Continuous set of eigenvalues in matrix representation?

In summary, observables are represented by Hermitian operators in matrix form with eigenvalues on the diagonal. However, for observables with continuous spectra, the representation is not a matrix but a distribution, as seen with the position operator in one-dimensional space. The action of the operator in such cases is given by a convolution integral, which is simplified in position representation.
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nomadreid
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Let's see if I have this straight: Observables are represented by Hermitian operators, which can be, for some appropriate base, represented in matrix form with the eigenvalues forming the diagonal. Sounds nice until I consider observables with continuous spectra. How do you get something like that into matrix form?
 
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  • #2
The representation of operators in the eigenbasis is not a matrix, if there are continuous spectra. Then you have distributions. Take the position representation of the position operator in one-dimensional space. Its spectrum is entirely continuous (entire ##\mathbb{R}##). It's position representation is
##X(x_1,x_2)=\langle x_1|\hat{x} x_2 \rangle=x_2 \delta(x_1-x_2).##
That's not a matrix but a distribution. The action of the operator on a vector in such a case is not given by a usual matrix-vector product but by a convolution integral. Of course, in position representation that's very simple
##\langle x|\hat{x} \psi \rangle=\int_{\mathbb{R}} \mathrm{d} x' X(x,x') \langle x'|\psi \rangle=\int_{\mathbb{R}} \mathrm{d} x' X(x,x') \psi(x')=x \psi(x)##
as it must be due to the direct evaluation
##\langle x|\hat{x} \psi \rangle = \langle \hat{x} x|\psi \rangle=x \langle x |\psi \rangle=x \psi(x).##
 
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  • #3
Thanks very much, vanhees71. That clears up my question completely. :)
 

Related to Continuous set of eigenvalues in matrix representation?

1. What is a continuous set of eigenvalues in matrix representation?

A continuous set of eigenvalues in matrix representation refers to a set of eigenvalues that form a continuum or a range of values rather than a discrete set. This means that the eigenvalues are not isolated points on the number line, but rather they are connected and can take on any value within the range.

2. How is a continuous set of eigenvalues represented in a matrix?

A continuous set of eigenvalues is represented in a matrix as a diagonal matrix, where the eigenvalues are the entries on the main diagonal and all other entries are zero. This allows for easy identification and manipulation of the eigenvalues in the matrix representation.

3. What is the significance of a continuous set of eigenvalues in matrix representation?

A continuous set of eigenvalues is significant because it allows for a more accurate representation of a system or process. In many real-world scenarios, the eigenvalues are not discrete and can take on a range of values. By representing them as a continuous set, we can better understand and analyze the behavior of the system.

4. How does a continuous set of eigenvalues differ from a discrete set of eigenvalues?

A continuous set of eigenvalues differs from a discrete set in that the eigenvalues are not isolated points, but rather they form a range of values. In a discrete set, the eigenvalues are distinct and do not have any values in between them. This can be seen in the representation of a discrete set as a diagonal matrix with only non-zero entries on the main diagonal.

5. Can a continuous set of eigenvalues have infinite values?

Yes, a continuous set of eigenvalues can have infinite values. This is because a continuous set represents a range of values, which can extend to infinity in both directions. This is different from a discrete set, where the number of eigenvalues is finite and can be counted.

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