Lecture notes on SUSY using finite matrix as example?

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SUMMARY

This discussion centers on the application of the factorization trick in Supersymmetry (SUSY), specifically using finite matrices as exemplified in Witten's "SUSY QM". The key point is the relationship between two Hamiltonians, \(H_0 = AA^+\) and \(H_1 = A^+A\), which share the same eigenvalues except for zeros. The proof involves taking an eigenvector \(\Psi\) of \(H_0\) and demonstrating that \(H_1 |A^+\Psi \rangle\) yields the same eigenvalue \(\lambda\). The discussion also highlights the search for lecture notes or blogs that illustrate this concept using finite matrices.

PREREQUISITES
  • Understanding of Supersymmetry (SUSY) concepts
  • Familiarity with Hamiltonians in quantum mechanics
  • Knowledge of matrix factorization techniques, specifically Cholesky factorization
  • Basic linear algebra, particularly eigenvalues and eigenvectors
NEXT STEPS
  • Research the factorization trick in Supersymmetry, focusing on finite matrix examples
  • Explore Witten's "SUSY QM" for detailed explanations and applications
  • Learn about Cholesky factorization and its role in quantum mechanics
  • Look for lecture notes or online resources specifically addressing SUSY transformations
USEFUL FOR

This discussion is beneficial for physicists, particularly those studying quantum mechanics and Supersymmetry, as well as students seeking to understand the mathematical foundations of these concepts through finite matrix examples.

arivero
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TL;DR
Eigen(AA^+)=Eigen(A^+A)
As you know, a lot of SUSY examples, particularly from Witten's "SUSY QM", pivot on the factorisation trick: produce two hamiltonians $$H_0=AA^+, H_1=A^+A$$ and see they have the same eigenvalues except for ceros.

The proof usually goes by: let ##\Psi## be an eigenvector of ##H_0##, consider ##|A^+\Psi \rangle ##, then $$H_1 |A^+\Psi \rangle =A^+AA^+\Psi=A^+H_0\Psi=A^+\lambda\Psi=\lambda|A^+\Psi \rangle$$
Now this can be already seen if A a 2x3 matrix, and I think that I have sometimes this example as an starting point but just now I can not locate it, do any of you remember perhaps a blog entry or, better, any set of lecture notes doing this? With finite matrices, I mean.

I got the idea of searching simultaneously for "susy lectures" and "Cholesky factorisation" but no results.
 
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Maybe try SUSY transformation and Cholesky factorization.
 

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