Making sense of the Differential of F at p, (where F: R^n -> R^m)

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In summary, the fundamental relation in this conversation is a simplified version of a map between real spaces. The right side of the relation has an implied sum over the index j and i is a free index on both sides. The symmetry of this relation is confusing as dFp is an operator on vectors in the domain, making it a matrix, but there is no implied sum on the left side. The difference between the symbol dFp on the left and the double-indexed derivative on the right is that the Jacobian matrix is the coordinate form, whereas dFp only names the operator. The essay linked in the conversation provides further explanation on this topic.
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bigbalpha
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I understand dFp as the jacobian (matrix of derivatives of F) but this specific relation shown below I am having a hard time understanding when I think of it in terms of matrix multiplication as an operator on a vector.
Here is a snip of the fundamental relation:
differential.PNG

This is from the book "Intro to Smooth Manifolds" and in this section it is simplified down to F as a map between just the real spaces R^n -> R^m (as shown above).
I understand the meaning of this relation, as the following: The rightside is the vector in the codomain of dFp, where the jacobian values are the components of the vector along the basis d/dy^j, mapped by dFp, from the i'th basis vector in the domain.

To my understanding, the rightside has an implied sum over the index j (1 - m), and i is a free index on both sides.

Fundamentally, the symmetry of this relation is what is confusing me. dFp is an operator, on vectors in the domain. This makes it a matrix (jacobian matrix), then how come there isn't an implied sum, just as on the rightside? And then what is the difference between the symbol dFp on the left, and the double-indexed derivative on the right (dF^j/dx^i), both are the jacobian matrix acting on vectors, right?
 

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bigbalpha said:
Fundamentally, the symmetry of this relation is what is confusing me. dFp is an operator, on vectors in the domain. This makes it a matrix (jacobian matrix), then how come there isn't an implied sum, just as on the right side?
Because it is the formula for the ##i-##th component, not the entire vector: ##w_i=A^j_iv_j##.
And then what is the difference between the symbol dFp on the left, and the double-indexed derivative on the right (dF^j/dx^i), both are the jacobian matrix acting on vectors, right?
Yes, but the Jacobian matrix is the coordinate form, whereas ##dF_p## only names the operator, regardless which coordinates are chosen.

If you like you can read our essay about it:
https://www.physicsforums.com/insights/the-pantheon-of-derivatives-i/
 

What is the differential of a function?

The differential of a function is a linear approximation of the function at a specific point. It represents the change in the function's output with respect to changes in its input variables.

Why is it important to make sense of the differential of a function?

Making sense of the differential of a function helps us understand how the function behaves around a specific point. It also allows us to approximate the function's output at nearby points and make predictions about its behavior.

How is the differential of a function calculated?

The differential of a function is calculated using partial derivatives. The partial derivatives are evaluated at the specific point and then combined to form a linear transformation, also known as the Jacobian matrix.

What does the differential of a function tell us about its behavior at a specific point?

The differential of a function tells us about the rate of change of the function at a specific point. It also gives us information about the direction in which the function is changing the most.

Can the differential of a function be used to optimize the function?

Yes, the differential of a function can be used to optimize the function by finding the critical points, where the differential is equal to zero. These points can be used to find the maximum or minimum values of the function.

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