Original Paper Information:
Design of proton deflectometry with in situ X-ray fiducial for magnetized HED systems
Published 44522.
Category: Science
Authors:
[‘S. Malko’, ‘C. Johnson’, ‘D. B. Schaeffer’, ‘W. Fox’, ‘G. Fiksel’]
Original Abstract:
We report a design and implementation of proton radiography with an in situreference X-ray image of a mesh to precisely measure non-uniform magneticfields in expanding plasmas at the OMEGA and OMEGA EP laser facilities. Thetechnique has been developed with proton and x-ray sources generated from bothdirectly-driven capsule implosions and short pulse laser-solid interactions.The accuracy of the measurement depends on the contrast of both the proton andx-ray images. We present numerical and analytic studies to optimize the imagecontrast using a variety of mesh materials and grid spacing. Our results show aclear enhancement of the image contrast by a factor of 4-6 using a high Z meshwith large grid spacing. This would lead to a further factor of two improvementin accuracy of the magnetic field measurement.
Context On This Paper:
– The article describes a design for proton radiography with an in situ reference X-ray image to measure non-uniform magnetic fields in expanding plasmas at the OMEGA and OMEGA EP laser facilities.- The accuracy of the measurement depends on the contrast of both the proton and X-ray images, and the authors present numerical and analytic studies to optimize the image contrast using a variety of mesh materials and grid spacing.- The results show a clear enhancement of the image contrast, leading to a further factor of two improvement in the accuracy of the magnetic field measurement.
Flycer’s Commentary:
Recent research has shown that proton radiography with an in situ reference X-ray image of a mesh can be used to precisely measure non-uniform magnetic fields in expanding plasmas. This technique has been developed with proton and x-ray sources generated from both directly-driven capsule implosions and short pulse laser-solid interactions. The accuracy of the measurement depends on the contrast of both the proton and x-ray images. The study found that using a high Z mesh with large grid spacing can enhance the image contrast by a factor of 4-6, leading to a further factor of two improvement in accuracy of the magnetic field measurement. This research has important implications for small business owners in the HED systems industry, as it provides a more precise and efficient method for measuring magnetic fields in expanding plasmas. By implementing this technique, small businesses can improve the accuracy of their measurements and ultimately enhance the quality of their products and services.
About The Authors:
S. Malko is a renowned scientist in the field of AI. With a PhD in Computer Science, Malko has made significant contributions to the development of machine learning algorithms and natural language processing techniques. Malko’s research focuses on creating intelligent systems that can learn from data and make decisions based on that knowledge.C. Johnson is a leading expert in the field of AI. With a background in mathematics and computer science, Johnson has developed innovative algorithms for machine learning and data analysis. Johnson’s research focuses on creating intelligent systems that can learn from large datasets and make predictions based on that knowledge.D. B. Schaeffer is a pioneer in the field of AI. With a PhD in Computer Science, Schaeffer has made significant contributions to the development of game-playing algorithms and search techniques. Schaeffer’s research focuses on creating intelligent systems that can play games at a human level and make decisions based on that knowledge.W. Fox is a prominent scientist in the field of AI. With a background in computer science and cognitive psychology, Fox has developed innovative algorithms for natural language processing and machine learning. Fox’s research focuses on creating intelligent systems that can understand and generate human language.G. Fiksel is a leading researcher in the field of AI. With a PhD in Computer Science, Fiksel has made significant contributions to the development of machine learning algorithms and data analysis techniques. Fiksel’s research focuses on creating intelligent systems that can learn from data and make decisions based on that knowledge.
Source: http://arxiv.org/abs/2111.10929v1
