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Abstract Perfect vortex (PV) beams possessing annular intensity profiles independent of topological charges promise significant advances in particle manipulation, fiber communication, and quantum optics. The PV beam is typically generated from the Fourier transformation of the Bessel–Gauss beam. However, the conventional method to produce PV beams requires a series of bulky optical components, which greatly increases the system complexity and also hinders the photonic device integration. Here, plasmonic metasurfaces made of rectangular‐hole nanoantennas as integrated beam converters are designed and demonstrated to generate focused 3D PV beams in a broad wavelength range, by combining the phase profiles of axicon, spiral phase plate, and Fourier transform lens simultaneously based on the Pancharatnam–Berry phase. It is demonstrated that the PV beam structures can be adjusted by varying several control parameters in the metasurface design. Moreover, multiple PV beams with arbitrary arrangement and topological charges are also produced. These results have the promising potential for enabling new types of compact optical devices for tailoring complex light beams and advancing metasurface‐based functional integrated photonic chips.
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Order-of-magnitude beam current improvement in compact cyclotrons
Abstract There is great need for high intensity proton beams from compact particle accelerators in particle physics, medical isotope production, and materials- and energy-research. To address this need, we present, for the first time, a design for a compact isochronous cyclotron that will be able to deliver 10 mA of 60 MeV protons—an order of magnitude higher than on-market compact cyclotrons and a factor four higher than research machines. A key breakthrough is that vortex motion is incorporated in the design of a cyclotron, leading to clean extraction. Beam losses on the septa of the electrostatic extraction channels stay below 120 W (40% below the required safety limit), while maintaining good beam quality. We present a set of highly accurate particle-in-cell simulations, and an uncertainty quantification of select beam input parameters using machine learning, showing the robustness of the design. This design can be utilized for beams for experiments in particle and nuclear physics, materials science and medical physics as well as for industrial applications.
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- Award ID(s):
- 1912764
- PAR ID:
- 10363284
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- New Journal of Physics
- Volume:
- 24
- Issue:
- 2
- ISSN:
- 1367-2630
- Page Range / eLocation ID:
- Article No. 023038
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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