Question about Gradient's Domain and Range

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Discussion Overview

The discussion revolves around the properties of the gradient of a function, specifically regarding the domain and range of the gradient operator. Participants explore the relationship between functions from \(\mathbb{R}^n\) to \(\mathbb{R}\) and their gradients, as well as the concept of the Jacobian matrix in the context of derivatives.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant questions whether the gradient operator \(\nabla f\) for a function \(f:\mathbb{R^n}\to \mathbb{R}\) is correctly represented as mapping from \(\mathbb{R^n}\) to \(\mathbb{R^n}\).
  • Another participant describes the derivative matrix for a function \(f: \mathbb{R}^n \to \mathbb{R}^n\) and asks if it is the Jacobian matrix.
  • Responses indicate that the Jacobian matrix is indeed relevant and that for a single-component function, the matrix reduces to a vector, linking it to the gradient.
  • There is a detailed exploration of the different interpretations of derivatives, including the mapping of locations, directions, and function spaces, emphasizing the importance of understanding the domain and range in these contexts.
  • One participant expresses appreciation for the explanations provided, indicating that the discussion has been informative.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the initial question regarding the mapping of the gradient operator. There are multiple interpretations of derivatives and their representations, leading to a nuanced discussion without a definitive resolution.

Contextual Notes

The discussion highlights the complexity of derivative notation and the implications for understanding the domain and range of functions and their gradients. The varying interpretations of derivatives and the Jacobian matrix introduce additional layers of complexity that remain unresolved.

littlemathquark
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TL;DR
$$f:\mathbb{R^n}\to \mathbb{R}$$ $$\nabla f:\mathbb{R^n}\to \mathbb{R^n}$$
İf $$f:\mathbb{R^n}\to \mathbb{R}$$ then $$\nabla f:\mathbb{R^n}\to \mathbb{R^n}$$ $$x\to \nabla f(x)$$ is true?
 
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A function f: \mathbb{R}^n \to \mathbb{R}^n has a derivative matrix <br /> Df|_{a} = \begin{pmatrix} \left.\frac{\partial f_1}{\partial x_1}\right|_{x=a} &amp; \cdots &amp; \left.\frac{\partial f_1}{\partial x_n}\right|_{x=a} \\<br /> \vdots &amp; \ddots &amp; \vdots \\<br /> \left.\frac{\partial f_n}{\partial x_1}\right|_{x=a} &amp; \cdots &amp; \left.\frac{\partial f_n}{\partial x_n}\right|_{x=a} \end{pmatrix}.
 
pasmith said:
A function f: \mathbb{R}^n \to \mathbb{R}^n has a derivative matrix <br /> Df|_{a} = \begin{pmatrix} \left.\frac{\partial f_1}{\partial x_1}\right|_{x=a} &amp; \cdots &amp; \left.\frac{\partial f_1}{\partial x_n}\right|_{x=a} \\<br /> \vdots &amp; \ddots &amp; \vdots \\<br /> \left.\frac{\partial f_n}{\partial x_1}\right|_{x=a} &amp; \cdots &amp; \left.\frac{\partial f_n}{\partial x_n}\right|_{x=a} \end{pmatrix}.
İs it Jakobien matrix?
 
Jacobian ..

Do you know how to use Google ?

##\ ##
 
BvU said:
Jacobian ..

Do you know how to use Google ?

##\ ##
Yes
 
littlemathquark said:
İs it Jakobien matrix?
Yes, and as in your example where ##f=(f_1)## has only one component, this matrix becomes a vector, and in this sense
$$
\nabla_a f = \left.Df\right|_a
$$
But let's be careful. Consider
$$
\left. \dfrac{d}{dx}\right|_{x=a}f(x)
$$
This is a simple derivative, but what are the variables? We technically have three possibilities:
\begin{align*}
a&\longmapsto f'(a)=\left. \dfrac{d}{dx}\right|_{x=a}f(x)\quad \text{location, result: a vector of partial derivatives}\\[6pt]
\mathbb{R}^n&\longrightarrow \mathbb{R}^n\\[6pt]
f'(a)&=\left.Df(x)\right|_a=\left.D\right|_af(x)=D_a f(x)=\nabla_a(f(x))\\[6pt]
&\text{It is often written as}\\[6pt]
f'(x)&=Df(x)=(Df)(x)=\nabla(f(x))\\[6pt]
&\text{neglecting the location}\\[18pt]
v&\longmapsto f'(a)\cdot v=\left(\left. \dfrac{d}{dx}\right|_{x=a}f(x)\right)\cdot v\quad \text{direction, result: a number, product of }f'(a)\text{ and }v\\[6pt]
\mathbb{R}^n&\longrightarrow \mathbb{R}\\[6pt]
f'(x)\cdot v&=Df(x)\cdot v=\nabla(f(x))\cdot v\\[18pt]
f&\longmapsto f'=\dfrac{df}{dx}\quad \text{differentiation, result: a function of a function space}\\[6pt]
\mathcal{C}^\infty(\mathbb{R}^n) &\longrightarrow \mathcal{C}^{\infty }(\mathbb{R}^n)\\[6pt]
f'&=Df =\nabla f
\end{align*}
A notation like ##f'(x)## does not distinguish between those meanings but they are important if you want to know the domain and the range of them.
 
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Thank you for your informative explanations.
 
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