Expanding the capabilities of neutron scattering simulation software to support the design of the European Spallation Source and its instruments

In material science, the most popular method for obtaining information about the atomic structure of condensed matter is arguably X-ray scattering, but there are weaknesses such as low sensitivity to hydrogen and heating of the sample from the powerful beam that makes the complementary technique of neutron scattering crucial. In the field of neutron scattering, beams of neutrons are used to investigate matter at the length scale of interatomic distances and at an energy scale that matches excitations in crystals. The European Spallation Source (ESS) aims to produce the world's brightest neutron source and is under construction in Lund, Sweden. The design of the neutron source and scattering instruments have all relied on computer simulations to maximize the capabilities afforded by this large investment. When I joined the field, the McStas Monte Carlo ray-tracing package was well established for instrument design. The focus of my career has been to improve its fidelity and usability with the aim of expanding the scope of the package beyond design of instruments. I created a system for simulating complex samples and sample environments with modularity for both the geometry and underlying physics. This contribution allowed for a completely new level of fidelity in McStas and opened new use-cases such as design of sample environments and replication of troublesome spurions from multiple scattering. I added a Python API allowing McStas to be used with modern scientific software and better suit new generations of scientists who are more likely to know Python than C which is used for the existing interface. I wrote tools such as an automatic optimizer of neutron guide systems that can handle tasks over great ranges of complexity and size. This had a large impact on the ESS when an opportunity arose for changing the source to achieve a higher brightness, at the cost of a smaller surface area. With my tools I could reoptimize guides for most of the instruments, and thus provide a large part of the data necessary for an informed decision on the source dimensions. I have chosen the path of a support scientist, and in this talk I will share my experience in this gratifying and important role.