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29 August 2017 Simulation and optimization of a soft gamma-ray concentrator using thin film multilayer structures
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We are reporting the investigation result of using multilayer thin film structures for channeling and concentrating soft gamma rays with energies greater than 100 keV, beyond the reach of current grazing-incidence hard X-ray mirrors. This will enable future telescopes for higher energies with same mission parameters already proven by NuSTAR. A suitable arrangement of bent multilayer structures of alternating low and high-density materials will channel soft gamma-ray photons via total external reflection and then concentrate the incident radiation to a point. We present the latest results of producing Ir/Si and W/Si multilayers with the required thicknesses and smoothness by using magnetron sputter technique. In addition to experimental works, we have been working on gamma-ray tracking model of the concentrator by IDL, making use of optical properties calculated by the IMD software. This modeling allows us to calculate efficiency and track photon for different energy bands and materials and compare them with experimental result. Also, we describe combine concentrator modeling result and detector simulation by MEGAlib to archive a complete package of gamma-ray telescope simulation. This technology offers the potential for soft gamma-ray telescopes with focal lengths of less than 10 m, removing the need for formation flying spacecraft and providing greatly increased sensitivity for modest cost and complexity and opening the field up to balloon-borne instruments.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Farzane Shirazi, Peter F. Bloser, James E. Krzanowski, Jason S. Legere, and Mark L. McConnell "Simulation and optimization of a soft gamma-ray concentrator using thin film multilayer structures", Proc. SPIE 10399, Optics for EUV, X-Ray, and Gamma-Ray Astronomy VIII, 103991A (29 August 2017);


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