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| | Abstract | | Muography is a method of estimating the density distribution inside an object by measuring the intensity of elementary particle muons. Although it is applied to underground due to the miniaturization of detectors, the interrelationship among space, time, and density resolution is unknown. Also, the number of data is small because of limited number of detectors, so sparse modeling may be better option than conventional smoothing methods for anomaly detection. The purpose of this paper is to evaluate the interrelationship of resolution and examine the applicability of sparse modeling in anomaly detection. For the former, we were able to quantitatively evaluate the interrelationships related to space, time, and density resolution by performing numerical calculations on the two-dimensional density model. In the latter case, the results of sparse modeling and the conventional smoothing method are in agreement, so it is necessary to apply it to another density model to find out difference between them. |
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