Eigenvalue for Orthogonal Matrix

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An orthogonal matrix Q has the property that its transpose Q^T is also its inverse. Given that λ_{1} = 1 is an eigenvalue of Q with corresponding eigenvector x, it follows that Qx = x. By applying the transpose, the relationship (Qx)^{T} = x^{T}Q^{T} can be established. This leads to the conclusion that x is also an eigenvector of Q^{T} corresponding to the eigenvalue λ_{1} = 1. Understanding the properties of orthogonal matrices simplifies the proof significantly.
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Homework Statement



Let Q be an orthogonal matrix with an eigenvalue λ_{1} = 1 and let x be an eigenvector belonging to λ_{1}. Show that x is also an eigenvector of Q^{T}.

Homework Equations



Qx = λx where x \neq 0

The Attempt at a Solution



Qx_{1} = x_{1} for some vector x_{1}

(Qx_{1})^{T} = x_{1}^{T}Q^{T}


I'm kind of stuck with how to start this problem, as I'm not sure what I've done is even starting down the right path. Can anyone give me a nudge in the right direction?
 
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What's (Q^T)(Q) if Q is real orthogonal?
 
Thank you. I didn't realize what an orthogonal matrix was (yikes!). Once I did the proof fell right out of the definition.
 
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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