A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation...

Area of Science:

• Nuclear Physics
• Spectroscopy
• Computational Physics

Background:

• Coincident counts complicate accurate radiation source quantification in experimental spectroscopy.
• Detection efficiency is often experimentally determined but can be estimated using Monte Carlo methods.
• Traditional Monte Carlo methods overestimate efficiency by neglecting coincident counts from cascade particles.

Purpose of the Study:

• To develop a novel algorithm for "multi-primary coincident counting" to improve Monte Carlo simulations.
• To accurately model a high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy.
• To validate the new algorithm's ability to determine detection efficiency a priori.

Main Methods:

• Development of a "multi-primary coincident counting" algorithm within the Geant4 Monte Carlo toolkit.
• Accurate modeling of a high-purity Germanium detector.
• Validation against experimental ⁶⁰Co gamma-ray spectroscopy data.

Main Results:

• The developed algorithm accurately accounts for coincident counts, reducing overestimation of detection efficiency.
• Simulated pulse height spectra showed good qualitative agreement with experimental measurements.
• The algorithm provides a priori determination of detection efficiency.

Conclusions:

• The novel "multi-primary coincident counting" algorithm enhances Monte Carlo simulations for radiation spectroscopy.
• This method offers a more accurate determination of detection efficiency, especially in complex radiation fields.
• The algorithm has potential applications in nuclear fission and spent nuclear fuel analysis.