Sean; Bethel, E. Wes; Biggin, Mark D.; Childs, Hank; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

Occam's Razor and Petascale Visual Data Analysis

Description: One of the central challenges facing visualization research is how to effectively enable knowledge discovery. An effective approach will likely combine application architectures that are capable of running on today?s largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena.
Date: June 12, 2009
Creator: Bethel, E. Wes; Johnson, Chris; Ahern, Sean; Bell, John; Bremer, Peer-Timo; Childs, Hank et al.
Partner: UNT Libraries Government Documents Department

Computational studies and optimization of wakefield accelerators

Description: Laser- and particle beam-driven plasma wakefield accelerators produce accelerating fields thousands of times higher than radio-frequency accelerators, offering compactness and ultrafast bunches to extend the frontiers of high energy physics and to enable laboratory-scale radiation sources. Large-scale kinetic simulations provide essential understanding of accelerator physics to advance beam performance and stability and show and predict the physics behind recent demonstration of narrow energy spread bunches. Benchmarking between codes is establishing validity of the models used and, by testing new reduced models, is extending the reach of simulations to cover upcoming meter-scale multi-GeV experiments. This includes new models that exploit Lorentz boosted simulation frames to speed calculations. Simulations of experiments showed that recently demonstrated plasma gradient injection of electrons can be used as an injector to increase beam quality by orders of magnitude. Simulations are now also modeling accelerator stages of tens of GeV, staging of modules, and new positron sources to design next-generation experiments and to use in applications in high energy physics and light sources.
Date: June 16, 2008
Creator: Tsung, Frank S.; Bruhwiler, David L.; Cary, John R.; Esarey, Eric H.; Mori, Warren B.; Vay, Jean-Luc et al.
Partner: UNT Libraries Government Documents Department