Sum over Eigenvalues in Spectral Theory

In summary, the conversation discusses the use of the expression \sum_{n} e^{-u\lambda (n) } in mathematics, specifically in the fields of Calculus, Statistical Mechanics, and Quantum Physics. It is used to represent a partition function and involves the eigenvalues of a linear operator. The conversation also mentions the use of integrals in approximating the series and the rigorousness of this approach in mathematics.
  • #1
lokofer
106
0
"sum" over Eigenvalues...

Is there any mathematical meaning or it's used in Calculus or other 2branch" of mathematics de expression:

[tex] \sum_{n} e^{-u\lambda (n) } [/tex]

where every "lambda" is just an Eigenvalue of a linear operator:

[tex] L[y]=-\lambda _{n} y [/tex]

We Physicist know it as the "partition function" and is used in Statistical Mechanics and Quantum physics...in first approximmation:

[tex] \sum_{n} e^{-u\lambda (n) } = \iint dxdpe^{-uH} [/tex]

Where all the "eigenvalues" are positive...here i would like to hear if this "approach" using integrals would be rigorous from a math point of view...:tongue2:
 
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  • #2
lokofer said:
Is there any mathematical meaning or it's used in Calculus or other 2branch" of mathematics de expression:

[tex] \sum_{n} e^{-u\lambda (n) } [/tex]

where every "lambda" is just an Eigenvalue of a linear operator:

[tex] L[y]=-\lambda _{n} y [/tex]

:

I think it is rigorous as far as [tex]u[/tex] is small enough. That's what happens with the constant that multiplies the square of the principal quantum number when summing for obtaining the partition function for the translational motion, isn't it?.

We Physicist know it as the "partition function" and is used in Statistical Mechanics and Quantum physics...in first approximmation:

We Engineers call it the "partition function" too. :)
 
  • #3
Uh..sorry then "Clausius"... perhaps you as an engineer have heard about "Semiclassical approach" in Physics so you approximate the series by means of an integral, to calculate "Thermodinamic" entities...:rolleyes:
 
  • #4
It's spectral theory as done by analysts, say, or measure theorists. (Lots of things are called spectral and are unrelated, so be careful).
 

1. What is "Sum over Eigenvalues"?

"Sum over Eigenvalues" is a mathematical concept that involves adding together all of the eigenvalues of a given matrix. Eigenvalues are special numbers that are associated with a matrix and can help to understand its properties and behaviors.

2. Why is "Sum over Eigenvalues" important?

"Sum over Eigenvalues" is important because it can provide insights into the behavior of a matrix, such as its stability, convergence, and overall behavior. It is also used in various mathematical and scientific fields, such as physics, engineering, and computer science.

3. How is "Sum over Eigenvalues" calculated?

To calculate "Sum over Eigenvalues", you first need to find all of the eigenvalues of the given matrix. Then, simply add them together to get the sum. This can be done using various methods, such as diagonalization, power iteration, or using specialized software.

4. What are some real-world applications of "Sum over Eigenvalues"?

"Sum over Eigenvalues" has many real-world applications, such as in quantum mechanics, where it is used to understand the energy levels of particles. It is also used in data analysis and pattern recognition, where it can help to identify important features and reduce dimensionality.

5. Can "Sum over Eigenvalues" be negative?

Yes, "Sum over Eigenvalues" can be negative. This means that the sum of the eigenvalues is less than zero, which can happen if the matrix has mostly negative eigenvalues. This can have important implications for the behavior and stability of the system represented by the matrix.

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