Can A Square Matrix with AA^T = A^TA = I_n Have a Determinant of \pm 1?

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Discussion Overview

The discussion revolves around the properties of square matrices, specifically addressing whether a square matrix \( A \) that satisfies the conditions \( AA^T = A^TA = I_n \) can have a determinant of \( \pm 1 \). The conversation includes attempts to prove this property and touches on related matrix concepts.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant asserts that if \( AA^T = A^TA = I_n \), then \( \det{A} = \pm 1 \), suggesting a proof involving the determinant properties of matrix products.
  • Another participant confirms the proof by stating that \( \det{AA^T} = \det{A}\det{A^T} = \det{A}^2 = \det{I_n} = 1 \), leading to the conclusion that \( \det{A} = \pm 1 \).
  • Some participants express frustration with the course material, indicating that they find the proving techniques challenging.
  • Several posts diverge into discussions about proving properties of symmetric matrices and the conditions under which matrix operations are defined, which are not directly related to the original question about the determinant.
  • There are questions about the necessity of certain mathematical expressions and whether specific assumptions are correct, indicating uncertainty in understanding the proofs presented.

Areas of Agreement / Disagreement

While there is a general agreement on the assertion that \( \det{A} = \pm 1 \) follows from the given conditions, the discussion also reveals a lack of consensus on the clarity and correctness of the proofs and related concepts, with some participants expressing confusion and seeking further clarification.

Contextual Notes

Participants express uncertainty regarding the assumptions made in their proofs and the definitions of matrix properties, indicating that the discussion may be limited by varying levels of understanding and familiarity with the material.

Nusc
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Prove that, if [tex]AA^T = A^TA = I_n[/tex], then [tex]\det{A} = \pm 1[/tex].

This is daunting.
 
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try w/o the spaces btw the brackets and the "tex". you don't need to rewrite [ tex ] on both sides of the "=" u know.

[tex]AA^T = A^TA = I_n[/tex]

then

[tex]\det{A} = \pm 1[/tex]
 
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As for the solution:

[tex]\det{AA^T} = \det{A}\det{A^T} = \det{A}^2 = \det{I_n} = 1 \Leftrightarrow \det{A} = \pm 1[/tex]
 
omg that's it. i hate this course
 
don't hate the course because it is daunting; see it as a challenge. as you see the answer is straight forward (i presume that's what the 'omg that's it' means), and all the answers are like that. just be calm and check your notes for things
 
I just have to get used to the proving techniques
 
Prove that any scalar multiple of a symmetric matrix is symmetric.

Let [tex]A = (a_i_j)[/tex]

Since [tex]A[/tex] is symmetric, [tex]A = A^T[/tex].

Then [tex]A^T = (a_i_j)[/tex].

Therefore, [tex](cA) = c(A) = c(A^T) = (cA^T)[/tex]

Was it necessary to show that [tex]A = (a_i_j)[/tex] and [tex]A^T = (a_i_j)[/tex]? Is [tex]A^T = (a_i_j)[/tex] even right? I can't express myself mathematically
 
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Prove that, if A and B are two matrices such that A + B and AB are defined, then both A and B are square matrices.


- Let A be an m x r matrix and B an r x n matrix such that,
[tex]A_m_x_rB_r_x_n = (AB)_m_x_n[/tex]

- We know that the sum A + B of the two matrices is the m x n matrix

How do I express this mathematically to show that they are square?
 
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Nusc said:
Prove that any scalar multiple of a symmetric matrix is symmetric.

Let [tex]A = (a_i_j)[/tex]

Since [tex]A[/tex] is symmetric, [tex]A = A^T[/tex].

Then [tex]A^T = (a_i_j)[/tex].

Therefore, [tex](cA) = c(A) = c(A^T) = (cA^T)[/tex]

Was it necessary to show that [tex]A = (a_i_j)[/tex] and [tex]A^T = (a_i_j)[/tex]? Is [tex]A^T = (a_i_j)[/tex] even right? I can't express myself mathematically

Just put the 'T' out of the brackets at the end (that is, over all of: cA).
 
  • #10
Nusc said:
Prove that, if A and B are two matrices such that A + B and AB are defined, then both A and B are square matrices.


- Let A be an m x r matrix and B an r x n matrix such that,
[tex]A_m_x_rB_r_x_n = (AB)_m_x_n[/tex]

- We know that the sum A + B of the two matrices is the m x n matrix

How do I express them together to show that they are square?

If A+B is defined, then their sizes are similar- i.e., they're both mxn.
Since AB is defined, as you yourself wrote, we must have m=n. (Because the product is an mxn*mxn, which is only defined when m=n).
Both matrices are therefor nxn, square matrices!
 
  • #11
Oops typo, thanks.
 
  • #12
Palindrom said:
Since AB is defined, as you yourself wrote, we must have m=n. (Because the product is an mxn*mxn, which is only defined when m=n).
Both matrices are therefor nxn, square matrices!

The r in A is the jth column and in B it's the ith row. So when you say m=n, are you referring to the r's?

And if I were to prove that any scalar multiple of a diagonal matrix is a diagonal matrix, how is that different from, say, letting [tex]A = (a_i_j)[/tex] be any m x n matrix and c any real number?

A diagonal matrix is a square matrix that all of its nonzero entries are on the diagonal.

Then [tex]cA = c(a_i_j) = (ca_i_j)[/tex] but it may not be diagonal.

I guess we assume that [tex]A = (a_i_j)[/tex] is a diagonal matrix?
 
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  • #13
Nusc said:
The r in A is the jth column and in B it's the ith row. So when you say m=n, are you referring to the r's?

And if I were to prove that any scalar multiple of a diagonal matrix is a diagonal matrix, how is that different from, say, letting [tex]A = (a_i_j)[/tex] be any m x n matrix and c any real number?

A diagonal matrix is a square matrix that all of its nonzero entries are on the diagonal.

Then [tex]cA = c(a_i_j) = (ca_i_j)[/tex] but it may not be diagonal.

Yes, I was referring to the 'r's.
And I'm sure I got your question. It's true that for any matrix A=(aij) that keeps aij=0 for all i!=j, cA keeps the same thing for any scalar c. In the private case of square matrix, it shows that any scalar multiple of a diagonal matrix is, indeed, a diagonal matrix.
Did I answer your question? :rolleyes:
 
  • #14
Yeah thanks, but I will be back with more
 
  • #15
Is that a threat?

Anyway, I'm off to bed. Be back in about 12 hours... (It's the middle of the night here).
 
  • #16
Haha what?
 

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