Ezra Savard

As a first step in my undergraduate research on simulating physical quantum annealing, I wrote some Monte Carlo solver. I wrote my first implementation of a path-integral Quantum Monte Carlo (PI-QMC) in Python using numpy linear algebra operations. The code quality was not great though and it was not particularly nice to use. So a few weeks ago, I decided to re-write it as something I would be happy to share with others, so here it is!

From January until late August of 2016, I pursued undergraduate research on simulating physical quantum annealing. In this post I’m going to give an overview about D-Wave, quantum annealing, heuristic optimization algorithms, and then touch on what I was researching exactly.

I was tinkering around with my partner’s LED wake-up light project and decided to try upgrading her PWM to a super smooth 16-bit version. Her original code used the Arduino analogWrite() method and worked quite well at higher values, but zero to one was a bit of a jump.