White Paper on DOE-HEP Accelerator Modeling Science Activities

Objective Toward the goal of maximizing the impact of computer modeling on the design of future particle accelerators and the development of new accelerator techniques & technologies, this white paper presents the rationale for: (a) strengthening and expanding programmatic activities in accelerator modeling science within the Department of Energy (DOE) Office of High Energy Physics (HEP) and (b) increasing the community-wide coordination and integration of code development. Expanding programmatic activities in computational accelerator science Importance of modeling is on the rise-Thanks to sustained advances in hardware and software technologies, computer modeling is playing an increasingly important role in all areas of science and technology, and this trend can be expected to continue for the foreseeable future. In application to the design of particle accelerators, this rise in importance is further fueled by the economic pressure for reducing uncertainties and the costs of development, construction and commissioning of accelerators. In light of this, it is logical to strengthen and expand programmatic activities of particle accelerator modeling within the HEP community. This increased focus on computational activities is all the more timely as computer architectures are transitioning to new technologies [1,2] that require the adaptation of existing-and emergence of new-algorithms and codes [3]. Optimizing resources via a comprehensive and balanced development strategy – Maximizing the overall scientific output per dollar means maximizing the usability of the pool of codes while minimizing spending on code development and support. Maximizing usability involves an aggregate maximization of effectiveness (completeness, accuracy of solution), efficiency (time to solution), and ease of use (learnability, error tolerance, versatility, visibility of functionalities, etc.). Minimizing spending on code development implies the reduction of duplication with commensurate increases in modularity and code interoperability. Optimizing