Proof of matrix conjugate (for the complex numbers)

In summary, the problem asks to prove that the conjugate of A * the conjugate of B is equal to the conjugate of A*B, where A and B are matrices in the field of complex numbers. The key to the proof is to use the properties of conjugates for complex numbers and extend it to matrices by showing that the conjugate of a matrix is equivalent to the transpose of its complex conjugate.
  • #1
philnow
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Homework Statement



Supposing that A*B is defined (where A and B are both matrices in the field of the complex numbers), show that the conjugate of matrix A * the conjugate of matrix B is equal to the conjugate of A*B.

Homework Equations



None.

The Attempt at a Solution



I'm stuck. I've already shown that for 2 complex numbers z1 and z2, the conjugate of z1 + the conjugate of z2 is equal to the conjugate of (z1+z2). I've also shown that the conjugate of z1 * the conjugate of z2 = the conjugate of (z1*z2). My prof says to use the above to help with the proof.

I'm quite inexperienced with proofs, so any hint or tip would be extremely appreciated. Thanks.
 
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  • #2
you could try writing out th sum as elements

Ie say you have

C = AB

then for and elemnt of C at row i, & column j, each cij is given by the sum
cij = (sum over k) aikbkj

This reduces the matrix multiplication to addition & multiplication of individual complex numbers
 
  • #3
How, exactly, is your "conjugate" defined? The conjugate of a linear operator, A, on an innerproduct space over the complex numbers is defined as the linear operator A* such that, for all vectors u, v, <Au, v>= <u, A*v> where < , > is the inner product. It is easy to show that if A and B are linear operators, <ABu, v>= <Bu, A*v>= <u, B*A*v> so that B*A*= (AB)*.

If you have defined the conjugate of a matrix as "the matrix you get by swapping rows and columns and taking the complex cojugate of the matrix" (the complex conjugate of the transpose), then it would be useful to prove that <Au, v>= (Au)v= u(A*v)= <u, A*v> for row vector u and column vector v.
 

1. What is a matrix conjugate?

A matrix conjugate is a matrix that is formed by taking the complex conjugate of each element in a given matrix. This means that for each complex number in the original matrix, the conjugate matrix will have the same real part, but the imaginary part will be multiplied by -1.

2. Why is the matrix conjugate important in complex numbers?

The matrix conjugate is important in complex numbers because it allows us to simplify calculations involving complex numbers. By taking the conjugate of a matrix, we can easily find the inverse, transpose, and determinant of the original matrix.

3. How is the matrix conjugate calculated?

The matrix conjugate is calculated by taking the complex conjugate of each element in the original matrix. This means that the real part remains unchanged, but the imaginary part is multiplied by -1. For example, if we have a matrix A with elements a + bi, the conjugate matrix A* will have elements a - bi.

4. What is the difference between a matrix conjugate and a complex conjugate?

A matrix conjugate is a type of complex conjugate, but it is specifically used for matrices. While a complex conjugate is the reflection of a complex number over the real axis, a matrix conjugate is the reflection of a matrix over the real axis. Additionally, a complex conjugate can be applied to any complex number, while a matrix conjugate is only applicable to matrices.

5. How is the matrix conjugate used in applications?

The matrix conjugate is used in various applications, such as in signal processing, quantum mechanics, and electrical engineering. It is particularly useful in calculations involving complex numbers, as it simplifies the process and allows for easier manipulation of matrices. It is also used in solving systems of linear equations and in finding the eigenvalues and eigenvectors of a matrix.

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