Linear algebra - squaring via transformations

In summary, the conversation is discussing a transformation F from P_4 (the space of polynomials over R of degree <4) to P_7 (the space of polynomials over R of degree <7), where F is defined as F(p(x)) = (p(x))^2. The conversation also mentions a matrix A representing F with respect to two bases, and a question about the linearity of F.
  • #1
Niles
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0

Homework Statement


I have a transformation (not linear! that is what I have to show) F given by:

F : P_4 -> P_7 (P_7 is the vector-space spanned by polynomials less than degree 7). I also know that F(p(x)) = (p(x))^2.

The matrix A representing F with respect to the two basis is the one I get by taking the transformation F on P_4's elements [x^3, x^2, x, 1] and expressing by P_7's elements. I get a 7x4-matrix with 4 zeroes and the rest are zero-entries.

The Attempt at a Solution


This matrix is the matrix A in L(x) = Ax. So if I take a polynomial in P_4 and multiply with A, it should be squared:

A*(a_1*x^3, a_2*x^2, a_3*x, a_0)^T.

But this doesn't make a_1*x^3 go to (a_1)^2*x^6 and so on? Where am I going wrong?

I hope you understand my questions.


Niles.
 
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  • #2
I don't really understand what you're asking. You're saying that F is not linear, but then you say it's represented by the matrix A.

What are you trying to do exactly? Prove that the mapping F:P_4->P_7 (where P_n is the space of polynomials over R of degree <n) given by F(p(x))=(p(x))^2 is linear? Well, it's not! For example: F(x+x) = F(2x) = 4x^2, which is not equal to F(x)+F(x)=2x^2.
 

What is linear algebra?

Linear algebra is a branch of mathematics that deals with the study of linear equations and their transformations. It involves the use of matrices and vectors to represent and solve systems of linear equations.

What is squaring via transformations?

Squaring via transformations is a method used in linear algebra to find the square of a matrix. It involves breaking down a matrix into a series of linear transformations, squaring each transformation, and then combining them back together to get the square of the original matrix.

Why is squaring via transformations useful?

This method is useful because it allows us to quickly find the square of a matrix without having to perform manual calculations. It also helps us understand the relationship between matrices and their transformations.

What are some applications of linear algebra and squaring via transformations?

Linear algebra and squaring via transformations have a wide range of applications in fields such as physics, engineering, computer graphics, and data analysis. They are used to solve complex systems of equations, perform image and signal processing, and analyze large datasets.

What are some common mistakes when working with linear algebra and squaring via transformations?

Some common mistakes include forgetting to apply the proper order of operations when squaring the transformations, confusing row and column operations, and making errors in matrix multiplication. It is important to pay attention to details and double-check calculations to avoid these mistakes.

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