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Register a new userA marine radioisotope gamma-ray spectrum analysis method based on Monte Carlo simulation and MLP neural network
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Wenhan Dai
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The monitoring of Cs-137 in seawater using scintillation detector relies on the spectrum analysis method to extract the Cs-137 concentration. And when in poor statistic situation, the calculation result of the traditional net peak area (NPA) method has a large uncertainty. We present a machine learning based method to better analyze the gamma-ray spectrum with low Cs-137 concentration. We apply multilayer perceptron (MLP) to analyze the 662 keV full energy peak of Cs-137 in the seawater spectrum. And the MLP can be trained with a few measured background spectrums by combining the simulated Cs-137 signal with measured background spectrums. Thus, it can save the time of preparing and measuring the standard samples for generating the training dataset. To validate the MLP-based method, we use Geant4 and background gamma-ray spectrums measured by a seaborne monitoring device to generate an independent test dataset to test the result by our method and the traditional NPA method. We find that the MLP-based method achieves a root mean squared error of 0.159, 2.3 times lower than that of the traditional net peak area method, indicating the MLP-based method improves the precision of Cs-137 concentration calculation
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Ultracold neutrons (UCN) with kinetic energies up to 300 neV can be stored in material or magnetic confinements for hundreds of seconds. This makes them a very useful tool for probing fundamental symmetries of nature, by searching for charge-parity violation by a neutron electric dipole moment, and yielding important parameters for Big Bang nucleosynthesis, e.g. in neutron-lifetime measurements. Further increasing the intensity of UCN sources is crucial for next-generation experiments. Advanced Monte Carlo (MC) simulation codes are important in optimization of neutron optics of UCN sources and of experiments, but also in estimation of systematic effects, and in bench-marking of analysis codes. Here we will give a short overview of recent MC simulation activities in this field.
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