Directional derivative and steepest ascent along the gradient
Statement
If is differentiable at and , then for any unit vector (with ), the directional derivative satisfies , where is the angle between and . Consequently, attains its maximum when , and its minimum in the opposite direction.
Why is it true?
The dot product projects the gradient onto your chosen walking direction: you gain the full magnitude of the gradient only when you align perfectly with it, and zero change when you walk perpendicular to it along a contour line.
Proof sketch
Define the single-variable function . By definition of the directional derivative, . Since is totally differentiable at , we have as . Dividing by and taking the limit yields .
By the geometric formula for the Euclidean inner product and the unit-length condition , we obtain . Since , the maximum value is achieved uniquely at , where , and the minimum is achieved at .
Topics that use this theorem
Step-by-step proofs
No step-by-step proof yet for this theorem.
References
- Jerrold E. Marsden, Anthony J. Tromba (2012). Vector Calculus
- James Stewart (2015). Calculus: Early Transcendentals
- Augustin-Louis Cauchy (1847). Méthode générale pour la résolution des systèmes d'équations simultanées