Linked from

The 15 pages that link to Lorenz system, each with the reason it gives.

• Numerical weather predictionRelated: Its behavior illustrates how tiny initial errors can grow into major forecast differences.

• Chaos theoryBroader topic: Its bounded, aperiodic trajectories became a landmark example of deterministic chaos.

• Poincaré mapBroader topic: Its section-crossing map helps display the geometry of its chaotic attractor.

• Bifurcation theoryBroader topic: Its parameter-dependent changes connect bifurcation structure with chaotic attractors.

• Lyapunov exponentBroader topic: Its positive largest exponent quantifies sensitive dependence in a classic chaotic model.

• Nonlinear dynamicsBroader topic: Its trajectories became a landmark example of deterministic chaos.

• Rayleigh–Bénard convectionRelated: Its equations retain a strikingly simplified form of convection dynamics.

• BifurcationRelated: Its parameter changes reveal transitions among steady states, periodic orbits, and chaos.

• AttractorBroader topic: Its trajectories approach the famous butterfly-shaped strange attractor.

• Phase portraitBroader topic: Its trajectories form a complex structure that phase-space plots can reveal.

• Dynamical systems theoryBroader topic: It arose in a simplified model of atmospheric convection and illustrates sensitive dependence.

• Butterfly effectBroader topic: Its trajectories demonstrate how small state differences can grow dramatically.

• Poincaré–Bendixson theoremCompared with: Its chaotic attractor illustrates behavior possible beyond the planar setting.

• Edward Norton LorenzBroader topic: This simplified model generated the sensitive, aperiodic trajectories central to Lorenz’s discovery.

• Chaos and nonlinear dynamicsBroader topic: Its strange attractor became an iconic example of deterministic chaos.