An inversion decomposition test based on Monte Carlo response matrix on the γ-ray spectra from NaI(T

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The Na I(Tl) scintillation detector has a number of unique advantages, including wide use, high light yield,and its low price. It is difficult to obtain the decomposition of instrument response spectrum because of limitations associated with the Na I(Tl) scintillation detector’s energy resolution. This paper, based on the physical process of c photons released from decay nuclides, generating an instrument response spectrum, uses the Monte Carlo method to simulate c photons with Na I(Tl) scintillation detector interaction. The Monte Carlo response matrix is established by different single energy γ-rays with detector effects. The Gold and the improved Boosted-Gold iterative algorithms have also been used in this paper to solve the response matrix parameters through decomposing tests,such as simulating a multi-characteristic energy c-ray spectrum and simulating synthesized overlapping peaks cray spectrum. An inversion decomposition of the c instrument response spectrum for measured samples(U series, Th series and U–Th mixed sources, among others)can be achieved under the response matrix. The decomposing spectrum can be better distinguished between the similar energy characteristic peaks, which improve the error levels of activity analysis caused by the overlapping peak with significant effects. The Na I (Tl) scintillation detector has a number of unique advantages, including wide use, high light yield, and its low price. It is difficult to obtain the decomposition of instrument response spectrum because of limitations associated with the Na I (Tl) This paper, based on the physical process of c photons released from decay nuclides, generating an instrument response spectrum, uses the Monte Carlo method to simulate c photons with Na I (Tl) scintillation detector interaction. The Monte Carlo response The Gold and the improved Boosted-Gold iterative algorithms have also been used in this paper to solve the response matrix parameters through decomposing tests, such as simulating a multi-characteristic energy c -ray spectrum and simulating interpreted overlapping peaks cray spectrum. An inversion decomposition of the c instrument response spectrum for measured sampl es (U series, Th series and U-Th mixed sources, among others) can be achieved under the response matrix. The decomposing spectrum can be better distinguished between the similar energy characteristic peaks, which improve the error levels of activity analysis caused by the overlapping peak with significant effects.
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