{"title":"Detecting and Counting of Each Nested Curve on Spectrum with Gaussian Package","authors":"Y. Kocak, S. Sevgen, R. Samli","doi":"10.23919/ELECO47770.2019.8990594","DOIUrl":null,"url":null,"abstract":"Spectral analysis plays an important role in the interpretation of astronomical data. The determination of the number and parameters of each nested Gaussian curve on spectrum of any object in the sky gives information about the physical and chemical structure of the object. In this study, determination of each nested Gaussian curve’s number and parameters such as position, width and amplitude in a given frequency range are performed. Thus, we have knowledge of about, which molecules there are in the observation region. Autonomous Gaussian Decomposition algorithm is implemented with additional scipy, numpy, h5py, lmfit packages. The algorithm is tested on spectral data that comes from active star forming region called as Orion KL obtained by SMA (Submillimeter Array) devices are used. Finally, information is given about positive and negative aspects of these study and in the future what should we do to improve the accuracy.","PeriodicalId":6611,"journal":{"name":"2019 11th International Conference on Electrical and Electronics Engineering (ELECO)","volume":"23 1","pages":"565-569"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Electrical and Electronics Engineering (ELECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ELECO47770.2019.8990594","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
Spectral analysis plays an important role in the interpretation of astronomical data. The determination of the number and parameters of each nested Gaussian curve on spectrum of any object in the sky gives information about the physical and chemical structure of the object. In this study, determination of each nested Gaussian curve’s number and parameters such as position, width and amplitude in a given frequency range are performed. Thus, we have knowledge of about, which molecules there are in the observation region. Autonomous Gaussian Decomposition algorithm is implemented with additional scipy, numpy, h5py, lmfit packages. The algorithm is tested on spectral data that comes from active star forming region called as Orion KL obtained by SMA (Submillimeter Array) devices are used. Finally, information is given about positive and negative aspects of these study and in the future what should we do to improve the accuracy.