Convergence of unfolded spectrum with response function for single radiation based on Bayes' theorem

Nauchi, Yasushi; Iwasaki, S.

doi:10.1016/j.nima.2013.09.064

Cited by 11 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) It never gives unfolded results having a negative value. (3) It does not require any constraint like an initial guess [10].…”

Section: Spectrum-type Bayesian Estimation Methodsmentioning

confidence: 99%

“…We describe the evaluation process of the response function in Equation (10) in this section, focusing on a 1-MeV X-ray source as an example. The maximum energy of the response function is, therefore, set to 1 MeV to cover X-rays emitted from the 1-MeV X-ray source.…”

Section: Evaluation Of Response Function K·r·fmentioning

confidence: 99%

“…Figure 6 shows an X-ray energy spectrum, φ(E j ), estimated for 0 • . The spectrum estimation was done with the spectrum-type Bayesian estimation method from the measured attenuation curve in Figure 5 as y in Equation (10). As an initial guess, a white spectrum was used.…”

Section: Measurement Of X-ray Energy Spectrum 51 Measurement Of Attmentioning

confidence: 99%

See 2 more Smart Citations

Development of precise energy spectrum measurement technique for high-power pulsed X-ray sources for industrial use

Takagi

Murata

2015

Journal of Nuclear Science and Technology

View full text Add to dashboard Cite

It is difficult to obtain an accurate energy spectrum by measurement for X-rays which are produced by linear accelerators because so many photons are emitted within a very short period and the photons have energies in a wide range. In order to solve the problem, we developed a new technique utilizing the Bayesian estimation method combined with attenuation curve measurement using a step-shaped attenuation material. We experimentally confirmed the validity of the presented technique for an X-ray computed tomography (CT) system. By using the accurate energy information of emitted X-rays obtained by the developed technique, the quality of non-destructive inspection images can be expected to be improved for industrial X-ray radiography, X-ray CT and so on, using high-power X-ray sources.

show abstract

“…(2) It never gives unfolded results having a negative value. (3) It does not require any constraint like an initial guess [10].…”

Section: Spectrum-type Bayesian Estimation Methodsmentioning

confidence: 99%

Section: Evaluation Of Response Function K·r·fmentioning

confidence: 99%

See 1 more Smart Citation

Development of precise energy spectrum measurement technique for high-power pulsed X-ray sources for industrial use

Takagi

Murata

2015

Journal of Nuclear Science and Technology

View full text Add to dashboard Cite

show abstract

“…(2.8), the initial distribution, C (0) i , can be set as the measured E i in the double-bunch distribution, or simply be set as a uniform distribution as described in ref. [24]. According to the convergence theory of iterative algorithm, the final convergent distribution is independent of the starting distribution, so the double-bunch distribution is set as the starting distribution in this unfolding research.…”

Section: Iterative Algorithm Based On Bayes' Theorem For Unfolding To...mentioning

confidence: 99%

“…The proof of the convergence of this iterative Bayesian unfolding method has been given in ref. [24] in an analytical way with the concept of Kullback-Leibler divergence.…”

Section: Iterative Algorithm Based On Bayes' Theorem For Unfolding To...mentioning

confidence: 99%

Double-bunch unfolding methods for the Back-n white neutron source at CSNS

Wang¹,

Li²,

Ruan³

et al. 2020

J. Inst.

View full text Add to dashboard Cite

A: The Back-n white neutron source at China Spallation Neutron Source (CSNS) is designed specifically for nuclear data measurements and multidisciplinary neutron applications. The time of flight (TOF) method is deployed to obtain a high resolution of neutron energy. In the normal operation mode of CSNS there are two proton bunches with a time interval of 410 ns in each pulse which has a repetition frequency of 25 Hz. Due to the superposition of the event distributions corresponding to two bunches, the resolution of the TOF measurement at Back-n will be degraded by the double-bunch characteristics if the measured event distribution is used directly without unfolding, especially in the higher neutron energy region. To nearly recover the event distribution corresponding to a single proton bunch, the unfolding methods have been developed to obtain better time resolution and energy resolution. Two kinds of unfolding algorithms based on the iterative Bayesian method and the iterative event re-distribution method, respectively, have been developed and tested with simulated data and experimental data. The developed methods have shown nice performance in unfolding the double-bunch event distributions with high accuracy and fast convergence. With the deploying of the unfolding methods, the data of the first batch experiments conducted at Back-n in the normal double-bunch mode were analyzed and nearly the same time resolution as in the case of the single-bunch mode has been obtained. K: Analysis and statistical methods; Data processing methods

show abstract

Experimental verification of real-time gamma-ray energy spectrum and dose monitor

Nishimura

Shinohara

Miyoshi

et al. 2022

Applied Radiation and Isotopes

View full text Add to dashboard Cite

Convergence of unfolded spectrum with response function for single radiation based on Bayes' theorem

Cited by 11 publications

References 5 publications

Development of precise energy spectrum measurement technique for high-power pulsed X-ray sources for industrial use

Development of precise energy spectrum measurement technique for high-power pulsed X-ray sources for industrial use

Double-bunch unfolding methods for the Back-n white neutron source at CSNS

Experimental verification of real-time gamma-ray energy spectrum and dose monitor

Contact Info

Product

Resources

About