CDS&E:Noise Reduction Methods for Particle Simulations of Intense Beams in Cyclotrons

越来越多的技术依赖于在加速器中产生高能带电粒子束来进行操作。质子疗法用于癌症治疗和食品辐照以消除病原体是最显着的应用之一。这些成功为粒子加速器的新应用铺平了道路，例如材料科学实验和核废料嬗变，这将需要比目前可用的更强的光束。困难在于，在如此高的束强度下，不能容忍在加速器结构上的束诱导损伤。因此，在整个加速过程中实现高光束质量成为一个关键问题。加速器中的光束动力学是由方程描述的，这些方程只能通过在超级计算机上运行的长时间和昂贵的模拟来精确求解。因此，加速器设计研究涉及耗时，计算机密集型模拟，限制了可以研究的设计方案的范围。该项目通过开发一种数值方法来解决这一限制，该方法将显着减少现有数值代码的运行时间，同时保持高精度。通过加速加速器中的束流动力学模拟，新的求解器将有助于改善下一代高强度加速器的设计优化。本项目的目的是开发新的方法来预测回旋加速器中高强度束流的动力学。束流动力学由Vlasov方程描述，这是一个六维非线性偏微分方程，定量结果只能通过数值模拟得到。基于Particle-In-Cell（PIC）算法的粒子代码已成功用于此目的。尽管如此，这些代码的局限性在于需要跟踪大量的粒子以限制统计误差，这导致了长的运行时间。为了减少运行时间，PI和研究生将为标准PIC算法开发一种基于稀疏网格的新型降噪技术。为了最大限度地利用这项新技术，他们将在稀疏PIC求解器中实现高性能算法，并使用为回旋加速器模拟量身定制的模型简化技术优化稀疏网格。在求解器开发的每个阶段，他们都会将新代码的性能与最先进的代码OPAL进行比较。该代码将提供给主要回旋加速器设施的合作者，以回答有关回旋加速器中高强度束流稳定性的未解决问题，并设计新机器。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

A growing number of technologies rely on the production of energetic beams of charged particles in accelerators for their operation. Proton therapy for cancer treatment and food irradiation to eliminate pathogens are among the most remarkable applications. These successes are paving the way for new applications for particle accelerators, such as materials science experiments and nuclear waste transmutation, which would require much more intense beams than are currently available. A difficulty is that at such high beam intensities, beam induced damages on the accelerator structures cannot be tolerated. Achieving a high beam quality throughout the acceleration process thus becomes a critical issue. The dynamics of beams in accelerators is described by equations which can only be accurately solved with long and expensive simulations run on supercomputers. Accelerator design studies therefore involve time consuming, computer intensive simulations, limiting the range of design options which can be investigated. This project addresses this limitation by developing a numerical method that will significantly reduce the run times of existing numerical codes while maintaining a high level of accuracy. By accelerating beam dynamics simulations in accelerators, the new solver will help improve design optimization for the next generation of high intensity accelerators.The purpose of this project is to develop new methods to predict the dynamics of high intensity beams in cyclotrons. The beam dynamics is described by the Vlasov equation, a six-dimensional nonlinear partial differential equation, and quantitative results can only be obtained through numerical simulation. Particle codes based on the Particle-In-Cell (PIC) algorithm have been successfully used for this purpose. Still, a limitation of these codes is that a large number of particles need to be followed to limit statistical error, which leads to long run times. To reduce run times, the PI and graduate students will develop a novel noise reduction technique for the standard PIC algorithm, based on the use of sparse grids. In order to maximize the leverage from this new technique, they will implement high performance algorithms in their sparse-PIC solver, and optimize the sparse grids using model reduction techniques tailored for cyclotron simulations. At every stage of the development of the solver, they will compare the performance of the new code with the state-of-the-art code OPAL. The code will be available to collaborators at major cyclotron facilities to answer unresolved questions regarding the stability of high intensity beams in cyclotrons and to design new machines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.