Markov Chain Steady States via Eigenvalues
How does iterating u_{k+1}=Au_k make every Markov chain forget its starting distribution and converge to the λ=1 eigenvector — with the second-largest |λ| dictating the mixing rate?
Loading notebook...
This may take a moment on first load
Feynman technique
Learn with the Feynman Technique
Explain each idea in your own words in handwriting, then upload a photo for AI critique. Two attempts per question — there's no "right" answer, only depth of understanding.