Abstract
A computational method in the modelling of neutron beams is described that blends neutron acceptance diagrams, GPU-based Monte-Carlo sampling, and a Bayesian approach to efficiency. The resulting code reaches orders of magnitude improvement in performance relative to existing methods. For example, data rates similar to world-leading, real instruments can be achieved on a 2017 laptop, generating 10 6 neutrons per second at the sample position of a high-resolution small angle scattering instrument. The method is benchmarked, and is shown to be in agreement with previous work. Finally, the method is demonstrated on a mature instrument design, where a sub-second turnaround in an interactive simulation process allows the rapid exploration of a wide range of options. This results in a doubling of the design performance, at the same time as reducing the hardware cost by 40%.
Highlights
Neutron scattering facilities such as the European Spallation Source (ESS) currently under construction in Lund, Sweden, and the world-leading Institut Laue Langevin (ILL) in Grenoble, France, rely increasingly upon beam simulations to steer the evolution of the design of their instruments
The principle was computationally automated for monochromatic beams in a previous technique called neutron acceptance diagram shading (NADS) [6]
The initial phase space volume is calculated from the same double triangle method as for standard computational acceptance diagrams [6], except that the trajectory “source” phase space is computed at the sample end with the guide exit geometry
Summary
Neutron scattering facilities such as the European Spallation Source (ESS) currently under construction in Lund, Sweden, and the world-leading Institut Laue Langevin (ILL) in Grenoble, France, rely increasingly upon beam simulations to steer the evolution of the design of their instruments. A new software methodology and tool for the design of neutron guides is described, called “Sandman” It is currently available on GitHub [4], and offers significant computing speed improvements over the existing codes. The principle was computationally automated for monochromatic beams in a previous technique called neutron acceptance diagram shading (NADS) [6] It provided a significant performance gain for the simulation of high resolution instruments, which would normally take several hours on large computing clusters using 3D Monte-Carlo approaches. The developments that enabled a successful project this time, starting in 2018, are a combination of easy access to good pseudo-random number generators on the GPU; an increasingly large memory bandwidth driven by the hardware needs of the 3D game industry; multiple GB of GPU memory being available; and mature, parallel methods to reduce large arrays of data The speed of this code brings great utility. From the perspective of the guide designer, running a white beam simulation is essentially instantaneous
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
