Parity effect confirmed
2026-07-14
Ran the clean 3× comparison for N=32,33,64,65 at K=1.75.
Odd-N always worse. The gap is larger than the variance between
runs — this is a real effect. Still no explanation. Asked on
the nonlinear-dynamics mailing list, no replies yet.
Noise threshold behaviour
2026-06-28
σ > 0.08 is where things get interesting. Above that threshold,
the slip rate doesn't just increase — the slip distribution
changes shape. Below σ=0.08, slips are Poisson-like. Above, they
cluster. Something about the effective potential landscape
flattening near the saddle?
Refactored the simulator
2026-05-10
Split the coupled-osc code into a proper library with a CLI wrapper.
New features: HDF5 output, seed management, checkpoint/resume.
Tagged v0.3.0. The v0.2.x API is broken, but nobody else was using it.
Long-range coupling — not started
2026-03-02
Thought about implementing power-law coupling (1/r^α) but decided
to finish the ring topology analysis first. There are enough open
questions with the nearest-neighbour case.
Read Acebrón et al. (2005) again
2025-12-15
The review covers the homogeneous all-to-all case exhaustively but
the section on sparse coupling is barely 3 pages long. They mention
the ring topology parity effect in passing ("an interesting
finite-size artifact") but don't pursue it. That's basically
what I'm looking at.
First simulation results
2025-09-20
Got the Euler-Maruyama integrator working. N=32 ring, fixed K,
zero noise — phase-locking behaves exactly as expected from the
Strogatz (2000) paper. Good sanity check. Next: add noise,
increase N, start parameter sweeps.
Scratch work on the critical coupling
2025-07-04
Tried to derive K_c for ring topology with Gaussian frequency spread.
Got stuck on the integral. The self-consistency equation for the
order parameter turns into something that doesn't have an elementary
closed form. Maybe numerical continuation is the way to go instead.
Why this problem
2025-04-11
This started as a clock synchronization problem. If you have N
nodes on a ring network trying to agree on time, the Kuramoto model
is a decent first approximation. The noise term maps to oscillator
jitter. K maps to the PLL loop bandwidth. σ maps to environmental
drift. It's not a perfect analogy but it's good enough to be useful.
Initial setup
2024-11-08
Putting together a minimal simulation framework in Python.
Don't want to use existing packages — I need control over the
integration and I want to understand every line. Will publish
the repo once it's not embarrassing.
Last entry: 2026-07-14. No fixed update schedule.