Presentation Title

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.

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Oct 26th, 2:00 PM Oct 26th, 3:00 PM

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.