Differentia of function-valued mapping

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I have difficulty in understanding why the differential [tex]d\varphi[/tex] of a function [tex]\varphi: \eta \rightarrow F(\cdot, \eta)[/tex] on [tex]\Re[/tex] can be written as:

[tex][\varphi'(b)](\xi)=\frac{\partial F}{\partial y}(\xi,b)[/tex] (F is defined on RxR)
according to the following theorem.

the differential [tex]d\varphi_{b}[/tex] is a linear mapping, and the skeleton (1x1 matrix) of this linear mapping is its derivative at b, which is [tex]\varphi'(b)[/tex]. So the differential [tex]d\varphi_{b}(\eta)=\varphi'(b)\eta[/tex], why does [tex]\eta[/tex] disappear from the above formula?

I think the above formula should be written as:
[tex][\varphi'(b)\eta](\xi)=[\frac{\partial F}{\partial y}(\xi,b)](\eta)[/tex]

Related Theorem:
If F is a bounded continuos mapping from an open product set MxN of a normed linear space VxW to a normed linear space X, and if [tex]dF{^2}{_<\alpha,\beta>}[/tex] exists and is a bounded uniformly continuous function of [tex]<\alpha,\beta>[/tex], then [tex]\varphi:\eta \rightarrow F(\cdot,\eta)[/tex] is a differentiable mapping and [tex][d{\varphi_\beta}(\eta)](\xi)=dF{^2}_{<\xi,\beta>}(\eta)[/tex]
 
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Thank you for bringing up this question. The formula you have suggested, [\varphi'(b)\eta](\xi)=[\frac{\partial F}{\partial y}(\xi,b)](\eta), is indeed correct and equivalent to the one stated in the theorem. Let me explain why.

First, let's clarify some notation. In the theorem, \varphi_{b} refers to the differential of \varphi at the point b, which is a linear mapping from the domain of \varphi (in this case, \Re) to the range of \varphi (in this case, F(\cdot, b)). This mapping is defined as d\varphi_{b}(\eta) = \varphi'(b)\eta, where \varphi'(b) is the derivative of \varphi at b and \eta is an element of the domain of \varphi.

Now, let's look at the formula in question, [\varphi'(b)](\xi)=\frac{\partial F}{\partial y}(\xi,b). The left side of the equation is the value of the linear mapping \varphi'(b) at the point \xi, which is a function of \xi. On the right side, we have the partial derivative of the function F with respect to its second argument y, evaluated at the point (\xi, b). This partial derivative is also a function of \xi.

So, we can rewrite this formula as [\varphi'(b)](\xi)=\frac{\partial F(\xi, b)}{\partial y}. Now, if we plug in the definition of \varphi'(b), we get [\varphi'(b)](\xi) = d\varphi_{b}(\xi). This means that the left side of the equation is the value of the differential of \varphi at the point b, evaluated at the point \xi. On the right side, we have the partial derivative of the function F with respect to its second argument y, evaluated at the point (\xi, b). This is exactly what we have in the formula you suggested, [\frac{\partial F}{\partial y}(\xi,b)](\eta).

In summary, the formula you suggested is indeed equivalent to the one stated in the theorem. The reason why \eta disappears in the original formula is because it is already contained in the definition of the differential d\var
 

FAQ: Differentia of function-valued mapping

What is a function-valued mapping?

A function-valued mapping is a mathematical concept where the outputs of a function are themselves functions. This means that the input values are mapped to functions rather than specific numerical values.

How is a function-valued mapping different from a regular function?

A regular function maps input values to specific output values, while a function-valued mapping maps input values to functions. This means that the output can vary depending on the input, and the output itself can also be a function.

What are some common examples of function-valued mappings?

One common example is a Fourier transform, where an input signal is mapped to a function representing its frequency components. Another example is the derivative operator, where a function is mapped to its derivative function.

How is the differentia of a function-valued mapping defined?

The differentia of a function-valued mapping is defined as the difference between two different function values at a specific input value. In other words, it is the change in the output function when the input value is changed by a small amount.

What is the significance of studying differentia of function-valued mappings?

Studying differentia of function-valued mappings is important in many fields of science, including mathematics, physics, and engineering. It allows us to analyze and understand the behavior of complex systems and functions, and make predictions about their future behavior. It also plays a crucial role in optimization and control theory.

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