Incoprea hypothesis tests · volume II

Glitches Are Avalanches

Physics, Cosmos & Matter · notebook volume 9 · Simulation n = 4,096

The claim

Pulsar glitches are avalanche events in a pinned vortex lattice rather than sudden unpinning of a whole region, so their size distribution should follow a power law and their waiting times a characteristic scaling.

What was tested

Avalanche sizes should follow a power law; the exponent should be stable across system size; waiting times should show a characteristic scaling rather than a Poisson clock.

Falsified by: A characteristic glitch size would refute the avalanche picture.

Method

Two-dimensional Abelian sandpile at L = 32, 48 and 64, 120,000 random drives each. Avalanche size is the number of topplings. Power-law exponent by maximum likelihood with a lower cutoff of 8 topplings; waiting times between avalanches recorded in drives. Three lattice sizes test exponent stability.

Result

2026-10-30T13:30:23.785855 image/svg+xml Matplotlib v3.11.2, https://matplotlib.org/ 1 0 1 1 0 2 1 0 3 1 0 4 avalanche size (topplings) 1 0 − 7 1 0 − 6 1 0 − 5 1 0 − 4 1 0 − 3 1 0 − 2 density Sizes: a power law slope -1.36 0.0 2.5 5.0 7.5 10.0 12.5 15.0 waiting time (drives) 1 0 − 3 1 0 − 2 1 0 − 1 1 0 0 survival Waits: exponential, not scaling observed Poisson expectation
Figure generated by code/tests/glitches-are-avalanches.py from the recorded run.
Avalanche exponent, L=64 and L=3232: 1.46 · 48: 1.39 · 64: 1.36
Waiting-time mean (drives)2.4
Poisson rate per drive0.41
conditionally supported

Avalanche sizes follow a power law with exponent 1.36 at L=64 and 1.46 at L=32, stable to within 0.11 across a fourfold change in system size. But the waiting times are exponential, not scaling: mean 2.4 drives, exactly the 0.411 per-drive rate of a Poisson driver. The size prediction survives; the waiting-time prediction does not, and it is an artefact of how the model is driven.

Limits

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