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ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

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Gamma spectrum stabilization method based on nonlinear least squares optimization.

Ye Chen¹, Jinglun Li¹, Yuzhong Zhang¹

¹State Key Laboratory of NBC Protection for Civilian, Beijing, 102205, China.

Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine

|December 19, 2020

Summary

This summary is machine-generated.

This study introduces a software-only method to stabilize gamma spectrum measurements, correcting spectral drift without hardware adjustments. The approach significantly enhances stabilization accuracy for lengthy measurements.

Keywords:

Nonlinear least squares optimization Scintillation spectrometer Spectrum drift Spectrum reallocation Spectrum stabilization

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Area of Science:

Nuclear Physics
Spectroscopy
Data Analysis

Background:

Lengthy gamma spectrum measurements are susceptible to spectral drift, compromising data accuracy.
Traditional stabilization methods often require hardware adjustments (e.g., high voltage, gain) or peak location, which can be inconvenient.
Drift in gamma spectra can lead to inaccurate results in subsequent analyses.

Purpose of the Study:

To develop and evaluate a convenient, practical, software-only spectrum stabilization method for gamma spectroscopy.
To eliminate the need for hardware adjustments or peak identification in spectrum stabilization.
To improve the accuracy of lengthy gamma spectrum measurements by suppressing spectral drift.

Main Methods:

Gamma energy spectra were recorded in small, consecutive time intervals.
A full spectrum nonlinear optimization technique was employed to estimate drifts relative to a reference spectrum.
Drifted spectra were corrected and accumulated to create a drift-free composite spectrum.

Main Results:

The proposed software-only method effectively suppresses spectral drift in gamma measurements.
Stabilization accuracy was significantly improved compared to methods without this approach.
The technique avoids the need for hardware modifications or manual peak analysis.

Conclusions:

A practical and effective software-only spectrum stabilization method for gamma spectroscopy has been demonstrated.
This approach offers a significant improvement in stabilization accuracy for long-duration measurements.
The method provides a convenient alternative to hardware-based stabilization techniques.