The measured characteristics of our device agree well with a numerical model. We find a low logical error probability of 3% per cycle when rejecting experimental runs in which leakage is detected. Repeatedly executing the cycle, we measure and decode both bit-flip and phase-flip error syndromes using a minimum-weight perfect-matching algorithm in an error-model-free approach and apply corrections in post-processing.

In an error-correction cycle taking only 1.1 μs, we demonstrate the preservation of four cardinal states of the logical qubit. Using 17 physical qubits in a superconducting circuit, we encode quantum information in a distance-three logical qubit, building on recent distance-two error-detection experiments 7, 8, 9. Here we demonstrate quantum error correction using the surface code, which is known for its exceptionally high tolerance to errors 3, 4, 5, 6. For fault-tolerant operation, quantum computers must correct errors occurring owing to unavoidable decoherence and limited control accuracy 2. Adding existing qubits to a logical qubit doesn't make it more robust it makes it more likely to have so many errors at once that they can't be corrected.Quantum computers hold the promise of solving computational problems that are intractable using conventional methods 1. The second issue is that the error rates of the hardware qubits are too high for any of this to work. Running a robust error correction scheme on the processors with the highest qubit counts would leave us looking at using fewer than 10 qubits for a calculation. One is that we don't have hardware qubits to spare.

The more hardware qubits you dedicate to a logical qubit, the more robust it should be. And measuring its neighbors will reveal the error and allow a bit of quantum manipulation to fix it. Now, if one of the hardware qubits that's part of the logical qubit has an error, the fact that it's only holding a fraction of the information of the logical qubit means that the quantum state isn't wrecked. These can be measured to infer the state of each qubit that's part of the logical qubit. (In terms of computational logic, all these hardware qubits can be addressed as a single unit, hence 'logical qubit.') Error correction is enabled by additional qubits neighboring each member of the logical qubit. This creation process involves distributing a quantum state among a set of connected qubits. AdvertisementĬreating an error-corrected logical qubit is generally accepted as the solution to this problem. So, we now have quantum computers with more than 400 qubits, but trying to do any calculation that required all 400 would fail. As a result, throwing more qubits at a problem makes it more likely you'll encounter an error before a calculation can complete. That is, assuming all the qubits behave correctly. By the time you have access to several hundred, it's thought that you can perform calculations that would be difficult to impossible to do on traditional computer hardware. The more qubits you have, the more capable the machine is.

The functional unit of a quantum processor is a qubit, which is anything-an atom, an electron, a hunk of superconducting electronics-that can be used to store and manipulate a quantum state. In this new iteration, adding more qubits and getting the error rate to go down is possible. In earlier generations of processors, qubits were error-prone enough that adding more of them to an error-correction scheme caused problems that were larger than the gain in corrections. Instead, the signs of progress are a bit more subtle. And getting quantum error correction isn't really the news-they'd managed to get it to work a couple of years ago. The iteration on Sycamore isn't dramatic-it's the same number of qubits, just with better performance. Today, Google announced a demonstration of quantum error correction on its next generation of quantum processors, Sycamore.

Google quantum error correction