Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport

Fuente: arXiv
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Autori principali: Olivares, Felipe, Zanin, Massimiliano
Natura: Preprint
Pubblicazione: 2025
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author Olivares, Felipe
Zanin, Massimiliano
author_facet Olivares, Felipe
Zanin, Massimiliano
contents Within the continuous endeavour of improving the efficiency and resilience of air transport, the trend of using concepts and metrics from statistical physics has recently gained momentum. This scientific discipline, which integrates elements from physics and statistics, aims at extracting knowledge about the microscale rules governing a (potentially complex) system when only its macroscale is observable. Translated to air transport, this entails extracting information about how individual operations are managed, by only studying coarse-grained information, e.g. average delays. We here review some fundamental concepts of statistical physics, and explore how these have been applied to the analysis of time series representing different aspects of the air transport system. In order to overcome the abstractness and complexity of some of these concepts, intuitive definitions and explanations are provided whenever possible. We further conclude by discussing the main obstacles towards a more widespread adoption of statistical physics in air transport, and sketch topics that we believe may be relevant in the future.
format Preprint
id arxiv_https___arxiv_org_abs_2507_20927
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
Olivares, Felipe
Zanin, Massimiliano
Data Analysis, Statistics and Probability
Physics and Society
Within the continuous endeavour of improving the efficiency and resilience of air transport, the trend of using concepts and metrics from statistical physics has recently gained momentum. This scientific discipline, which integrates elements from physics and statistics, aims at extracting knowledge about the microscale rules governing a (potentially complex) system when only its macroscale is observable. Translated to air transport, this entails extracting information about how individual operations are managed, by only studying coarse-grained information, e.g. average delays. We here review some fundamental concepts of statistical physics, and explore how these have been applied to the analysis of time series representing different aspects of the air transport system. In order to overcome the abstractness and complexity of some of these concepts, intuitive definitions and explanations are provided whenever possible. We further conclude by discussing the main obstacles towards a more widespread adoption of statistical physics in air transport, and sketch topics that we believe may be relevant in the future.
title Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
topic Data Analysis, Statistics and Probability
Physics and Society
url https://arxiv.org/abs/2507.20927