275. Phase Plane

A graphical method for analyzing 2-state dynamical systems. Plot the two state variables on axes; the system’s trajectory traces a curve in this plane.

275.1. For a 2-state system

Each point has a velocity vector . The phase portrait is the field of these vectors plus typical trajectories.

275.2. Key features

275.3. Linearizing at an equilibrium

Near , Taylor-expand :

where is the Jacobian:

The eigenvalues of classify the equilibrium.

275.4. Classification by eigenvalues

Eigenvalues Type Behavior
Both real, both Stable node Trajectories approach from all directions
Both real, both Unstable node Trajectories diverge from
Real, opposite signs Saddle Stable along one direction, unstable along other; separatrix
Complex, real part Stable spiral Trajectories spiral inward
Complex, real part Unstable spiral Trajectories spiral outward
Pure imaginary Center Closed orbits around equilibrium (oscillation)

The trace-determinant plane visualizes these regimes:

275.5. Lotka-Volterra as example

Equilibrium at .

Jacobian at equilibrium:

Trace , . Pure imaginary eigenvalues → center → closed orbits. (Confirms Lotka-Volterra’s well-known oscillation.)

275.6. Limit cycles and chaos

For nonlinear systems with appropriate structure, isolated closed orbits (limit cycles) appear. Examples:

In dimension , chaos becomes possible (Lorenz attractor, etc.). 2-D systems can’t be chaotic by Poincaré-Bendixson theorem.

275.7. Routh-Hurwitz stability for higher dimensions

For 3+ states, eigenvalue computation generalizes. The Routh-Hurwitz criterion gives an algorithmic stability test from coefficient signs of the characteristic polynomial.

275.8. See also