Yanbiao Zhang | Searcharxiv

arXiv2025

Compton Edge Convolutional Model and Algorithm for Energy-channel Calibration

Scintillation detectors are essential tools for radiation measurement, but calibrating them accurately can be challenging, especially when full-energy peaks are not prominent. This is common in detectors like plastic scintillators. Current methods for calibrating these detectors often require manual adjustments. To address this, we propose a new method called the convolution model. This model accurately calibrates the energy-channel relationship of the Compton edge in various detectors. We tested it with plastic scintillator BC408, NaI crystal, and LaBr$_3$ crystal. Using ${}^{137}$Cs radioactive sources, we calibrated NaI and LaBr$_3$ detectors using full-energy peaks, then applied the convolution model to fit the Compton edge. Our results show errors within 1\% when compared to full-energy peak calibration.

physics.ins-det↗

arXiv2025

The Automatic Calibration Method of the Compton Edge Based on Normalized Cross-correlation and Simulated Annealing Algorithm

Accurate energy channel calibration in scintillation detectors is essential for reliable radiation detection across nuclear physics, medical imaging, and environmental monitoring. Organic scintillators like BC408 and EJ309 lack full-energy peaks, making their Compton edge a critical calibration alternative where traditional peak methods fail. Existing Compton edge identification techniques - Gaussian fitting for the 50%-70% amplitude point, first derivative minimum detection, and Monte Carlo simulation - suffer significant degradation from low count rates, spectral overlap, and subjective interval selection. For the first time, we propose an automated calibration procedure based on Normalized Cross-Correlation (NCC), Simulated Annealing (SA), and a convolutional response model to address these issues. This method automates the selection of the Compton edge interval through NCC-based matching, utilizes SA for global parameter optimization, and then employs a convolutional model for precise matching. Experiments involving the irradiation of organic scintillators (BC408, EJ309) and inorganic scintillators (NaI:Tl, LaBr3:Ce) with 137Cs, 22Na, 54Mn, and 60Co radiation sources demonstrate that this method achieves accuracy commensurate with full-energy peak calibration method (cosine similarity >99.999%) and exhibits superior stability compared to the two traditional methods. In the extreme cases of spectral overlap and low count rate, the average errors of this method are 19.77% and 15.65% of those from the two traditional methods in BC408, 56.44% and 33.15% of those from the two traditional methods in EJ309. This work advances detector calibration and offers a scalable, automated solution for high-energy experiments and portable devices.

physics.ins-det↗