How can I understand linear functions and their matrices in polynomials?

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Understanding linear functions and their matrices in the context of polynomials involves recognizing that the derivative operator is a linear function because it satisfies the properties of closure under vector addition and scalar multiplication. The discussion emphasizes the importance of precise definitions in mathematics, particularly the criteria for linearity, which include the additive and scalar multiplication properties. To find the matrix representation of a linear transformation, one must apply the transformation to each basis vector and express the results in terms of the chosen basis. The conversation also touches on the significance of the vector space of polynomials of degree three or less and the implications for derivatives and their matrices. Mastery of these concepts is crucial for a deeper understanding of linear functions in polynomial contexts.
mrroboto
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I should just give math up, I don't understand this at all. It seems like for a) the function could be squared, and other than that it doesn't make any sense.


Let V = {p element of R[x] | deg(p) <=3} be the vector space of all polynomials of degree 3 or less.

a) Explain why the derivative d/dx: V -> V is a linear function

b) Give the matrix for d2/dx2 in the basis {1,x,x^2, x^3} for V

c) Give the matrix for the third derivative d2/dx2: V->V using the same basis

d) Give the matrix for the third derivative d3/dx3: V->V using the same basis

e) Give a basis for ker(d2/dx2)

f) what is the matrix for the linear map (d/dx + 4(d3/dx)): V->V

g) Let T: R[x] ->R[x] be the function T(p(x))= integral from -2x to 2 of p(t)dt

Explain why T is an element of L(R[x])
 
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OK, let's start with a)
What does it mean for a function to be linear?
What is the formula you have to check, that needs to be true for a linear function f?
 
That is is closed under vector addition and scalar multiplication? In this case, the derivative's dimension will always be a square (or less), and it is closed under addition because added two squares will always be within a cube, and it is closed under multiplication because any constant times a square will still be within a cube.
 
I think your problem is that you don't learn the definitions well enough! In mathematics, all definitions are "working" definitions- you use the precise words of the definition in proofs and problems.

My point is that you were asked, "What does it mean for a function to be linear?" by Compuchip and answered, "That is is closed under vector addition and scalar multiplication? " That has nothing to do with functions at all- that is a definition of "subspace". A function f(x) on a vector space is linear if and only if f(u+ v)= f(u)+ f(v) and f(av)= af(v) for any vectors u and v and scalar a. If p(x) and q(x) are in your set of polynomials, what is d(p+q)/dx? If, also, a is a number, what is d(ap(x))/dx?

A standard way of finding the matrix representing a linear transformation in a given basis is to apply the linear transformation to each basis vector in turn. The coefficients of the result, written in that basis, form the colums of the matrix.
 
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Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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