| Issue |
EPL
Volume 150, Number 3, May 2025
|
|
|---|---|---|
| Article Number | 31002 | |
| Number of page(s) | 6 | |
| Section | Statistical physics and networks | |
| DOI | https://doi.org/10.1209/0295-5075/adc9de | |
| Published online | 06 May 2025 | |
Estimating transmission noise on networks from stationary local order
1 Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester Manchester M13 9PL, UK
2 Department of Linguistics, University of Konstanz - Universitätsstraße 10, 78464 Konstanz, Germany
3 Institutionen för lingvistik och filologi, Uppsala Universitet - 751 26 Uppsala, Sweden
4 Department of Linguistics and English Language, School of Arts, Languages, and Cultures, The University of Manchester - Manchester M13 9PL, UK
5 Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB), Campus Universitat Illes Balears - Palma de Mallorca E-07122, Spain
Received: 28 February 2025
Accepted: 7 April 2025
We study networks of nodes characterised by binary traits that change both endogenously and through nearest-neighbour interaction. Our analytical results show that those traits can be ranked according to the noisiness of their transmission using only measures of order in the stationary state. Crucially, this ranking is independent of network topology. As an example, we explain why, in line with a long-standing hypothesis, the relative stability of the structural traits of languages can be estimated from their geospatial distribution. We conjecture that similar inferences may be possible in a more general class of Markovian systems. Consequently, in many empirical domains where longitudinal information is not easily available the propensities of traits to change could be estimated from spatial data alone.
© 2025 The author(s)
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