کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5493166 | 1526280 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-dimensional optimization of a terawatt seeded tapered Free Electron Laser with a Multi-Objective Genetic Algorithm
ترجمه فارسی عنوان
بهینه سازی چند بعدی از یک لیزر آزاد الکترونی با یک الگوریتم ژنتیک چند هدفه
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
ابزار دقیق
چکیده انگلیسی
There is a great interest in generating high-power hard X-ray Free Electron Laser (FEL) in the terawatt (TW) level that can enable coherent diffraction imaging of complex molecules like proteins and probe fundamental high-field physics. A feasibility study of producing such X-ray pulses was carried out employing a configuration beginning with a Self-Amplified Spontaneous Emission FEL, followed by a “self-seeding” crystal monochromator generating a fully coherent seed, and finishing with a long tapered undulator where the coherent seed recombines with the electron bunch and is amplified to high power. The undulator tapering profile, the phase advance in the undulator break sections, the quadrupole focusing strength, etc. are parameters to be optimized. A Genetic Algorithm (GA) is adopted for this multi-dimensional optimization. Concrete examples are given for LINAC Coherent Light Source (LCLS) and LCLS-II-type systems. Analytical estimate is also developed to cross check the simulation and optimization results as a quick and complimentary tool.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 846, 21 February 2017, Pages 56-63
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 846, 21 February 2017, Pages 56-63
نویسندگان
Juhao Wu, Newman Hu, Hananiel Setiawan, Xiaobiao Huang, Tor O. Raubenheimer, Yi Jiao, George Yu, Ajay Mandlekar, Simone Spampinati, Kun Fang, Chungming Chu, Ji Qiang,