Using the Chicago Marathon to learn quantum complexity
On Oct. 12, I ran the 2025 Chicago Marathon, joining more than 50,000 people stretching the limits of human endurance through the neighborhoods of the Second City.
To comprehend that volume of runners, imagine a porta potty line stretching a city block – and multiply by about 200.
Imagine start corrals so full, those of us who endured that porta potty line…twice (I drank too much coffee and water when I woke up – call me well hydrated) couldn’t get into the football field-sized F corral until after the gun went off and our more punctual colleagues started to move onto the course. And G, H, I, J, K and M still had to line up behind us.
Imagine a flow of runners so long that I finished, stretched, found my family, ate an amazing Korean bowl lunch (love you, Seoul Spice) and played for an hour with my kid on the Maggie Daly playground and people were still running.
Now imagine each of those 50,000 runners, from the elites to the rear guard, having some kind of a relationship with each of the others. And hold that thought.
Almost every one of these runners had a phone camera with them, and large numbers of them were documenting along the way. Watching my Instagram feed the days after, seeing the same race from so many different angles, made me think that in a weird way, every one of the runners, from the winners and national record setters to the mid-packers to the last people to get swept to the sidewalks by trucks had some kind of a connection to every other one.
It also made me think of something I struggled to write about about the week before the marathon: quantum complexity.
Quantum complexity refers to the vastly complicated interactions that happen when nature’s smallest particles interact. Understanding it is important to physicists and other material scientists who want to do things like develop useful superconductivity (electron flow free of resistance) and useful quantum computers.
In my story, I wrote about Cornell physicists and computer scientists who have developed a machine learning architecture that is helping them quantify quantum complexity. Bringing it a tiny bit closer to my experience, this machine learning system is inspired by the large language models (LLMs) behind ChatGPT and similar products. Not that this helps me understand how it works, but it gives a tiny bit of context.
My main Cornell physics contact for this story described their mission to understand quantum complexity “challenging,” which I take to mean entire data centers working full time for a year still wouldn’t complete one problem. “It’s a great opening for AI methods to come in and help,” she said.
So they’ve found a shortcut, using approximations and organizing the AI like a large language mode. By treating each snapshot (I imagine electrons caught mid-stride with silly or embarrassing looks on their faces) like a token the way ChatGPT treats each word like a token, the scientists can learn this shape of the probabilistic distribution.
Among 50,000 runners and nearly as many cell phones, more than a million snapshots must have been taken during the Chicago Marathon, each capturing all those runners in one of relations to each other. For instance, my friend T started in a different corral and at a different time than me. But she found me at about Mile 20 and we ran along together for about a mile. Then we got separated again. Further snapshots would catch me the moment Runner 21574 gives me a thumbs-up or Runner 17399 cuts me off to high-five some kids or Runner 36511 spills Gatorade on me.
Do I understand quantum complexity any better? A tiny bit. And I am appreciating the way my brain scratches at something until it finds a way in.
Did I enjoy my Chicago Marathon experience? Yes. I could have been braver at the start and paced myself better for a faster time. But I had a great time out there, running through a non-stop tunnel of cheering, one happy little electron flowing through a highly-charged day.
I’m sure I’ll write more about quantum research, so I’d better find good ways to represent it to myself. It’s comforting to me to know the researchers themselves use analogies. Next time I talk to one of these physicists, I might ask them about my marathon comparison.
And next time I run a marathon, I’m bringing my phone/camera along. From all those 26.2 miles, I only have one photo. Although I’m sure I appear in several more.
