Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Prediction of Large Events in Directed Sandpiles

Prediction of Large Events in Directed Sandpiles

Thumbnail Image
Download
Name

10955_2025_Article_3548.pdf

Size

1.45 MB

Format

Adobe PDF

Checksum (MD5)

ceb7dd7f806ac894ff5b140a119c09e3

Download all files submitted through automated deposit
art_5061011772066178264.zip (1.04 MB)
Author(s)
Shah, Dhruv
Date Issued
November 15, 2025
Journal
Journal of Statistical Physics
Publisher
Springer US
Citation
Shah, D. Prediction of Large Events in Directed Sandpiles. J Stat Phys 192, 164 (2025).
Version
Final published version
Abstract
The degree of predictability of large avalanche events in the directed sandpile model is studied. This degree is defined in terms of how successfully a strategy can predict such events, as compared to a random guess. A waiting time based prediction strategy which exploits the local anticorrelation of large events is discussed. With this strategy we show analytically and numerically that large events are predictable, and that this predictability persists in the thermodynamic limit. We introduce another strategy which predicts large avalanches in the future based on the present excess density in the sandpile. We obtain the exact conditional probabilities for large events given an excess density, and use this to determine the exact form of the ROC predictability curves. We show that for this strategy, the model is predictable only for finite lattice sizes, and unpredictable in the thermodynamic limit. This behaviour is to be contrasted with previously established numerical studies carried out for Manna sandpiles.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/163674
DOI of Published Version
https://doi.org/10.1007/s10955-025-03548-0
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.