Jeremy Côté

Sharing Your Research

Here’s a question for you: How do you describe your research?

No, I’m not talking about how you would describe it in technical detail for half an hour. Instead, what if you only had five minutes to explain? And worse, what if the person asking had barely any idea about the field you’re in?

Okay, I can see that you’re starting to get worried. That’s because it’s difficult! When you suddenly have to work with constraints and can’t rely on the fact that the other person has the background you do, creativity needs to be used to get the point across. It’s not enough to simply wave your hands and use impressive-sounding words. If you want to give the person a sliver of understanding, you’re going to need to do some work.

No matter your research topic, you should be able to give a compelling description of what you do in a variety of lengths (and preferably, formats). Can you sum up what you do in five minutes? Three minutes? One? A single sentence? On the other side of the spectrum, are you able to go longer, up to an hour or so?

These should all be within your abilities. That’s because you are the only advocate for your work (unless you have a whole press team behind you). If you want your work to succeed and be known to others, being able to describe it at various timescales is critical. Yes, I know this might sound like marketing that will only distract you, but it’s actually important. Doing science isn’t only about butting your head against a problem. It’s also about sharing your discoveries with the world. The whole world.

Of course, if you have more time you can go in greater depth, but the point is that you should always have a go-to way of explaining your scientific research for a variety of scenarios.

To give you some ideas, I’ll give it a try. Here’s how I would describe my research, in a few different timescales.

The one sentence executive summary

I use machine learning techniques to tackle problems in quantum computing.

The elevator pitch

Computers have errors, and we know how to fix them. Quantum computers will also have errors, but these are much more delicate to deal with. We can’t directly see the errors, so I come up with ways to make machines good at guessing the right corrections to implement in order for the errors to go away.

The abstract

I work on quantum error correction, which is a field that seeks to answer the question, “What is the best way to fix the errors that will accumulate on a quantum computer?” Specifically, I work on a system called the surface code, and my research involves neural networks that try and learn about how errors tend occur. Using this knowledge, they can then predict what kind of corrections to apply when they are only given an object called a syndrome, which is indirect information about the errors. The hope is that machine learning techniques can be used in actual quantum computers to make them more robust to errors.

I’ll stop here so that I don’t get into the really long timescales, but I think you get the idea. At each level, there’s something meaningful to be said about your research. Instead of thinking of this as less information → more information, it’s better to think of it in terms of the most efficient use of space. You won’t be able to get a lot across about your research in one sentence, but what can you communicate? It’s a challenge worth taking seriously, because attention spans are short and these are great opportunities to share what you know.

An objection might be that nobody can possibly understand the depth and significance of your research in such a concise form, so this makes it ripe for misunderstandings. That’s true, but it’s also where you come in. You’re the expert! Get across as much as you can, as accurate as you can, with the space you have. I’m not suggesting we throw out every other form of communication and relegate ourselves to a few sentences at a time. Instead, we should have the ability to talk about our scientific work across all timescales, not just the ones which are the lengths of talks or lectures1.

The best outcome here is that you find out your “short game” is lacking, and you work to fix it. Communication in science is crucial if you want your work to be understood by even a tiny fraction of people, so there shouldn’t be any artificial barriers put into place by you.

  1. Nor, for that matter, should these only be at the technical level of a graduate course.