2019
DOI: 10.1088/1741-4326/aafe30
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Radiography of direct drive double shell targets with hard x-rays generated by a short pulse laser

Abstract: Direct drive implosion experiments of a cone inserted double shell target were carried out at the SG-II Upgrade laser facility. Time-resolved radiographic images of the targets were obtained with hard x-rays generated by irradiating a short-pulse laser on a metal microwire embedded in a low-Z substrate. Since the SG-II Upgrade laser facility is mainly designed for indirect drive, it will lead to high direct illumination nonuniformity of the target surface. 2D nonuniformities of the inner shell were clearly sho… Show more

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Cited by 15 publications
(8 citation statements)
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“…This algorithm also aims at minimizing an objective function which is known as squared error function, given by : ||x i -v j || is the Euclidean distance between x i -v j, Ci is the number of data points in ith cluster, C is the number of cluster center’s, convolution neural network which is a type of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex. Convolution is the first step in the process that convolution neural network undergoes (Zhang et al 2019 ) where (f*g)(t) = functions that are being convoluted, t = real number variable of functions f and g, g( ) = convolution of time function, = first derivative of tau function, a recurrent neural network which is used for handling sequential data and its formula in which h(t) is a function f of the previously hidden state h(t − 1) and the current input x(t). The theta are the parameters of the function f is (Yang et al 2020 ) …”
Section: Methodsmentioning
confidence: 99%
“…This algorithm also aims at minimizing an objective function which is known as squared error function, given by : ||x i -v j || is the Euclidean distance between x i -v j, Ci is the number of data points in ith cluster, C is the number of cluster center’s, convolution neural network which is a type of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex. Convolution is the first step in the process that convolution neural network undergoes (Zhang et al 2019 ) where (f*g)(t) = functions that are being convoluted, t = real number variable of functions f and g, g( ) = convolution of time function, = first derivative of tau function, a recurrent neural network which is used for handling sequential data and its formula in which h(t) is a function f of the previously hidden state h(t − 1) and the current input x(t). The theta are the parameters of the function f is (Yang et al 2020 ) …”
Section: Methodsmentioning
confidence: 99%
“…Then, these electrons can generate X-rays through betatron radiation [2] , inverse Compton scattering [3][4][5] , and bremsstrahlung [6] , thus providing tabletop complements to large-scale conventional accelerator-based X-ray sources. These X-rays sources have advantages of femtosecond duration, micron source size, wide spectral range [7] , thus have tremendous potentials for applications [8] , e.g., biology radiagraphy [9] , non-destructive testing [10,11] , and high-energy-density physics [12,13] .…”
Section: Introductionmentioning
confidence: 99%
“…Laser Fusion Research Center, CAEP, Mianyang, Sichuan, 621900, China. Email: zhaozongqing99@caep.ac.cn the X-ray spectrum characterizes the electron dynamics in plasma [4,5,15,16] and is useful for the applications [13] . There are multiple types of spectrometers have been developed to cover the photon energies ranging from a few keV to tens of MeV in laser-plasma experiments.…”
Section: Introductionmentioning
confidence: 99%
“…X-ray sources have many applications in fields such as radiography [1], nondestructive testing (NDT) [2][3] and plasma hydrodynamic diagnostics [4] [5]. Laserplasma-based X-ray sources have attracted considerable attention in recent years owing to their compact size, short duration and broadband spectrum [6] [7][8] [9].…”
Section: Introductionmentioning
confidence: 99%