Francisco J. Franco;Juan C. Fabero;Hortensia Mecha;Mohammadreza Rezaei;Guillaume Hubert;Juan A. Clemente
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Best-Fit Techniques to Estimate SBU/MCU Cross Sections From Radiation-Ground Tests in Memories
This article studies the probability distribution for the expected number of bitflips per round of reading in radiation-ground tests on a memory device where only single-bit upsets (SBUs) and multiple-cell upsets (MCUs) occur. This distribution is used to estimate the soft error cross sections in actual experiments by means of two best-fit approaches: one based on the gradient descent (GD) algorithm and the other on genetic algorithms (GAs). Besides, it is investigated how this mathematical study is suitable to detect possible variations in the soft error rate (SER) due to different reasons, such as variations in the radiation flux. Finally, the inherent stochastic characteristics of the experiments are used to provide tools to detect forgery in experiment data.
期刊介绍:
The IEEE Transactions on Nuclear Science is a publication of the IEEE Nuclear and Plasma Sciences Society. It is viewed as the primary source of technical information in many of the areas it covers. As judged by JCR impact factor, TNS consistently ranks in the top five journals in the category of Nuclear Science & Technology. It has one of the higher immediacy indices, indicating that the information it publishes is viewed as timely, and has a relatively long citation half-life, indicating that the published information also is viewed as valuable for a number of years.
The IEEE Transactions on Nuclear Science is published bimonthly. Its scope includes all aspects of the theory and application of nuclear science and engineering. It focuses on instrumentation for the detection and measurement of ionizing radiation; particle accelerators and their controls; nuclear medicine and its application; effects of radiation on materials, components, and systems; reactor instrumentation and controls; and measurement of radiation in space.