Find eigenvalues & eigenvectors

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The discussion revolves around finding eigenvalues and eigenvectors for a given matrix problem. A method is proposed for quickly determining eigenvectors by manipulating the matrix after substituting the eigenvalue. It is confirmed that the eigenvectors presented are equivalent up to a constant factor, despite being in opposite order. The validity of the method is supported by the fact that any scalar multiple of an eigenvector remains an eigenvector of the same eigenvalue. The conversation concludes with an acknowledgment of understanding the relationship between the eigenvectors and eigenvalues.
rugerts
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Homework Statement
Find eigenvalues & eigenvectors
Relevant Equations
det(A-r*I) = 0
IMG-2047.JPG
Here's the problem along with the solution. The correct answer listed in the book for the eigenvectors are the expressions to the right (inside the blue box). To find the eigenvectors, I tried using a trick, which I don't remember where I saw, but said that one can quickly find eigenvectors (at least for simple 2x2 cases like these) by simply taking a row (of the matrix after having plugged in the eigenvalue) and shaping it such that the leftmost value is the first value for the eigenvector (with opposite sign) and the second eigenvector value is the same as the rightmost value. I heard that this is valid for either row choice... but when I do this, the answers appear to be different (hence the question mark over the inequality). So, my question is, are these eigenvectors shown in the blue box equivalent to one another? Does this trick really work? It seems to.
Thanks for your time.
 
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Sort of. Those are the same two eigenvectors up to a constant, but in opposite order.

Multiply your ##\vec v## by the constant (1 + i). As you know, any multiple of an eigenvector is still an eigenvector of the same eigenvalue.
$$(1 + i) {2 \choose {2 - 2i}} = {{2 + 2i} \choose {2(1 - i)(1+i)}} = {{2+2i} \choose 4}$$
and similarly multiply ##\vec w## by the constant (1 - i).
$$(1 - i) {2 \choose {2 + 2i}} = {{2 - 2i} \choose {2(1 + i)(1-i)}} = {{2-2i} \choose 4}$$
Since the order is reversed, so are the eigenvalues with which each is associated.
 
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Also, you can verify that your eigenvalues and eigenvectors are correct or not by plugging them into the matrix equation and determining whether ##(A - \lambda I) \vec x = \vec 0##.
 
RPinPA said:
Sort of. Those are the same two eigenvectors up to a constant, but in opposite order.

Multiply your ##\vec v## by the constant (1 + i). As you know, any multiple of an eigenvector is still an eigenvector of the same eigenvalue.
$$(1 + i) {2 \choose {2 - 2i}} = {{2 + 2i} \choose {2(1 - i)(1+i)}} = {{2+2i} \choose 4}$$
and similarly multiply ##\vec w## by the constant (1 - i).
$$(1 - i) {2 \choose {2 + 2i}} = {{2 - 2i} \choose {2(1 + i)(1-i)}} = {{2-2i} \choose 4}$$
Since the order is reversed, so are the eigenvalues with which each is associated.
Ahh, I see. Thank you
 
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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