Quantum Computing Explorations
In the past year, I’ve had the pleasure of jumping into a great number of new things. The biggest shift, of course, was starting my new position at Texas A&M in May, 2020. The transition was a bit harder than usual, thanks in part to the global pandemic, but the social isolation paired with moving to a strange new land permitted me to allow myself the pleasure of getting into things that may not have an immediate payoff. While I hope to put together another of my famed “Yearly Updates”, this post will highlight some interesting excursions into quantum computing that I stumbled into earlier this year.
The starting point for most of this was the announcement of the IBM Quantum Challenge in April of this year. I actually missed the announcement, however, and got started halfway through the four day event and to make up lost ground. The exercises in the challenge started out at the introductory level and then focused on some specific problems and implementations in quantum computing, culminating in a bit of an optimization problem where you were meant to find an optimal circuit representation of a generic unitary matrix. The first three challenge went rather fast (with the third one in particular being a fun python problem in addition to implementing a quantum algorithm), though I struggled with the final one for a few hours on the final day. I did manage to “solve” the challenge, though my solution was quite inefficient and was far from the optimal solution at the top of the leaderboards. I eventually managed to match the second highest score after the challenge by reading an information thread someone posted, but I was much prouder of my own, hacky method. If you’d like to try your hand at the challenges, you can find them on Github. Unfortunately I did my solutions on the IBM notebook server, so I can’t readily link them here.
The next big personal milestone in getting involved with this exciting field was another event that I got engaged with through random chance as part of the Lindau Sciathon. I was scrolling through the project descriptions when I saw one that wanted to build an open science platform that made it easier to get into quantum computing. Once we got started with the full group, we realized that the focus should turn away from the hardware-first approach that the project proposal had put forth and instead try to make something more general that could be picked up by anyone and could be expanded to include extensions to the project in the future. We settled on a simple story-based approach to explaining complex topics in the same vein as Quantum Physics for Babies by Chris Ferrie. We built this story within a Jupyter notebook so that anyone could also follow along with the implementations of these concepts as well. You can find a link to the notebook on Google Colab here and can step through it after making a local copy. The code relies on a library hacked together by Martin Pauly and myself that was originally written for the IBM Quantum Challenge mentioned above, so things have truly come full circle. To see a more detailed overview, check out the great piece written by Aleksander Kubica for the Caltech Quantum Frontiers blog here and many thanks to my teammates Shuang, Martin, Aleksander, Hadewijch, Saskia, Michael, Bartłomiej, Ahmed, and Watcharaphol.
I’ve had a blast this year with my two spontaneous dives into quantum circuit design and implementation, and I sincerely hope that my exposure doesn’t end there. After getting the basics dumped on me during the IBM weekend challenge, I’ve began looking into domain specific problems and solutions and have started to form a few potential ideas for how I can bring this technology to the research questions I care about most. I’m finding some excellent work is being done in this field and it’s quite honestly hard to keep up with the impressive advances that occur on the regular. If anything cool comes out from my playing in the quantum sandbox, expect a feature on it when I compose my future yearly update posts.