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The total (Fréchet) derivative Df(a) as the linear first-order approximation with o(∥h∥2) remainder

Definition

Let m,n∈N, let U⊆Rm be open in the metric induced by its Euclidean norm, let a∈U, and let f:U→Rn. The map f is totally differentiable at a when there is a linear map L:Rm→Rn (A linear map L:Rm→Rn in Euclidean coordinates) such that for every ε>0 there is δ>0 for which

∥f(a+h)−f(a)−Lh∥2≤ε∥h∥2whenever a+h∈U and ∥h∥2<δ.

The map L, when it exists, is denoted Df(a) and called the total derivative. Equivalently, f(a+h)=f(a)+Df(a)h+r(h) with the displayed remainder estimate for every ε>0. At h=0 the remainder is zero because L0=0.

For m≥1, openness of U provides admissible nonzero increments arbitrarily near zero, and dividing the estimate by ∥h∥2>0 gives the usual notation

lim⁡h→0∥f(a+h)−f(a)−Lh∥2∥h∥2=0,

where the quotient is considered for h≠0 with a+h∈U. Conversely this punctured normwise limit gives the estimate above (using a smaller positive tolerance if necessary). Thus the positive-dimensional definition is unchanged. This is the multivariate normwise remainder condition; no limit at an isolated point is asserted.

When m=0, the Euclidean zero space consists only of 0, so a=0 and U={0}; its Euclidean norm and induced metric exist by A norm on a real vector space, the induced metric, and the dictionary with the metric axioms. The unique linear map L:R0→Rn sends 0 to 0, and its remainder is identically zero. It is therefore the total derivative by the displayed estimate, with any δ>0. When n=0, the unique map f and the unique linear map into R0 likewise have zero remainder, in every source dimension.

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