Show this is a projection on a vector space

In summary, the linear operator T is defined as (1/2)(A+transpose(A)) for A in the vector space V of all nxn matrices over F. It is also a projection since T squared is equal to T, i.e. T(TA) = TA for all A. However, it is important to note that A is a projection when A squared is equal to A, not when (Ax) squared equals Ax.
  • #1
JaysFan31

Homework Statement


Let V=Mn(F) be the space of all nxn matrices over F; define TA=(1/2)(A+transpose(A)) for A in V.
Verify that T is not only a linear operator on V, but is also a projection.


Homework Equations


A is a projection when A squared=A.


The Attempt at a Solution


I don't see how this works since clearly (1/2)(A+transpose(A)) squared does not equal (1/2)(A+transpose(A)) for all matrices.

What am I doing wrong?
 
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  • #2
A is a projection when A2 = A, not when (Ax)2 = Ax. So you don't need to look at whether

[tex]\left [\frac{1}{2}(A + A^t)\right ]^2 = \frac{1}{2}(A + A^t)[/tex]

You need to look at whether T2 = T, i.e. whether T(TA) = TA for all A, i.e. whether:

[tex]\frac{1}{2}\left [\left (\frac{1}{2}(A + A^t)\right ) + \left (\frac{1}{2}(A + A^t)\right )^t\right ] = \frac{1}{2}(A + A^t)[/tex]

Remember, you're used to writing A for your linear operators, and vectors in your vector space V are normally written as x or v or something. But now you have matrices AS THE VECTORS IN YOUR VECTOR SPACE, so you'll probably use A to stand for a vector, and now T is the operator.

And you still need to check linearity.
 

Related to Show this is a projection on a vector space

1. What is a projection on a vector space?

A projection on a vector space is a linear transformation that maps a vector onto a subspace. This means that the projection maps the original vector onto a smaller vector space that is contained within the original space. It is similar to creating a shadow of an object on a wall, where the shadow is a projection of the object onto a 2-dimensional surface.

2. How is a projection on a vector space different from a projection in everyday language?

In everyday language, a projection usually refers to the act of predicting or estimating something. However, in the context of vector spaces, a projection is a mathematical operation that involves transforming a vector onto a subspace. It is a specific and precise term used in linear algebra.

3. What is the purpose of a projection on a vector space?

The purpose of a projection on a vector space is to simplify and analyze complex vector spaces. By projecting a vector onto a smaller subspace, we can reduce the dimensionality of the problem and make it easier to work with. Projections are commonly used in computer graphics, machine learning, and data analysis.

4. How is a projection on a vector space calculated?

A projection on a vector space is calculated using the inner product or dot product of two vectors. The projection of a vector v onto a subspace U can be written as ProjU(v) and is calculated as ProjU(v) = (v⋅u)u / (u⋅u), where u is a unit vector in the direction of the subspace U.

5. Can a projection on a vector space be reversed?

No, a projection on a vector space cannot be reversed. This is because the projection maps the original vector onto a subspace, resulting in a loss of information. Once a vector has been projected onto a subspace, it is impossible to reconstruct the original vector. However, the projection can be undone if the original vector is orthogonal to the subspace it was projected onto.

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