Recovering corrections in the analysis of intermittent data
B. Ziaja
TL;DR
This paper improves the analysis of intermittent data by identifying limitations of the standard recovery method for particle cascades and proposing corrections tested within multiplicative cascade models.
Contribution
It introduces corrections to the standard particle cascade recovery method, enhancing accuracy in analyzing intermittent data structures.
Findings
Standard method fails to reproduce true cascade structure.
Proposed corrections improve recovery accuracy.
Tests conducted within multiplicative cascade models.
Abstract
The analysis of intermittent data is improved. The standard method of recovering the history of a particle cascade is proved in general not to reproduce the structure of the true cascade. The recovering corrections to the standard method are proposed and tested in the framework of multiplicative cascading models.
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