Assistant Project Scientist
Member of Leonid Pryadko's research group in the Department of Physics Developing models of random graph percolation: establishing algebraic bounds on the percolation threshold using the non-backtracking spectrum of a graph and incorporating weighted and correlated random processes. Applications include quantum error correction and fault tolerance. - Supporting algebraic analysis with numerical simulations of directed graphs of > 10,000 nodes.- Written and debugged Python code utilizing libraries NetworkX, Numpy/Scipy and Pandas to simulate random percolation process and search for, count and analyze connected components - Written code for Mathematica for symbolic calculation of spectral radius of large sparse matrices