Unfolding of particle spectra

Matzke, M.

doi:10.1117/12.267860

Cited by 35 publications

(20 citation statements)

References 5 publications

(8 reference statements)

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“…Each optimi- The small peaks can be caused by noise in the measurement, approximations in the shape of the peaks, or by the optimization procedure. 8 These small peaks are not relevant for our investigation. Figure 2 shows the progress of an optimization routine.…”

Section: ͑1͒mentioning

confidence: 95%

Finding mechanisms responsible for the spectral distribution of electron beams produced by a linear accelerator

Kok

Welleweerd

1999

Medical Physics

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The measured electron spectra of linear accelerators from several manufacturers differ in comparison to the spectral form and width. As part of our investigations of linac performance and stability, we analyzed the electron spectra of our linacs. After building a spectrometer the electron spectra were measured. The measured spectral widths were comparable with the results published in the literature. It appeared that the phase of the recycled radio pulse in combination with the limited bandwidth of the bending magnet are responsible for unusual (multipeak) electron spectra. The scatter filters only have a relatively small widening effect on the spectrum. There was no indication that multipeak or wide spectra are related to linac instabilities.

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Section: ͑1͒mentioning

confidence: 95%

Finding mechanisms responsible for the spectral distribution of electron beams produced by a linear accelerator

Kok

Welleweerd

1999

Medical Physics

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“…We assess the performance of proposed algorithm (referred to as MCMC in the remainder of the paper) with GRAVEL [9], [41], [47], Tik (Tikhonov regularization with L-curve method) [39] and PIDAL [36] applied to simulated neutron sources. We consider three sources: 2.5 MeV monoenergetic neutron source, 252 Cf and 241 AmBe.…”

Section: Unfolding Results and Discussionmentioning

confidence: 99%

“…The uncertainty associated with the simulated bins was calculated as the square root of the counts. GRAVEL stopping criterion is either the user-defined chi-squared per degree of freedom (PDF) or the input maximum number of iterations (to stop the algorithm after a given number of iterations if the first criterion is not satisfied yet) [41]. In our case, the number of degrees of freedom is M and the chi-squared-PDF was set to one, while the maximum number of iterations was 6000.…”

Section: Existing Unfolding Approachesmentioning

confidence: 99%

A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators

Zhu

Altmann

Fulvio

et al. 2019

IEEE Trans. Nucl. Sci.

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We propose a hierarchical Bayesian model and stateof-art Monte Carlo sampling method to solve the unfolding problem, i.e., to estimate the spectrum of an unknown neutron source from the data detected by an organic scintillator. Inferring neutron spectra is important for several applications, including nonproliferation and nuclear security, as it allows the discrimination of fission sources in special nuclear material (SNM) from other types of neutron sources based on the differences of the emitted neutron spectra. Organic scintillators interact with neutrons mostly via elastic scattering on hydrogen nuclei and therefore partially retain neutron energy information. Consequently, the neutron spectrum can be derived through deconvolution of the measured light output spectrum and the response functions of the scintillator to monoenergetic neutrons. The proposed approach is compared to three existing methods using simulated data to enable controlled benchmarks. We consider three sets of detector responses. One set corresponds to a 2.5 MeV monoenergetic neutron source and two sets are associated with (energy-wise) continuous neutron sources ( 252 Cf and 241 AmBe). Our results show that the proposed method has similar or better unfolding performance compared to other iterative or Tikhonov regularization-based approaches in terms of accuracy and robustness against limited detection events, while requiring less user supervision. The proposed method also provides a posteriori confidence measures, which offers additional information regarding the uncertainty of the measurements and the extracted information.

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“…It is clear that one cannot cover all the methods that have been proposed, but it is hoped that many of the methods of interest are discussed here. There are a number of articles that give an overview of unfolding in the context of neutron spectrometry (Cross and Ing, 1987;Matzke, 1997;Matzke, 2003;Routti and Sandberg 1985;Sekimoto and Nobuhiro, 1982). Chapter 18 of Ref.…”

Section: Unfolding Methodsmentioning

confidence: 99%

Overview of spectral unfolding techniques and uncertainty estimation

Reginatto

2010

Radiation Measurements

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Unfolding of particle spectra

Cited by 35 publications

References 5 publications

Finding mechanisms responsible for the spectral distribution of electron beams produced by a linear accelerator

Finding mechanisms responsible for the spectral distribution of electron beams produced by a linear accelerator

A Hierarchical Bayesian Approach to Neutron Spectrum Unfolding With Organic Scintillators

Overview of spectral unfolding techniques and uncertainty estimation

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