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\[ r=\frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i-\bar{y})}{\sqrt{\sum_{i=1}^{n} (x_i-\bar{x})^2} \sqrt{\sum_{i=1}^{n} (y_i -\bar{y})^2}} \] |
CAGMon etude
Descripstion
The CAGMon etude is a study version of CAGMon that evaluates the dependence between the primary and auxiliary channels.
Project Goal
The goal of this project is to find a systematic way of identifying the abnormal glitches in the gravitational-wave data using various methods of correlation analysis. Usually, the community such as LIGO, Virgo, and KAGRA uses a conventional way of finding glitches in auxiliary channels of the detector - Klein-Welle, Omicron, Ordered Veto Lists, etc. However, some different ways can be possible to find and monitor them in a (quasi-) realtime. Also, the method can point out which channel is responsible for the found glitch. In this project, we study its possible to apply three different correlation methods - maximal information coefficient, Pearson's correlation coefficient, and Kendall's tau coefficient - in the gravitational wave data from the KAGRA detector.
Participants
- John.J Oh (NIMS)
- Young-Min Kim (UNIST)
- Pil-Jong Jung (NIMS)
Methods and Frameworks
Maximal Information Coefficient (MIC)
\[ r=\frac{\sum_{i=1}{n} (x_i - \bar{x})(y_i-\bar{y})}{\sqrt{\sum_{i=1}{n} (x_i-\bar{x})2} \sqrt{\sum_{i=1}{n} (y_i -\bar{y})^2}} \]
Pearson's Correlation Coefficient (PCC)
Kendall's tau Coefficient
Exemplary Results
Beyond
References
Presentation Materials