Kwok Ko

Bio: Kwok Ko is an academic researcher from Stanford University. The author has contributed to research in topics: Particle accelerator & International Linear Collider. The author has an hindex of 11, co-authored 39 publications receiving 481 citations.

Advances in Parallel Electromagnetic Codes for Accelerator Science and Development

Abstract: Over a decade of concerted effort in code development for accelerator applications has resulted in a new set of electromagnetic codes which are based on higher-order finite elements for superior geometry fidelity and better solution accuracy. SLAC's ACE3P code suite is designed to harness the power of massively parallel computers to tackle large complex problems with the increased memory and solve them at greater speed. The US DOE supports the computational science R&D under the SciDAC project to improve the scalability of ACE3P, and provides the high performance computing resources needed for the applications. This paper summarizes the advances in the ACE3P set of codes, explains the capabilities of the modules, and presents results from selected applications covering a range of problems in accelerator science and development important to the Office of Science.

Omega3P: A Parallel Finite-Element Eigenmode Analysis Code for Accelerator Cavities

Abstract: Omega3P is a parallel eigenmode calculation code for accelerator cavities in frequency domain analysis using finite-element methods. In this report, we will present detailed finite-element formulations and resulting eigenvalue problems for lossless cavities, cavities with lossy materials, cavities with imperfectly conducting surfaces, and cavities with waveguide coupling. We will discuss the parallel algorithms for solving those eigenvalue problems and demonstrate modeling of accelerator cavities through different examples.

Nonlinear rayleigh-ritz iterative method for solving large scale nonlinear eigenvalue problems

Abstract: A nonlinear Rayleigh-Ritz iterative (NRRIT) method for solving nonlinear eigenvalue problems is studied in this paper. It is an extension of the nonlinear Arnoldi algorithm due to Heinrich Voss. The efficiency of the NRRIT method is demonstrated by comparing with the inverse iteration method to solve a highly nonlinear eigenvalue problem arising from finite element electromagnetic simulation in accelerator modeling.

Adjoint methods for electromagnetic shape optimization of the low-loss cavity for the International Linear Collider

Abstract: We formulate the problem of designing the low-loss cavity for the International Linear Collider (ILC) as an electromagnetic shape optimization problem involving a Maxwell eigenvalue problem. The objective is to maximize the stored energy of a trapped mode in the end cell while maintaining a specified frequency corresponding to the accelerating mode. A continuous adjoint method is presented for computation of the design gradient of the objective and constraint. The gradients are used within a nonlinear optimization scheme to compute the optimal shape for a simplified model of the ILC in a small multiple of the cost of solving the Maxwell eigenvalue problem.

Advanced Visualization Technology for Terascale Particle Accelerator Simulations

Abstract: This paper presents two new hardware-assisted rendering techniques developed for interactive visualization of the terascale data generated from numerical modeling of next-generation accelerator designs. The first technique, based on a hybrid rendering approach, makes possible interactive exploration of large-scale particle data from particle beam dynamics modeling. The second technique, based on a compact texture-enhanced representation, exploits the advanced features of commodity graphics cards to achieve perceptually effective visualization of the very dense and complex electromagnetic fields produced from the modeling of reflection and transmission properties of open structures in an accelerator design. Because of the collaborative nature of the overall accelerator modeling project, the visualization technology developed is for both desktop and remote visualization settings. We have tested the techniques using both time-varying particle data sets containing up to one billion particles per time step and electromagnetic field data sets with millions of mesh elements.

Multiphysics simulations: Challenges and opportunities

Abstract: We consider multiphysics applications from algorithmic and architectural perspectives, where “algorithmic” includes both mathematical analysis and computational complexity, and “architectural” includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

Collaborative visualization: definition, challenges, and research agenda

Abstract: The conflux of two growing areas of technology - collaboration and visualization - into a new research direction, coLLaborative visualization, provides new research chaLLenges TechnoLogy now aLLows us to easily connect and collaborate with one another - in settings as diverse as over networked computers, across mobile devices, or using shared displays such as interactive waLLs and tabletop surfaces Digital information is now reguLarLy accessed by muLtipLe people in order to share information, to view it together, to analyze it, orto form decisions VisuaLizations are used to deal more effectively with Large amounts of information white interactive visuaLizations aLLow users to expLore the underlying data White researchers face many chaLLenges in coLLaboration and in visualization, the emergence of coLLaborative visualization poses additional chaLLenges, but it is also an exciting opportunity to reach new audiences and applications for visualization tooLs and techniques] to provide a definition, clear scope, and overview of the evolving field of coLLaborative visualization, (2) to help pinpoint the unique focus of coLLaborative visualization with its specific aspects, chaLLenges, and requirements within the intersection of generaL computer-supported cooperative work and visualization research, and (3) to draw attention to important future research questions to be addressed by the community We conclude by discussing a research agenda for future work on coLLaborative visualization and urge for a new generation of visuaLization toots that are designed with coLLaboration in mind from their very inception

Space-time density of trajectories: exploring spatio-temporal patterns in movement data

Abstract: Modern positioning and identification technologies enable tracking of almost any type of moving object. A remarkable amount of new trajectory data is thus available for the analysis of various phenomena. In cartography, a typical way to visualise and explore such data is to use a space-time cube, where trajectories are shown as 3D polylines through space and time. With increasingly large movement datasets becoming available, this type of display quickly becomes cluttered and unclear. In this article, we introduce the concept of 3D space-time density of trajectories to solve the problem of cluttering in the space-time cube. The space-time density is a generalisation of standard 2D kernel density around 2D point data into 3D density around 3D polyline data (i.e. trajectories). We present the algorithm for space-time density, test it on simulated data, show some basic visualisations of the resulting density volume and observe particular types of spatio-temporal patterns in the density that are specific to trajectory data. We also present an application to real-time movement data, that is, vessel movement trajectories acquired using the Automatic Identification System (AIS) equipment on ships in the Gulf of Finland. Finally, we consider the wider ramifications to spatial analysis of using this novel type of spatio-temporal visualisation.

The nonlinear eigenvalue problem

Abstract: Nonlinear eigenvalue problems arise in a variety of science and engineering applications and in the past ten years there have been numerous breakthroughs in the development of numerical methods. This article surveys nonlinear eigenvalue problems associated with matrix-valued functions which depend nonlinearly on a single scalar parameter, with a particular emphasis on their mathematical properties and available numerical solution techniques. Solvers based on Newton's method, contour integration, and sampling via rational interpolation are reviewed. Problems of selecting the appropriate parameters for each of the solver classes are discussed and illustrated with numerical examples. This survey also contains numerous MATLAB code snippets that can be used for interactive exploration of the discussed methods.