Conjugate of a matrix and of a function

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SUMMARY

The discussion centers on the differences between the conjugate of a matrix and the conjugate of a function within linear vector spaces (LVS). It clarifies that the conjugate of a matrix involves replacing its entries with their complex conjugates, while the conjugate of a matrix with all real entries remains unchanged. The conversation also distinguishes between the conjugate and the conjugate transpose (or Hermitian transpose), which involves transposing the matrix and taking the conjugate of each entry. Additionally, it addresses the concept of adjoint linear transformations in inner-product spaces, emphasizing the relationship between a linear transformation and its adjoint through the conjugate transpose.

PREREQUISITES
  • Understanding of linear vector spaces (LVS)
  • Familiarity with complex numbers and their properties
  • Knowledge of matrix operations, including transpose and conjugate transpose
  • Basic concepts of inner-product spaces and linear transformations
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  • Study the properties of the adjoint of linear transformations in inner-product spaces
  • Learn about the applications of Hermitian matrices in quantum mechanics
  • Explore the differences between linear functions and their matrix representations
  • Investigate the implications of complex conjugates in various mathematical contexts
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Mathematicians, physicists, and students studying linear algebra, particularly those interested in the applications of matrices and linear transformations in quantum mechanics and functional analysis.

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Hello,

Working without complex numbers a conjugate of any function in a LVS is always the same thing. A conjugate of any matrix in a LVS is very often not the same thing though. I am just confused as to why functional spaces rely on complex numbers for the conjugate to have any importance and a matrix does not.
 
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Where did you see that? The "conjugate" of a matrix is just the matrix with the entries replaced by there complex conjugates. If M is a matrix with all real entries then the conjugate of M is just M itself.

You may be confusing "conjugate" with the "conjugate transpose" or "Hermitian transpose" of a matrix: swap rows and columns and take the conjugate of each entry. Of course, if M has all real entries, it "conjugate transpose" is just its transpose.
 
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HallsofIvy said:
Where did you see that? The "conjugate" of a matrix is just the matrix with the entries replaced by there complex conjugates. If M is a matrix with all real entries then the conjugate of M is just M itself.

You may be confusing "conjugate" with the "conjugate transpose" or "Hermitian transpose" of a matrix: swap rows and columns and take the conjugate of each entry. Of course, if M has all real entries, it "conjugate transpose" is just its transpose.

So guess my question is if functions are a different represenation of a matrix why is there no option to transpose a function?
 
In what sense is a function a "different representation of a matrix"? Are you talking about representing linear functions represented by a matrix?
 
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In my QM class Operator functions are said to be like a matrix.
 
I don't fully understand your question, but maybe you'd like to hear about the adjoint of a linear transformation.

Let V,W be inner-product spaces, let T\in L(V,W) be a linear transformation, and T^*\in L(W,V) its adjoint. This means that \langle Tv,w \rangle=\langle v,T^*w \rangle for all v\in V,w\in W. Then, the matrix of T^* with respect to orthonormal bases of V and W is just the conjugate transpose of the matrix of T with respect to these bases. As mentioned earlier, the conjugate transpose of a matrix is just the transpose (interchange rows and colums) of the matrix with all entries replaced by their complex conjugates.
 

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