Masahiko Hayashi, T. Ishida, H. Shishido, The Dang Vu, S. Kawamata
{"title":"Restoration of Vector Magnetization Image from Vector Scanning-SQUID Microscope Measurement","authors":"Masahiko Hayashi, T. Ishida, H. Shishido, The Dang Vu, S. Kawamata","doi":"10.1088/1742-6596/2776/1/012001","DOIUrl":null,"url":null,"abstract":"A generalized mathematical framework to treat image data measured by the scanning superconducting quantum interference device (SQUID) microscope using a three-dimensional vector pickup coil is presented. The blurring of the images originating from the effects of diamagnetism due to the superconductivity of the sensor, the non-zero sensor size, and the finite sensor-to-sample separation are numerically reduced. We use a lattice model of the measurement system, and singular value decomposition and the Moore-Penrose pseudo-inverse matrix are employed to handle ill-conditioned matrices we encounter in the numerical processes. Based on a numerical model, measurement of the vector magnetization distributed on a sample surface, and the image restoration using the present procedure are demonstrated.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics: Conference Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1742-6596/2776/1/012001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A generalized mathematical framework to treat image data measured by the scanning superconducting quantum interference device (SQUID) microscope using a three-dimensional vector pickup coil is presented. The blurring of the images originating from the effects of diamagnetism due to the superconductivity of the sensor, the non-zero sensor size, and the finite sensor-to-sample separation are numerically reduced. We use a lattice model of the measurement system, and singular value decomposition and the Moore-Penrose pseudo-inverse matrix are employed to handle ill-conditioned matrices we encounter in the numerical processes. Based on a numerical model, measurement of the vector magnetization distributed on a sample surface, and the image restoration using the present procedure are demonstrated.