Simulation #47 · Nonlinear Dynamics

Kuramoto Coupled Oscillators

Above a critical coupling K, independent oscillators spontaneously synchronise — a second-order phase transition from chaos to coherence.

Preset:
Order r:0.000
K:
Frame:0

The Kuramoto Model

In 1975, Japanese physicist Yoshiki Kuramoto simplified Winfree's (1967) model of biological oscillators into an exactly solvable mean-field system. The model describes N oscillators, each with a natural frequency ωᵢ drawn from a probability distribution g(ω), coupled through the phase differences of neighbours.

Kuramoto Equation:
dθᵢ/dt = ωᵢ + (K/N)·Σⱼ sin(θⱼ − θᵢ)

Each oscillator i feels a torque from every other oscillator j proportional to the sine of their phase difference. The coupling parameter K controls the interaction strength.

Order Parameter r

r·e^{iψ} = (1/N)·Σⱼ e^{iθⱼ}. When r≈0 phases are incoherent; r≈1 means full synchrony. ψ is the mean phase.

Critical Coupling Kc

For a Lorentzian g(ω)=γ/π(ω²+γ²), the critical value is Kc=2γ. For Gaussian g, Kc=2/[π·g(0)].

Phase Transition

For K>Kc, a bifurcation gives r≈√(8(K−Kc)/Kc·π·g(0)) — a continuous transition with β=1/2.

Mean-Field Form

Using the order parameter, each oscillator couples to the collective mean field: dθᵢ/dt = ωᵢ + K·r·sin(ψ−θᵢ).

Mathematical Analysis

Kuramoto solved the N→∞ limit exactly using the self-consistency equation. In steady state with r constant, oscillators with |ωᵢ − Ω| ≤ Kr are locked to the mean field at frequency Ω; those outside this band remain drifting.

Self-Consistency:
r = K·∫_{−Kr}^{Kr} cos(θ*)·g(Ω+Kr·sin θ*)·Kr·cos θ* dθ*

For a symmetric distribution this reduces to 1 = K·∫_{−π/2}^{π/2} cos²(θ)·g(Kr·sin θ) dθ, with the trivial solution r=0 always present and a non-trivial r>0 branch appearing at K=Kc.

The density of locked oscillators grows as K exceeds Kc, contributing a coherent component to r. The Ott–Antonsen ansatz (2008) showed the dynamics reduce exactly to two real ODEs for r and ψ when g(ω) is a rational function, making the Kuramoto model analytically tractable far from equilibrium.

Presets

PresetNKω distributionExpected behaviour
🌀 Subcritical800.5Gaussian σ=1.0r≈0; incoherent drifting phases
⚡ Near Critical801.6Gaussian σ=1.0r fluctuates around Kc; partial locking
✨ Synchronized804.0Gaussian σ=1.0r→0.8–0.95; majority phase-locked
〰 Bimodal ω1003.0Bimodal ±1.5Two clusters; harder to synchronise
🔵 Large Network2002.5Gaussian σ=1.0Large-N limit; sharper transition
💫 Pulse Reset605.0Tight σ=0.2Strong coupling; oscillator flashing

Emergent Phenomena

PhenomenonConditionDescription
IncoherenceK < KcPhase distribution remains uniform on [0,2π]; r≈0
Partial synchronyK ≈ KcA locked cluster coexists with drifting oscillators; r intermediate
Full synchronyK ≫ KcNearly all oscillators lock; r→1; coherent mean field dominates
Chimera statesNon-uniform couplingCoexisting coherent and incoherent domains; found in 2D networks
Travelling wavesBimodal g(ω)Two clusters counter-rotate; beating oscillations in r(t)
Explosive syncCorrelated K−ωDiscontinuous (first-order) transition if large K assigned to high-ω oscillators

Real-World Applications

DomainSystemRole of synchronisation
NeuroscienceGamma-band oscillations (40 Hz)Cortical binding; attention; epileptic seizures when over-synchronised
BiologyFirefly flash synchronyMales synchronise flashes to attract females; Southeast Asian species Pteroptyx malaccae
CardiologySinoatrial node pacemaker cells~10 000 cells synchronise to drive heartbeat at consistent rate
ChronobiologySuprachiasmatic nucleus (SCN)~20 000 neurons synchronise circadian rhythms; jet lag is de-synchronisation
EngineeringPower grid frequency (50/60 Hz)Generators must maintain phase lock; loss of synchrony causes blackouts
PhysicsJosephson junction arraysSuperconducting junctions synchronise to emit coherent microwave radiation

Kuramoto vs Other Collective Behaviour

ModelAgentsInteractionOrder parameter
Kuramoto (1975)Oscillators on ℝPhase difference sin(θⱼ−θᵢ)r = |⟨e^{iθ}⟩|
Vicsek (1995)Moving particles in 2DAverage velocity directionφ = |⟨v/|v|⟩|
Boids Reynolds (1987) 2D agents with positionsSep/Ali/Coh forcesPolarisation P
Ising model (1925)Lattice spins ±1Ferromagnetic coupling JMagnetisation m

Educational Context

LevelKey concept
A-level / Pre-universitySimple harmonic oscillators; phase; coupled pendula
Undergraduate PhysicsNonlinear dynamics; mean-field theory; bifurcations; statistical mechanics analogy
Graduate / ResearchOtt–Antonsen reduction; finite-size fluctuations; chimera states; network topology effects
InterdisciplinarySystems biology; neuroscience; power systems; complex network science

Frequently Asked Questions

Why does the order parameter r stay below 1 even at large K?

Finite-size fluctuations prevent exact r=1. In the N→∞ limit, r→1 only if all ωᵢ are identical (δ-distribution). For any distribution with finite spread, a fraction of drifting oscillators always exists at finite K, keeping r < 1. Increasing N sharpens the transition and reduces fluctuations, but the asymptotic r∞(K) < 1 for finite spread remains.

What is the golden angle and how does it appear here?

When oscillators initialise with uniformly random phases, they sample the circle uniformly — the Kuramoto model's incoherent state corresponds to a uniform distribution on S¹. As coupling increases and a cluster forms, the phases of locked oscillators converge toward ψ while drifting oscillators spread uniformly. The visual ring arrangement helps distinguish these two populations: the dense arc is the locked cluster.

How does the bimodal distribution change the transition?

A bimodal g(ω) = [δ(ω−ω₀) + δ(ω+ω₀)]/2 creates oscillators in two groups rotating in opposite directions. They form two competing clusters. For small |ω₀| the transition is still continuous; at a tricritical point (|ω₀| = √3/4·Kc) the transition becomes discontinuous — an explosive first-order synchronisation where r jumps from 0 to a finite value.

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