What If Your Random Walk Could Walk Twice As Fast, Without Breaking the Laws of Physics?

Biography
Dr. Tushar Vaidya is a researcher in applied probability and quantum computing. With a solid background in quantitative finance, having worked as a trader and quantitative strategist in fixed income derivatives, he brings practical industry insights to his academic pursuits. His current research encompasses algebraic AI and quantum algorithms for tackling fundamental problems in machine learning. His work includes using algebraic geometry to solve puzzles and employing probability theory to address new challenges in social networks and interacting particle systems. The thrust of his work lies in the development of mathematical techniques drawn from both algebra and analysis.

Lecture Abstract
What happens when we let a particle “walk” using the rules of quantum mechanics? Starting from the simple idea of a coin flip and a step left or right, we’ll see how quantum interference changes motion itself. Classical random walks spread slowly, distance grows only as the square root of the number of steps, but quantum walks spread linearly, much faster. This talk introduces the mathematics and intuition behind quantum walks in an accessible way. No prior knowledge of quantum mechanics is assumed: only curiosity about how probability, walks and computation meet. Intuition will be stressed.