Resolution of Identity Crisis of Events in Pile-up
Avinash A. Deshpande, Harsha Raichur

TL;DR
This paper introduces an analytical method using Poisson statistics and Fourier transforms to accurately recover true event distributions distorted by pile-up effects in measurements, applicable across various scientific fields.
Contribution
The authors propose the first explicit analytical solution to correct pile-up distortions in event rate distributions, improving accuracy over existing simulation-based estimates.
Findings
Method effectively restores true distributions from distorted data.
Performs well even with significant pile-up distortions.
Applicable to diverse fields like physics and medical diagnostics.
Abstract
Mutually uncorrelated random discrete events, manifesting a common basic process, are examined often in terms of their occurrence rate as a function of one or more of their distinguishing attributes, such as measurements of photon spectrum as a function of energy. Such rate distributions obtained from the observed attribute values for an ensemble of events will correspond to the "true" distribution only if the event occurrence were {\it mutually exclusive}. However, due to finite resolution in such measurements, the problem of event {\it pile-up} is not only unavoidable, but also increases with event rate. Although extensive simulations to estimate the distortion due to pile-up in the observed rate distribution are available, no restoration procedure has yet been suggested. Here we present an elegant analytical solution to recover the underlying {\it true} distribution. Our method,…
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Taxonomy
TopicsStatistical Mechanics and Entropy · Radiation Detection and Scintillator Technologies · Gamma-ray bursts and supernovae
