Inside the Race to Revolutionize Quantum Computing

This grid of arrows is actually a theoretical physics problem about magnetism that would take your laptop years to figure out, but a quantum computer like this could solve it. Before this video ends, it has the largest quantum processors in the world. Tech giants like IBM, Google, and Microsoft are racing to invent the next iteration of quantum computing. Let’s say you want to build a better alloy for a car, or a better battery for an electric vehicle, or create new binding molecules for a target drug. So that will benefit from quantum computers. But getting there is easier said than done. If I were to rank the level of difficulty of building quantum computers, I would give it a 10 out of 10. Here’s how quantum computing works, why experts say it’ll revolutionize business, and the technical challenges ahead. To learn how difficult building quantum computers really is, we visited IBM Quantum Computing Research Lab. I’m standing in front of IBM Quantum System 2, which is our latest quantum system and the evolution of a system that’s been designed for modularity and for scale. Building bigger quantum computers like these could save companies millions of dollars. Here’s how. Say a company has a global supply chain, a process that involves thousands of ships, changing weather patterns, precise inventories, and thousands of other inputs. To optimize its roots, a quantum computer could game out each possible combination of every conceivable factor, a number that exceeds the number of atoms in the universe. Researchers also think that in as little as 10 years, they will be able to develop new drugs as much as 100 times faster than they’re made now. The biggest pharmaceutical companies have already begun preparing. In January, Pfizer announced a collaboration with biotech firm Jarrow that debuted in AI that could use a quantum computer to generate new chemical structures for potential drugs, which has never been done before. At IB, Ms. Lab researchers are already experimenting with similar problems. They do it using these quantum computer chips, which hold bits of information called, well, bits. Regular computers also have bits that can be one or zero. But quantum bits, called qubits, can be both one and zero and the infinite combinations of the two simultaneously. Another way to represent it is with that sphere. And you can imagine if you have a little arrow that was from the center of the sphere to the North Pole, you would call it a zero because in the South Pole you would call it a one. But you could put that arrow anywhere you want this sphere, let’s say in the equator. And now in the equator it will be equal part zero and one. So that flexibility of representing combinations of states, it’s an important element of quantum computers. But that’s not all, because that’s just about 1 qubit. The real power in quantum computers comes from a phenomena called entanglement. Entanglement is when qubits share a quantum state and so connect and work together. Entanglement is what will allow quantum computers to work faster and better than classical computers, which IBM proved was possible with this paper in June 2023 for the first time. Remember this physics problem? They used one like it to pit a quantum computer and a classical supercomputer against one another. And the quantum computer performs better. But creating one qubit is hard enough. Getting thousands to work together is incredibly difficult. That’s what Jerry Chow is working on in this experimental lab. What may be the industry’s biggest hurdle is keeping the qubits stable. The problem with these qubits is that those states, zero and one, they’re very fragile in the quantum world. Almost any kind of stray electromagnetic fields will try and affect the quality of these qubit states. So things like heat, noise, and magnetic fields can affect that quality, causing a qubit to drop its information that can throw off the large complex calculations being processed. So the balance of building a good quantum computer is this aspect of shielding and isolating my system, but still allowing information to go in and out so that I can compute usefully. And the best way to strike that balance is to keep the computers 400° below 0. That’s colder than the vacuum of space. They do it using helium. The sound that you hear in the background is actually a compressor that’s working to pump to actually help it cool down. The temperature is also the reason why they’re golden. Each computer is coated in gold to reflect light, preventing it from absorbing heat. What’s really important within these systems is how well we can isolate any kind of stray light or stray radiation in order to prevent thermal radiation from warmer stages from getting down to the lower stages. Now we have quantum computers that have over 100 qubits and that can run using these error mitigation techniques that you can now start doing calculations that you couldn’t do efficiently classically. Dario and the IBM team see quantum entering mainstream industries in the next 6 to 10 years, when quantum computers make fewer errors and so can be more useful. That’s when experts suggest that companies will begin to integrate quantum computing into their businesses. Why do I have so much confidence on on what’s happening in quantum computing? I remember witnessing this in AI over a decade ago and progressively growing it, and we’re starting to see this in quantum. Like AI, quantum computing is growing steadily, solving problems like these math questions faster and better. But researchers highlight a long road ahead before these computers go mainstream.