Computational Accelerator Physics: Advanced Modeling for Next-Generation Accelerator Applications

Research Objectives

The next generation of particle accelerators will require a major advance in numerical modeling capability, due to extremely stringent beam control and beam loss requirements and the presence of highly complex three-dimensional accelerator components. The primary goal of this Grand Challenge is to develop an advanced, parallel modeling capability, based on High Performance Computing and Communications resources and state-of-the-art numerical methods and algorithms, that will enable the design, optimization, and numerical validation of future accelerators.

Computational Approach

A charged particle beam in a high-intensity accelerator is subject to strong linear and nonlinear, internal and external forces. It requires a careful treatment of both magnetic optical effects and space charge effects. The field of magnetic optics has matured greatly with the development of transfer matrix and Lie methods. Similarly, the simulation of space charge effects in plasmas has also matured with the development of the plasma particle-in-cell (PIC) approach and other methods. Our approach is to combine the best features of high-order magnetic optics simulation techniques with PIC simulation techniques in a framework optimized for parallel computations. To accomplish the fusion of these two separate fields, we are using modern split-operator symplectic integration algorithms. We are also optimizing the space charge algorithm, which is the most time-consuming part of high-current beam dynamics simulations, in order to achieve high performance on parallel platforms.

Accomplishments

This past year we developed a parallel version of the code LINAC, which is being used to support the Accelerator Production of Tritium (APT) project. This is now the primary code for performing large-scale beam halo simulations for the project. A primary accomplishment was a 5-fold increase in the performance of the space charge algorithm over our initial implementation.

In addition to LINAC, we developed a new code called IMPACT, which is based on split-operator techniques. IMPACT (Integrated-Map and Particle Accelerator Tracking code) has an especially accurate and efficient treatment of radio frequency accelerating gaps, obtained by numerical integration of the gap transfer map rather than integration of single particle trajectories. The code is especially useful for modeling superconducting proton linear accelerators, where there are only a few types of accelerating cavities.

A third code, called HALO, has been developed specifically for beam halo studies. Beam loss is known to be associated with the very low-density distribution of charge far from the beam core (the halo). This is a major issue for future high intensity LINACs, since the particle loss can lead to activation of accelerator components, thereby hindering or preventing hands-on maintenance. HALO, developed in collaboration with the University of Maryland, includes a new three-dimensional beam equilibrium model, which helps isolate beam halo growth mechanisms.

The huge amount of data in a high-resolution beam dynamics simulation, coupled with the fact that we are often interested in a very small fraction of the particles in the halo, necessitates the use of internal data analysis in our codes prior to storing simulation results. We have developed and implemented algorithms on the T3E that drastically reduce the amount of data needed to visualize the halo.

Significance

The advanced modeling tools developed through this Grand Challenge are an enabling technology that will allow future particle accelerators to be designed with reduced cost and risk and improved reliability and efficiency. The projects that this effort supports will have significant societal, economic, and scientific impacts, including impacts on DOE missions in the offices of Energy Research, Defense Programs, and Environmental Management.

The societal impacts are related to both environmental and national security-related issues. Benefits to the environment are based on the proposed use of accelerators for nuclear waste transmutation and plutonium disposal. Benefits to national defense are based on the use of accelerators for tritium production and Science Based Stockpile Stewardship.

Economic impacts include both energy-related and industrial issues. Accelerator-driven fission energy production schemes have the potential to produce clean, safe energy without critical assemblies and in accord with non-proliferation concerns.

In the area of fundamental science, high-resolution accelerator modeling is crucial to the development of next-generation spallation neutron sources for materials science and biological science research, as well as the design of next-generation accelerators for high energy physics, including linear colliders.

Publication

R. Gluckstern, A. Fedotov, S. Kurennoy, and R. Ryne. N. d. Halos in Beam Bunches with Self-Consistent 6-Dimensional Distributions, Phys. Rev. Lett., submitted.

URL

http://t8web.lanl.gov/people/salman/capgca

Longitudinal phase space of a 3D mismatched beam. The density varies by a factor of 10,000 from the core (blue) to the edge of the halo (red). The system being modeled is a spheroidal bunch, initially a stationary solution of the Vlasov/Poisson equations, which develops a halo due to improper matching into the beamline. The simulation used 25 million particles and a 256 x 256 x 256 grid for the Poisson solver. The figure shows the longitudinal phase space (z, pz) after the halo has formed. It contains approximately 100,000 particles color-coded according to density. In the blue region (the core), the density equals 1 at the center and 1/10 at the blue-green boundary. It decreases through the green, yellow, and red regions, and equals 1/10,000 at the edge of the red region. If we had simply plotted the same number of particles chosen randomly from the 25 million in the simulation, the halo would barely be visible and show almost no structure.