What good is a fast computer if you can't trust it? Thanks to half a century of research on getting computers to do their job correctly even in the presence of mechanical errors, our modern machines tend to be pretty reliable. Unfortunately, the laws of quantum mechanics render all that research useless for quantum computers, the sheer complexity of which leaves them prone to errors. Now, we finally have the first demonstration of a quantum program that can detect data corruption. Two research groups – one from the University of Maryland and Georgia Tech and the other from IBM – have demonstrated the same quantum error-detecting program, albeit implemented with different hardware.
Useful quantum computers are one step closer, thanks to the latest demonstration of a technique designed to stop them making mistakes. Quantum computers store information as quantum bits, or qubits. Unlike binary bits, which store a 0 or a 1, qubits can hold a mixture of both states at the same time, boosting their computing potential for certain types of problems. But qubits are fragile – their quantum nature means they can't hold data for long before errors creep in. So researchers wanting to build large-scale computers invented quantum error correction (QEC).
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.
January 17, 2017 --The dream of useful quantum computing may have just come one step closer. Australian researchers are combining two of the hottest topics in science: quantum computing and machine learning. Specifically, they've succeeded in training an algorithm to predict the evolving state of a simple quantum computer. Such an understanding allows real time stabilization of the system, much as tightrope walker uses a pole for balance, according to a paper published Monday in Nature Communications. That would be a big deal for everyone – from Silicon Valley to Washington, D.C.
In 2016, the computer program AlphaGo won four out of five games of Go against the world's best human player. Given that a game of Go has more combinations of moves than there are estimated to be atoms in the universe, this required more than just sheer processing power. Rather, AlphaGo used artificial neural networks, which can recognize visual patterns and are even capable of learning. Unlike a human, the program was able to practise hundreds of thousands of games in a short time, eventually surpassing the best human player. Now, the Erlangen-based researchers are using neural networks of this kind to develop error-correction learning for a quantum computer.