Q&A: Quantum computing

Physics student Brian Vlastakis GRD ’15 works in the lab of Yale applied physics professor Robert Schoelkopf, associate director of the Yale Institute for Nanoscience and Quantum Engineering. Vlastakis sat down with the News on Monday to discuss quantum computing.

Q: Can you briefly summarize the importance of quantum computing?

A: The idea for our field of quantum information and quantum computation is trying to manipulate quantum mechanics in order to perform very complicated computation algorithms. A classical computer is made up of very many digital bits that have a 0 or a 1 state. In a quantum computer, the bit is now acting quantum mechanically. A quantum mechanical bit — we call it a qubit — is forced to obey the laws of quantum mechanics, in the sense that it’s not just in one place at once. It can be both 0 and 1 at the same time, and the idea here is that you’re performing multiple calculations at once. A nice analogy that people like to use for quantum computers is that you’re kind of essentially doing the ultimate “parallel processing.” The quantum processor is sort of like having many classical processors all performing a calculation in parallel, doing separate smaller calculations and then putting them together.

Q: How does the lab that you’re working in contribute to quantum information?

A: We’re trying to build quantum computers, but there are many ways you can implement them. One way, what we do, is called superconducting qubits.

In quantum information, you want to be able to create quantum bits, which are essentially a system with ground-state energy, representing 0, and some excited-state energy level, representing 1. You want to be able to address the transition between these states. We’re trying to create these “two-level systems,” which is just another word for a quantum bit, and we’re creating them with superconducting circuits.

There are other crazy ways to make quantum bits, but what’s really nice about the way that we’re making these quantum bits is that we’re able to print them out on a circuit board. This is actually the same technique that big companies use to make regular computers. This makes the field that we’re in very exciting, because a lot of these companies say that if you guys can figure out how to control them and understand them, then we can make them.

Now, we’re slowly trying to put all these components together in order to perform very rudimentary quantum algorithms. What’s exciting is that these really have a great potential to scale up and become powerful quantum computers.

Q: How do you hope to expand to scaling up?

A: When you have only a few quantum bits, it’s okay if they mess up every once in a while, because the probability of only one messing up is pretty slim. But if you had a million of those bits, there’s a very good chance that one of them will mess up when you’re doing your algorithm. This is actually a very difficult thing for quantum algorithms, because quantum bits are extremely sensitive to errors that might occur to them. Unfortunately for these quantum bits, any fluctuation between the 0 and 1 states actually corresponds to a completely different quantum state.

So, we need to know precisely what state our bit is actually in. What this requires is something called quantum error correction. This is what almost everyone in quantum computation is striving to achieve. Being able to do quantum error correction will be the biggest stepping stone is scaling up to these very large scales of quantum bits. We’ll forever be stuck in these few qubit systems until we can sort out quantum error correction. So the big five-year goal in the field is to try to be able to perform rudimentary quantum error correction schemes.

Q: How will the work of your lab contribute to the quantum error correction?

A: What’s really great about using superconducting qubits is that they are circuits, so if we want to have one qubit interact with another qubit, we can just design a system where’s there’s just a wire that attaches them. This has a lot of really big advantages if we want to implement a type of quantum error correction. We can design a system where different qubits will only interact with other certain qubits. That’s one of the things we’re actively exploring right now.

The thing that I’m actually looking into is seeing if we can go beyond just using a quantum bit for these sorts of error correction schemes and regular quantum algorithms. So, something that I’m looking into is using a resonator. In quantum mechanics you have these two-level systems, and then what you call “harmonic oscillators” — or “resonators.” I’m trying to look if we can use cavity resonators as a resource for some sort of quantum memory.

There are many ways you can think of a cavity. Typically when we say “cavity” you think of photons, so a cavity resonator is just a box that’s trapping photons, and they’re forced to bounce back and forth inside this cavity. A typical one that most people think of is just two mirrors facing each other — if you send in light, you just get light that’s stuck bouncing back and forth. We can essentially create the same thing with these superconducting circuits.

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