Event-sequence time series analysis in ground-based gamma-ray astronomy.

de Almeida, U. Barres; Chadwick, P.; Daniel, M.; Nolan, S.; McComb, L.

Abstract

The recent, extreme episodes of variability detected from Blazars by the leading atmospheric Čerenkov experiments motivate the development and application of specialized statistical techniques that enable the study of this rich data set to its furthest extent. The identification of the shortest variability timescales supported by the data and the actual variability structure observed in the light curves of these sources are some of the fundamental aspects being studied, that answers can bring new developments on the understanding of the physics of these objects and on the mechanisms of production of VHE gamma‐rays in the Universe. Some of our efforts in studying the time variability of VHE sources involve the application of dynamic programming algorithms to the problem of detecting change‐points in a Poisson sequence. In this particular paper we concentrate on the more primary issue of the applicability of counting statistics to the analysis of time‐series on VHE gamma‐ray astronomy.

Citation

de Almeida, U. B., Chadwick, P., Daniel, M., Nolan, S., & McComb, L. (2009). Event-sequence time series analysis in ground-based gamma-ray astronomy. In F. Aharonian, W. Hofmann, & F. Rieger (Eds.), High energy gamma-ray astronomy: 4th International Meeting on High Energy Gamma-Ray Astronomy, Heidelberg, Germany, 7-11 July 2008 (775-778). https://doi.org/10.1063/1.3076794

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: High energy gamma-ray astronomy: 4th International Meeting on High Energy Gamma-Ray Astronomy
• Publication Date: 2009
• Deposit Date: Feb 5, 2014
• Publisher: American Institute of Physics
• Volume: 1085
• Pages: 775-778
• Series Title: AIP Conference Proceedings
• Book Title: High energy gamma-ray astronomy: 4th International Meeting on High Energy Gamma-Ray Astronomy, Heidelberg, Germany, 7-11 July 2008
• DOI: https://doi.org/10.1063/1.3076794
• Public URL: https://durham-repository.worktribe.com/output/1155798