Physics

Every few months, some headline says quantum computers just broke encryption or solved a problem that classical computers could never solve. Then a physicist clarifies that it was a 5-qubit system running at near absolute zero that factored the number 15.

I got into quantum computing because I was into astrophysics and classical physics, but I’d never really explored quantum computing, and I wanted to learn about a completely different side of physics.

Here's what actually happens. A classical computer uses bits: 0 or 1. A qubit can be in a superposition of both until you measure it, at which point it collapses to one. That part everyone's heard of. What nobody thinks about or explains is why that's useful, and more importantly, why it's so hard to use.

The trick isn't that a quantum computer tries every answer at once. That's the most common misconception out there, and it's wrong. If it did that, you'd just measure it and get a random answer, which is useless. The real trick is interference. You design your algorithm so that wrong answers cancel each other out (destructive interference) and right answers reinforce each other (constructive interference). So when you finally measure, the correct answer has the highest probability of showing up. That's the thing about quantum computing: it's all probability, never certainty.

The reason quantum computers aren't solving anything big right now is that qubits are hard to maintain and hard to scale. Your phone's processor can sit on your desk and get warm. A qubit needs to be isolated from basically everything (vibrations, heat, stray electromagnetic fields) because any interaction with the environment collapses the superposition. This is called decoherence, and it's the problem a lot of people miss when talking about quantum. Right now, most quantum processors operate at temperatures colder than outer space. The error rates are still high enough that you need error correction, and error correction requires many physical qubits per logical qubit; estimates range from hundreds to thousands. So when a company says they have a 1,000-qubit machine, that doesn't mean 1,000 reliable logical qubits doing useful computation. It's more complicated and less impressive than the headline suggests.

That's not me saying quantum computing is fake. Shor's Algorithm, which can break RSA encryption, is mathematically proven to work on a quantum computer. Grover's Algorithm gives a real boost in speed for search problems. These aren't hypothetical, but Shor's needs thousands of error-corrected qubits to break real-world encryption keys. We're not there. We're years away, maybe more.

What frustrates me is that the actual progress is interesting enough without the hype. People are solving real problems in error correction, in qubit design, in the algorithms themselves. The gap between "a quantum computer exists" and "a quantum computer threatens global security" is enormous, and crossing it requires engineering breakthroughs that aren't guaranteed. The theory is solid, and some early applications in chemistry simulation and optimisation look really promising.

Next time you see a headline about quantum computing, ask what problem it solved, how many qubits it used, and whether those qubits were error-corrected.

A few months ago, I remember getting an email saying my application to the CCIR symposium had been accepted. I remember reading it twice out of excitement and doubt that I didn’t get in. They pick presenters based on how rigorous their research is, so getting in already felt like a win.

My paper is called “Photon Trajectories in the Vicinity of Black Holes”, which is about how photons bend and behave around an ideal black hole(symmetrical and non-rotating). I had spent months on it, coding and running simulations on MATLAB, and getting feedback from my mentor. By the time I landed in the UK, I knew all the material. What I did not know was how to present it to a room full of people and a Nobel laureate and not make mistakes.

My presentation was about presenting the methods, results, and conclusion of my paper. I explained the variable launch angles of photons and photons’ behaviour around black holes of different masses and radii.

I had spent 2 weeks or so on the actual presentation, and I was pretty well versed in what to say, but I wouldn’t say I was confident. Just before the presentation, while I was preparing, I got that feeling of anxiety that you sometimes get in your stomach. Around me, there were students from all around the world, and I remember thinking they were also as nervous as I was, which made me feel a little better somehow.

I sat in for a few of the presentations to see what I was dealing with, and it did not help. Everyone looked very intimidating with their questions. However, when I actually started my presentation, the nerves didn’t disappear, but it became a lot easier. I fell into flow state. I kept telling myself I knew the material, and it was true. I went through the methods and results, and people were following and nodding, and I felt like I belonged there for the first time.

Then came Q&A.

Someone from the audience asked a question about the programming side of my simulations, and I fumbled. The question was “What step-size control or stopping criteria did you use to distinguish between photons that are captured and those that scatter to infinity?"(what values did I use to distinguish captured and non captured photons) and I gave some vague answer rather than a confident response, and I sat with that feeling for the rest of the session, thinking about how I could’ve answered it differently.

After all the presentations, there was a formal dinner with various presenters, some professors and Dr Thomas R. Cech, who won the Nobel Prize in Chemistry for his work on RNA. He did seem a little intimidating at first, but once we actually started talking, he was easy to talk to, curious about what everyone was working on, and seemed very approachable.

He gave a talk that night about the research that led to his Nobel Prize, walking us through how the discovery came together and what the process behind it actually looked like. It was the first time someone wasn’t just talking about the facts but was also giving a glimpse of how real scientific breakthroughs happen. Everyone got handed a free copy of his book, which is on my shelf as a reminder.

I don’t think the question actually ruined my presentation, though. If anything, it taught me something a perfect Q&A doesn’t have: you can know your research and still get asked something you didn’t prepare for, and that’s just what happens when you put your work in front of people smart enough to understand.