PC spectra analysis of L-shell copper X-pinch plasma produced by the compact generator of Ecole polytechnique

Yilmaz, M.F.; Danışman, Yusuf; Larour, Jean; Aranchuk, L.E.

doi:10.1063/1.4975726

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…This shows that addition of electron beams stimulate collective behavior. Such V-shapes are observed in coronal bursts and described by the two stream instability due to collective and hybrid nature of photon and plasmon interactions [24]. Gedik et al, 2016 illustared experimentally periodic V shape like Dirac cones was due to the interaction of photons with the free electrons (plasmons) of the Floquet-Bloch states of topological insulators.…”

Section: B Pca Analysis Of L Shell Mo Synthetic Databasementioning

confidence: 99%

“…Normalized XRD Signals this work, the fraction f of hot electrons was described by a Gaussian distribution centered at the characteristic energy E 0 = 5 keV. [12,13]. Voigt profiles with the resolution of d = 500 were used to fit line broadening of the experimental spectra [17].…”

Section: Normalized Electric Recordsmentioning

confidence: 99%

“…Stokes I represents the unpolarized light, Q and U represent linearly polarized light, and V represents the circulary polarized light [23]. Since PCA can represent the database in a scalar and vectoral manner, one can easily observe the direction change of the spectral lines in vectoral representation of the spectral database [24]. Paletou et al, 2012 showed that PCA is an efficient tool to extract Stokes parameters of the polarized stellar data [25].…”

Section: B Pca Analysis Of L Shell Mo Synthetic Databasementioning

confidence: 99%

“…It has been used in many fields like robotics, medicine, remote sensing and so on. PCA has also many applications in spectroscopy, especially in unmixing species and decomposing overlapped spectral lines of UV-VIS-NIR spectroscopy, which is critical for spectral fingerprinting [12][13]. Artificial neural network (ANN), in simple terms, is a well-known machine learning algorithm that uses examples to extract rules.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition

Yilmaz

Danışman

Özdemir

et al. 2019

Matter and Radiation at Extremes

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In this paper, the effects of electron beam on the X pinch produced spectra of L-shell Mo plasma have been investigated by principal component analysis (PCA), and this analysis is compared with that of line ratio diagnostics. Spectral database for PCA extraction was arranged using the non-LTE collisional radiative L-shell Mo model. PC vector spectra of L shell Mo including F, Ne, Na and Mg-like transitions were studied to investigate the polarization types of these transitions. PC1 vector spectra of F, Ne, Na and Mg-like transitions resulted in linear polarization of Stokes Q profiles. Besides, PC2 vector spectra showed linear polarization of Stokes U profiles of 2p 5 3s of Ne like transitions which were recognized as responsive to the magnetic field (Trabert et al., 2017). 3D representation of PCA coefficients demonstrated that addition of electron beam to the non-LTE model generates the quantized collective clusters which are translations of each other and follow Vshaped cascade trajectories except for the case f = 0.0. The extracted principal coefficients were used as a database for the Artifical Neural Network (ANN) to estimate the plasma electron temperature, density and beam fractions of time integrated spatially resolved L-shell Mo X-pinch plasma spectrum. PCA based ANN provides advantage in reducing the network topology with a more efficient Backpropagation supervised learning algorithm. The modeled plasma electron temperature is about T e~6 60 eV and density n e =1x10 20 cm -3 in the presence of the fraction of the beams with f~0.1 and centered energy of 5 keV.

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Section: B Pca Analysis Of L Shell Mo Synthetic Databasementioning

confidence: 99%

Section: Normalized Electric Recordsmentioning

confidence: 99%

Section: B Pca Analysis Of L Shell Mo Synthetic Databasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition

Yilmaz

Danışman

Özdemir

et al. 2019

Matter and Radiation at Extremes

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Advanced data analysis in inertial confinement fusion and high energy density physics

Knapp

Lewis

2023

Review of Scientific Instruments

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Bayesian analysis enables flexible and rigorous definition of statistical model assumptions with well-characterized propagation of uncertainties and resulting inferences for single-shot, repeated, or even cross-platform data. This approach has a strong history of application to a variety of problems in physical sciences ranging from inference of particle mass from multi-source high-energy particle data to analysis of black-hole characteristics from gravitational wave observations. The recent adoption of Bayesian statistics for analysis and design of high-energy density physics (HEDP) and inertial confinement fusion (ICF) experiments has provided invaluable gains in expert understanding and experiment performance. In this Review, we discuss the basic theory and practical application of the Bayesian statistics framework. We highlight a variety of studies from the HEDP and ICF literature, demonstrating the power of this technique. Due to the computational complexity of multi-physics models needed to analyze HEDP and ICF experiments, Bayesian inference is often not computationally tractable. Two sections are devoted to a review of statistical approximations, efficient inference algorithms, and data-driven methods, such as deep-learning and dimensionality reduction, which play a significant role in enabling use of the Bayesian framework. We provide additional discussion of various applications of Bayesian and machine learning methods that appear to be sparse in the HEDP and ICF literature constituting possible next steps for the community. We conclude by highlighting community needs, the resolution of which will improve trust in data-driven methods that have proven critical for accelerating the design and discovery cycle in many application areas.

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Investigation of electron beam effects on L shell Mo plasma produced by a compact LC generator using pattern recognition

Yilmaz

Danışman

Özdemir

et al. 2018

Preprint

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PC spectra analysis of L-shell copper X-pinch plasma produced by the compact generator of Ecole polytechnique

Cited by 3 publications

References 3 publications

Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition

Investigation of electron beam effects on L-shell Mo plasma produced by a compact LC generator using pattern recognition

Advanced data analysis in inertial confinement fusion and high energy density physics

Investigation of electron beam effects on L shell Mo plasma produced by a compact LC generator using pattern recognition

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