Eigenvalues and Eigenvectors of 2x2 Matrix | Homework Help

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Homework Help Overview

The discussion revolves around finding the eigenvalues and corresponding eigenvectors of the matrix [1,1;1,1]. Participants are exploring the methods to derive these values and the implications of their properties.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss solving the determinant to find eigenvalues and the subsequent steps to find eigenvectors. There is mention of different methods, including setting up equations based on the eigenvalue definition and row reduction techniques. Questions arise about the implications of choosing values for variables in the context of eigenvectors.

Discussion Status

The discussion is active, with participants providing guidance on how to approach the problem and clarifying concepts related to eigenvectors and their properties. There is an acknowledgment of the infinite nature of eigenvectors corresponding to a given eigenvalue, and some participants are exploring the dimensionality of the eigenspace.

Contextual Notes

Participants are navigating the definitions and properties of eigenvalues and eigenvectors, with some uncertainty about the implications of their choices in solving for eigenvectors. The discussion reflects a mix of understanding and questions about the methods being employed.

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Homework Statement



Find the eigenvalues and correspointing eigenvectors of the matrix:

[1,1;1,1]

Homework Equations





The Attempt at a Solution



I can solve the determinant to get the eigenvalues: e1=2, e2=0, and from here I am supposed to sub these values back into my matrix and find the eigenvectors, right? I'm not sure how to perform this process though...
 
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hex.halo said:
Find the eigenvalues and correspointing eigenvectors of the matrix [1,1;1,1]

I can solve the determinant to get the eigenvalues: e1=2, e2=0.

Hi hex.halo! :smile:

The standard way (which you must be able to do): just write [1,1;1,1](a,b) = (0,0), and solve; and the same for [1,1;1,1](a,b) = (2a,2b). :smile:

(And the shortcut in this case: the eigenvectors for M + a.I are the same as for M, for any matrix M and any number a … so just look for the eigenvectors of [0,1;1,0], which you can probably guess! :smile:)
 
Some people (on this board) use a "complicated method" of putting the eigenvalues into the matrix A-\lambda I and row reducing but I much prefer tiny-tims method: any eigenvector, by definition, must satisfy Av= \lambda v. Set up that equation and solve for v.
For example, with eigenvalue 2, you must solve
\left[\begin{array}{cc}1 &amp; 1 \\ 1 &amp; 1\end{array}\right]\left[\begin{array}{c} x \\ y\end{array}\right]= \left[\begin{array}{c} 2x \\ 2y\end{array}\right][/itex]<br /> You will NOT be able to solve for both x and y, only for y, say, as a function of x because any multiple of an eigenvector is also an eigenvector. Choose any convenient value of x, calculate the corresponding y, and any eigenvector is a multiple of that.
 
¿ "board" ?​

oh … do you mean "planck" … ? :biggrin:

(:confused: I take two!)
 
So, you're telling me that I need to solve y in terms of x from that (very nice) matrix set up, then I can sub in ANY number for x that I want to get my eigenvector and have the right answer? Wouldn't this result in an infinite number of correct eigenvectors? Actually, don't worry about that, I imagine i'll have that explained to me at some point. What I'd really like to know is, for any question, am I right to sub in 1 for my x value then just put a scalar multiple out the front of the matrix to represent all the multiples and that would be correct?
 
Yes, of course! If v is an eigenvector corresponding to eigenvalue \lambda, then so is any number times v. The set of all eigenvectors corresponding to a given eigenvalue forms a subspace! That always has an infinite number of vectors.

Yes, if you choose anyone of the vectors in the (one-dimensional) subspace, any other can be written as a multiple of it. You can choose x (or y and then solve for x) to be any number you please. "1" seems like a simple choice!

It is possible that the set of eigenvectors corresponding to an eigenvalue is a subspace of dimension larger than 1. For a 2 by 2 that would of course be all of R2. In that case that the matrix is larger than 2 by 2, with a single eigenvalue having "eigenspace" of dimension greater than 1, solving the equation Ax= \lambda x would give an equation where other variables depend on two (or more) of the variables. In that case, taking them to be 1 and 0, then 0 and 1 should give you independent basis vectors for the subspace.
 

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