Application of artificial neural networks to the inversion of positron lifetime spectrum

doi:10.1088/1674-1056/21/11/117803

Abstract A new method of processing positron annihilation lifetime spectra is proposed. It is based on an artificial neural network (ANN)-back propagation network (BPN). By using data from simulated positron lifetime spectra which are generated by a simulation program and tested by other analysis programs, the BPN can be trained to extract lifetime and intensity from a positron annihilation lifetime spectrum as an input. In principle, the method has the potential to unfold an unknown number of lifetimes and their intensities from a measured spectrum. So far, only a proof-of-principle type preliminary investigation was made by unfolding three or four discrete lifetimes. The present study aims to design the network. Besides, the performance of this method requires both the accurate design of the BPN structure and a long training time. In addition, the performance of the method in practical applications is dependent on the quality of the simulation model. However, the chances of satisfying the above criteria appear to be high. When appropriately developed, a trained network could be a very efficient alternative to the existing methods, with very short identification time. We have used the artificial neural network codes to analyze the data such as the positron lifetime spectra for single crystal materials and monocrystalline silicon. Some meaningful results are obtained.

Keywords: positron lifetime spectrum neural network

Received: 29 November 2011
Revised: 22 June 2012
Accepted manuscript online:

PACS:	78	(Optical properties, condensed-matter spectroscopy and other interactions of radiation and particles with condensed matter )
	70.Bj
	29.85.Fj	(Data analysis)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 10835006 and 10975133).

Corresponding Authors: Ye Bang-Jiao
E-mail: bjye@ustc.edu.cn

Cite this article:

An Ran (安然), Zhang Jie (张杰), Kong Wei (孔伟), Ye Bang-Jiao (叶邦角 ) Application of artificial neural networks to the inversion of positron lifetime spectrum 2012 Chin. Phys. B 21 117803

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