High Power Cyclotrons: The Bridge Between Beyond the Standard Model Physics, Computation, and Medical Applications

Abstract

The IsoDAR cyclotron is a 60 MeV cyclotron designed to output lOmA of protons in order to be a driver for a neutrino experiment. Coupling the high flux generated by the IsoDAR system with a kiloton neutrino detector will provide sterile neutrino ex­clusion searches covering anomalous regions indicated by short baseline experiments. Simultaneously, the coupling of a high power target and kiloton detector allows for the investigation of dark matter candidates, namely axion-like particles. We have shown that nuclear excitations within the IsoDAR target create a unique opportunity to produce axions and detect monoenergetic peaks with the nearby kiloton detector. Beyond this, the high power produced by the IsoDAR cyclotron can be used for ap­plications beyond particle physics. The lsoDAR cyclotron accelerates and extracts Ht, which allows the beam to be split downstream, a versatile and important de­velopment to alleviate the problem of producing high-power targets for the medical isotope community. This thesis presents a proposal for production of an more than an order of magnitude higher rates than are available at present for certain highly-need medical isotopes, including Ac-225.

In developing the proof of principle of this state-of-the-art cyclotron, the results in this thesis focus on two points related to the production and transport of ions to the accelerator. The first step was to construct an Ht ion source with the necessary excellent emittance parameters and low contamination of non-Ht ions. In this thesis, we report results from a multi-cusp ion source that meets these requirements and produces a record level of high purity, low emittance Ht current. The second has been to design a radio-frequency quadrupole (RFQ) that will allow for gentle bunching of the high current before injection. This is the first use of axial direct injection with a compact cyclotron. This thesis reports the first application of machine learning to the RFQ design. These tools enable the high currents required by lsoDAR cyclotron, leading to important impact on the accelerator, medical, and physics communities.