Coding drops quantum computing error rate by order of magnitude

  Last updated April 9, 2019 at 5:42 pm

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Australian breakthrough brings workable quantum computers a big step closer.


quantum computing

Quantum computing holds great promise, but its fundamental process is delicate and prone to error. Credit: Alfred Pasieka/Science Photo Library/Getty Images


Errors in quantum computing have limited the potential of the emerging technology. Now, however, researchers at University of Sydney have demonstrated a new code to catch these bugs.


The promised power of quantum computing lies in the fundamental nature of quantum systems that exist as a mix, or superposition, of all possible states.


A traditional computer processes a series of “bits” that can be either 1 or 0 (or, on or off). The quantum equivalent, called a “qubit”, can exist as both 1 and 0 simultaneously, and can be “solved” together.


One outcome of this is an exponential growth in computing power. A traditional computer central processing unit is built on 64-bit architecture. The equivalent-size quantum unit would be capable of representing 18 million trillion states, or calculations, all at the same time.


The challenge with realising the exponential growth in qubit-powered computing is that the quantum states are fragile and prone to collapsing or producing errors when exposed to the electrical ‘noise’ from the world around them. If these bugs could be caught by software it would make the underlying hardware much more useful for calculations.


“This is really the first time that the promised benefit for quantum logic gates from theory has been realised in an actual quantum machine,” says Robin Harper, lead author of a new paper published in the journal, Physical Review Letters.


Reducing quantum computing errors


Harper and his colleague Steven Flammia implemented their code on one of tech giant IBM’s quantum computers, made available through the corporation’s IBM Q initiative. The result was a reduction in the error rate by an order of magnitude.


The test was performed on quantum logic gates, the building blocks of any quantum computer, and the equivalent of classical logic gates.


“Current devices tend to be too small, with limited interconnectivity between qubits and are too ‘noisy’ to allow meaningful computations,” Harper says.


“However, they are sufficient to act as test beds for proof of principle concepts, such as detecting and potentially correcting errors using quantum codes.”


Everyday devices have electronics which can operate for decades without error, but a quantum system can experience an error just fractions of a second after booting up.


Improving that length of time is a critical step in the quest to scale up from simple logic gates to larger computing systems.


The team’s code was able to drop error rates on IBM’s systems from 5.8% to 0.60%.


“One way to look at this is through the concept of entropy,” explains Flammia.


“All systems tend to disorder. In conventional computers, systems are refreshed easily, effectively dumping the entropy out of the system, allowing ordered computation.


“In quantum systems, effective reset methods to combat entropy are much harder to engineer. The codes we use are one way to dump this entropy from the system.”


Companies such as IBM, Google, Rigetti and IonQ have started or are about to start allowing quantum researchers to test their theoretical approaches on these small, noisy machines.


“These experiments are the first confirmation that the theoretical ability to detect errors in the operation of logical gates using quantum codes is advantageous in present-day devices, a significant step towards the goal of building large-scale quantum computers,” Harper says.


Related


Two-qubit chip draws quantum computing closer


World’s first complete design of a silicon quantum computer chip


Precision atom qubits achieve major quantum computing milestone




About the Author

Alan Duffy
Associate Professor Alan Duffy is an astronomer and physicist at Swinburne University of Technology, Melbourne. He's also lead scientist for Australia's Science Channel. You can find him on Twitter @astroduff.

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