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Variational equations

HOW DOES A SMALL CHANGE EVOLVE?

Variational equations

2D system

Base x′ = f(x)Variation η′ = Df(x(t))ηPrediction y(t) ≈ x(t) + η(t)

Phase portrait

Base x(t)Comparison y(t)Variational arrow η(t)

Click to add a comparison · scroll to zoom. The orange arrow starts at the moving base point.

t = 0.00

Separation & approximation error

Selected comparison
Actual |y − x|Linearized |η|Error |y − x − η|

Along the base trajectory

Df(x(t)) · current Jacobian

Actual separation
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Variational magnitude
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Approximation error
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The arrow keeps its true length. Its tip predicts the comparison point; the gap between them is the linearization error.

Explore nearby solutions

The base trajectory solves x′ = f(x). A comparison solves the same equation from a different initial point y₀. The variational vector solves η′ = Df(x(t))η, starting from η(0) = y₀ − x₀.

Arrows are never rescaled to fit the picture. Large vectors can extend outside the view. Numerical paths stop if they grow beyond the integration limit; backwards-time trajectories may also escape.