Surface codes are favorable in this respect: they can tolerate the highest error rate of all fault-tolerant error-correcting schemes. Below this threshold value, increasing the code size would decrease error rates of the logical qubit to arbitrarily low values. If the error rate of a quantum computer is below a certain threshold value, called the fault-tolerant threshold, then the code will be able to deal not only with random qubit errors induced by the environment but also with imperfect operations of the computer and of the error-correcting circuits themselves. Doing so will require the error rates of the operations to be significantly lower than they currently are, and it may require using a number of qubits of an order of tens of thousands.ĭespite the difficulty in achieving break even, a surface code is still an attractive approach because of its long-term possibility of enabling a fully fault-tolerant quantum computer. This condition has already been achieved in quantum error-correction schemes using a class of codes called bosonic codes but not yet in schemes involving a surface code. One of the first steps in demonstrating a successful error-correcting code is achieving “break even,” a condition where the lifetime of the logical qubit is at least as long as that of the best uncorrected physical qubit. A surface code accomplishes this correction by using a 2D array of qubits. One can correct for these two types of errors simultaneously by combining bit-flip and phase-flip error-correcting codes. Quantum states also suffer phase-flip errors, which affect the superposition of states by converting a | 0 ⟩ + | 1 ⟩ qubit state to | 0 ⟩ − | 1 ⟩ and vice versa. The number of physical qubits used to encode a logical qubit is called the distance of the code, and a code gets exponentially better at suppressing logical errors as the distance increases (at the cost of increased hardware complexity). Then if fewer than half of the physical qubits suffer one of these bit-flip errors, the code can catch and correct mistakes before they corrupt the logical data. For example, in a simple “repetition code,” to correct for noise that erroneously flips a bit value from | 0 ⟩ to | 1 ⟩ or vice versa, one can take a 1D chain of multiple qubits and label a logical state | 0 ⟩ or | 1 ⟩ if the value of all the qubits have a bit value equal to 0 or 1 simultaneously. Importantly, these comparison measurements do not reveal the actual value of any of the qubits-they only reveal which qubit, if any, has suffered an error. The schemes involve redundantly encoding quantum information of a single “logical” qubit in a many-body entangled state of multiple “physical” qubits so that comparisons between these qubits reveal if one or more of them has changed. These results bring us a step closer toward realizing a practical quantum computer.Įrror correction requires monitoring the quantum bits, or qubits-the basic units of binary data used for quantum computing-which can simultaneously be in any superposition of | 0 ⟩ and | 1 ⟩ states. Now, two groups, led by Jian-Wei Pan at the University of Science and Technology of China in Hefei and Andreas Wallraff at the Swiss Federal Institute of Technology (ETH) in Zurich, have achieved the first-ever demonstration of error correction with surface codes. But until now, demonstrations with the surface code have only detected errors, not corrected them. These codes are promising because they are experimentally straightforward to implement and because, under certain conditions, they can tolerate relatively large error rates. A promising approach to QEC involves surface codes, where the connections between the elements of the quantum computer can be visualized as forming a 2D checkerboard pattern. QEC provides a way to fight noise by detecting and correcting the errors in calculations that the noise causes. ×įor quantum computers to reach their full potential, the need for quantum error correction (QEC) is inevitable. The gray disks represent the qubits used to store logical information, while the green and red disks are two different types of “ancilla” qubits used to perform operations that allowed the researchers to detect and correct errors. APS/Carin Cain Figure 1: Artistic rendition of the 17-qubit surface code used by Jian-Wei Pan and colleagues to demonstrate surface error correction.
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