P-44 A Statistical Analysis of X-Ray Bursts Using Mutual Information
Presenter Status
Undergraduate Student, Department of Physics
Second Presenter Status
Undergraduate Student, Department of Engineering & Computer Science
Third Presenter Status
Professor of Engineering and Physics
Fourth Presenter Status
Researcher, Johns Hopkins University Applied Physics Laboratory
Preferred Session
Poster Session
Start Date
26-10-2018 2:00 PM
End Date
26-10-2018 3:00 PM
Presentation Abstract
A statistical study on solar flares stronger than C1 class detected by the Geostationary Operational Environmental Satellite (GOES) from 1975 to 2017 was performed. A sequence of waiting times (time elapsed between adjacent X-ray flare peaks) was constructed from the data. A surrogate waiting time distribution (WTD) is produced using a time varying Poisson firing rate from the Bayesian Block procedure (Scargle et al., 2012). Utilizing Shannon entropy, the mutual information of the original and surrogate waiting time sequences is then computed at various look-aheads. It is shown that the observed waiting time sequence has a mutual information greater than the constructed sequence that is statistically significant at relatively small timescales. This suggests there is structure not sufficiently captured by a non-stationary Poisson distribution, despite accurately representing the observed distribution.
P-44 A Statistical Analysis of X-Ray Bursts Using Mutual Information
A statistical study on solar flares stronger than C1 class detected by the Geostationary Operational Environmental Satellite (GOES) from 1975 to 2017 was performed. A sequence of waiting times (time elapsed between adjacent X-ray flare peaks) was constructed from the data. A surrogate waiting time distribution (WTD) is produced using a time varying Poisson firing rate from the Bayesian Block procedure (Scargle et al., 2012). Utilizing Shannon entropy, the mutual information of the original and surrogate waiting time sequences is then computed at various look-aheads. It is shown that the observed waiting time sequence has a mutual information greater than the constructed sequence that is statistically significant at relatively small timescales. This suggests there is structure not sufficiently captured by a non-stationary Poisson distribution, despite accurately representing the observed distribution.