Google is on a mission to build an error-corrected quantum computer. To begin this ambitious journey, the tech giant has set up a Quantum AI Campus in Santa Barbara, California, housing Google's first quantum data center, quantum hardware research laboratories and quantum processor chip fabrication facilities. Google said their future challenges include building more efficient batteries, creating better fertilisers to increase crop yield, and developing medicines that can stop the next pandemic in its tracks. That is, the bonds and interactions among atoms behave probabilistically, with richer dynamics that exhaust the simple classical computing logic. Exactly why we need quantum computers to solve future challenges.
Google's researchers have successfully tested error correction methods with the company's Sycamore processor. Google's researchers have demonstrated that, subject to certain conditions, error correction works on the company's Sycamore quantum processor and can even scale exponentially, in what is yet another step towards building a fault-tolerant quantum computer. The breakthrough is likely to catch the attention of scientists working on quantum error correction, a field that is concerned not with qubit counts but rather with qubit quality. While increasing the number of qubits supported by quantum computers is often presented as the key factor in unlocking the unprecedented compute power of quantum technologies, equally as important is ensuring that those qubits behave in a way that allows for reliable, error-free results. This is the idea that underpins the concept of a fault-tolerant quantum computer, but quantum error correction is still in very early stages.
Google's new Quantum AI Campus in Santa Barbara, California, will employ hundreds of researchers, engineers and other staff. Google has begun building a new and larger quantum computing research center that will employ hundreds of people to design and build a broadly useful quantum computer by 2029. It's the latest sign that the competition to turn these radical new machines into practical tools is growing more intense as established players like IBM and Honeywell vie with quantum computing startups. The new Google Quantum AI campus is in Santa Barbara, California, where Google's first quantum computing lab already employs dozens of researchers and engineers, Google said at its annual I/O developer conference on Tuesday. A few initial researchers already are working there. One top job at Google's new quantum computing center is making the fundamental data processing elements, called qubits, more reliable, said Jeff Dean, senior vice president of Google Research and Health, who helped build some of Google's most important technologies like search, advertising and AI.
Google is leading the pack when it comes to quantum computing. The company is testing a 20-qubit processor – its most powerful quantum chip yet – and is on target to have a working 49-qubit chip by the end of this year. Qubits, or quantum bits, can be a mixture of 0 and 1 at the same time, making them potentially more powerful than classical bits. And if everything goes to plan, the 49-qubit chip will make Google the first to build a quantum computer capable of solving certain problems that are beyond the abilities of ordinary computers. Google set itself this ambitious goal, known as quantum supremacy, in a paper published last July.
After decades of research, quantum computers are approaching the scale at which they could outperform their "classical" counterparts on some problems. They will be truly practical, however, only when they implement quantum error correction, which combines many physical quantum bits, or qubits, into a logical qubit that preserves its quantum information even when its constituents are disrupted. Although this task once seemed impossible, theorists have developed multiple techniques for doing so, including "surface codes" that could be implemented in an integrated-circuit-like planar geometry. For ordinary binary data, errors can be corrected, for example, using the majority rule: A desired bit, whether 1 or 0, is first triplicated as 111 or 000. Later, even if one of the three bits has been corrupted, the other two "outvote" it and allow recovery of the original data.