Math 2.0

statement corollary

Chain rule for Jacobian matrices

Statement

Let U⊆RnU \subseteq \mathbb{R}^n and W⊆RmW \subseteq \mathbb{R}^m be open, let g ⁣:U→Wg \colon U \to W, let f ⁣:W→Rkf \colon W \to \mathbb{R}^k, and let a∈Ua \in U. Suppose that gg is differentiable at aa and ff is differentiable at g(a)g(a). Then the Jacobian matrices satisfy Jf∘g(a)=Jf(g(a)) Jg(a),J_{f \circ g}(a) = J_f(g(a)) \, J_g(a), a product of a k×mk \times m matrix and an m×nm \times n matrix.

Remarks

This is the chain rule in several variables, written with matrices: the matrix of a composition of linear maps is the product of their matrices. For k=m=nk = m = n, taking determinants gives det⁡Jf∘g(a)=det⁡Jf(g(a))⋅det⁡Jg(a)\det J_{f \circ g}(a) = \det J_f(g(a)) \cdot \det J_g(a). For example, let g(r,θ)=(rcos⁡θ,rsin⁡θ)g(r, \theta) = (r \cos \theta, r \sin \theta) and f(x,y)=x2+y2f(x, y) = x^2 + y^2. Then Jf(g(r,θ))Jg(r,θ)=(2rcos⁡θ, 2rsin⁡θ)Jg(r,θ)=(2r, 0)J_f(g(r, \theta)) J_g(r, \theta) = (2r \cos \theta, \, 2r \sin \theta) J_g(r, \theta) = (2r, \, 0), which is the Jacobian matrix of (f∘g)(r,θ)=r2(f \circ g)(r, \theta) = r^2.

Explanations

L1 human

Each Jacobian matrix turns small input steps into small output steps. Doing two maps one after the other means multiplying their matrices, in the same order as the maps act, from right to left.

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  1. Euclidean space object
  2. Function concept
  3. Function composition concept
  4. Fréchet derivative definition
  5. Function of several variables concept
  6. Limit of a function of several variables concept
  7. Partial derivative concept
  8. Differentiable function of several variables definition
  9. Jacobian matrix definition
  10. Chain rule in several variables statement
  11. Chain rule for Jacobian matrices statement

Sources

  1. Web https://en.wikipedia.org/wiki/Chain_rule, General rule: Vector-valued multivariate functions