Nonextensive Statistical Analysis of Meteor Showers and Lunar Flashes

TL;DR

This study applies Tsallis nonextensive statistical mechanics to model meteor and lunar flash magnitude distributions, revealing consistent patterns across data sources and highlighting observational biases.

Contribution

It introduces a nonextensive statistical approach to model the entire range of meteor magnitudes, improving upon traditional power-law models.

Findings

Meteor magnitude distribution is well modeled by Tsallis statistics.

Approximately 2.4% of meteors in showers are telescopic.

Lunar flash durations follow a power-law distribution.

Abstract

The distribution of meteor magnitudes is usually supposed to be described by power-laws. However, this relationship is not able to model the whole data set, and the parameters are considered to be dependent on the magnitude intervals. We adopt a statistical distribution derived from Tsallis nonextensive statistical mechanics which is able to model the whole magnitude range. We combined meteor data from various sources, ranging from telescopic meteors to lunar impactors. Our analysis shows that the probability distribution of magnitudes of IMO and MORP data are similar. The distribution of IMO visual magnitudes indicates that $2.4\pm0.5%$ of the meteors of a shower may be telescopic ($m> 6$). We note that the distribution of duration of lunar flashes follows a power-law, and a comparison with the distribution of meteor showers suggests the occurrence of observational bias. The IMO sporadic meteor distribution also seems to be influenced by observational factors.