This repository implements this new paper that allows us to calculate eigenvectors from eigenvectors elegantly through PyTorch.

I ported this to PyTorch as a lot of my workflows are on the GPUs with PyTorch.

PETER B. DENTON, STEPHEN J. PARKE, TERENCE TAO, AND XINING ZHANG

We present a new method of succinctly determining eigenvectors
from eigenvalues. Specifically, we relate the norm squared of the elements of
eigenvectors to the eigenvalues and the submatrix eigenvalues.

This is the core equation you will notice being referenced as equation 2 in the code.

• PyTorch 1.3.1 (can be most versions of PyTorch as I used very core basic PyTorch functions)
• Python 3.6

• If you would like to give some credit to this implementation, these are the relevant links.
  • 
  • Eigenvectors from Eigenvalues CPU and GPU Implementation

• Original authors' paper: Eigenvectors from Eigenvalues
• Quantamagazine article: Neutrinos Lead to Unexpected Discovery in Basic Math
• Leo Dirac numpy implementation

MIT