Differentiability at a Point and Jacobian Matrix for Maps Between Euclidean Spaces

definitionMultivariable Calculus

Differentiability at a Point and Jacobian Matrix for Maps Between Euclidean Spaces

definitionMultivariable Calculusdef:differentiable-map-at-point-euclidean-2026a
· by ChatGPT-5.4, Aaron ·
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Reason: Publish differentiability and Jacobian definition for Euclidean maps.

Let n,mNn,m\in\mathbb{N}. Let URnU\subseteq \mathbb{R}^n be \reftext{def:open-subset-euclidean-space-2026a}{open}, let f=(f1,,fm):URmf=(f_1,\dots,f_m):U\to\mathbb{R}^m, and let a=(a1,,an)Ua=(a_1,\dots,a_n)\in U. Suppose that for every j{1,,m}j\in\{1,\dots,m\} and every i{1,,n}i\in\{1,\dots,n\} the partial derivative \ref{def:partial-derivative-coordinate-map-2026a} fjxi(a)\frac{\partial f_j}{\partial x_i}(a) exists. The matrix

Jf(a)=(fjxi(a))1jm, 1inJ_f(a)=\left(\frac{\partial f_j}{\partial x_i}(a)\right)_{1\le j\le m,\ 1\le i\le n}

is called the Jacobian matrix of ff at aa. We say that ff is differentiable at aa if for every ε>0\varepsilon>0 there exists δ>0\delta>0 with the following property: whenever h=(h1,,hn)Rnh=(h_1,\dots,h_n)\in\mathbb{R}^n satisfies

0<i=1nhi2<δ20<\sum_{i=1}^n h_i^2<\delta^2

and a+hUa+h\in U, one has

j=1m(fj(a+h)fj(a)i=1nfjxi(a)hi)2ε2i=1nhi2.\sum_{j=1}^m \left(f_j(a+h)-f_j(a)-\sum_{i=1}^n \frac{\partial f_j}{\partial x_i}(a) h_i\right)^2 \le \varepsilon^2 \sum_{i=1}^n h_i^2.
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