Understanding Gamma Ray Energy Spectra: Smoothing Methods and Algorithms

AI Thread Summary
A smooth gamma ray energy spectrum refers to a refined representation of gamma radiation data that reduces random fluctuations. The gamma spectrum typically follows a Gaussian distribution, particularly noted in radioisotope Cs-137 at the 661 keV energy peak. Smoothing methods, such as those used in Canberra's Genik software, involve averaging data points over a specified range, commonly between 3 to 13 points. The discussion highlights a need for clarity on the algorithms used to achieve this smoothing process. Understanding these algorithms is essential for accurate gamma spectrum analysis.
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Hi every one,
What is the smooth gamma ray energy spectrum in gamma radiation? And, What is the algorithm of smooth gamma spectrum?
Thank every one to much!
 
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Without more context, the question does not make sense.

Do you know what a smooth spectrum in general is? If not, you can look it up.
You probably have something that produces such a smooth spectrum.
 
The gamma ray spectrum depends on the process giving rise to the gamma rays.
 
Thank you,
Gamma spectrum of radioisotope cs-137, at 661 keV energy peak, is the Gaussian distribution. In order to decrease the random data fluctuations, it is necessary to smooth the gamma spectrum. For Genik software of Canberra, the smoothing methods is smoothing with different quantity points, from 3 points to 13 points. I don't understand what is alogrithm to get one.
Thank you too much!
 
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