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Journal article

Quantitative shadowgraphy and proton radiography for large intensity modulations

Abstract:
Shadowgraphy is a technique widely used to diagnose objects or systems in various fields in physics and engineering. In shadowgraphy, an optical beam is deflected by the object and then the intensity modulation is captured on a screen placed some distance away. However, retrieving quantitative information from the shadowgrams themselves is a challenging task because of the non-linear nature of the process. Here, a novel method to retrieve quantitative information from shadowgrams, based on computational geometry, is presented for the first time. This process can also be applied to proton radiography for electric and magnetic field diagnosis in high-energy-density plasmas and has been benchmarked using a toroidal magnetic field as the object, among others. It is shown that the method can accurately retrieve quantitative parameters with error bars less than 10%, even when caustics are present. The method is also shown to be robust enough to process real experimental results with simple pre- and post-processing techniques. This adds a powerful new tool for research in various fields in engineering and physics for both techniques.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1103/PhysRevE.95.023306

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Physics - Central
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atomic & Laser Physics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atomic & Laser Physics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atomic & Laser Physics
Role:
Author




Pubs id:
pubs:680862
UUID:
uuid:a2487e75-7703-4bd9-8d8f-e9ddc546cec9
Local pid:
pubs:680862
Source identifiers:
680862
Deposit date:
2017-02-21

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