The Geforce chip is made of copper instead of aluminium, which means it can run faster - Spencer Kelly, BBC Click Online
RESEARCHERS have reported a technological breakthrough that is set to speed the arrival of real-world quantum devices that will be orders of magnitude more powerful than today's best supercomputers.
A team at IBM Research reported that they have achieved major advances towards creating real-world quantum computing devices that exploit the underlying quantum mechanical behavior of matter.
"The quantum computing work we are doing shows it is no longer just a brute force physics experiment. It's time to start creating systems based on this science that will take computing to a new frontier," said IBM scientist Matthias Steffen, manager of the IBM Research team that's focused on developing quantum computing to a point where it can be applied to real-world problems.
The scientists described how they have established new techniques for reducing errors in elementary computations and retaining the integrity of quantum mechanical properties in quantum bits (qubits) - the basic units that carry information within quantum computing. They explained they have chosen to employ superconducting qubits, which use established microfabrication techniques developed for silicon technology, providing the potential to one day scale up to and manufacture thousands or millions of qubits.
The special properties of qubits have the potential to allow quantum computers to work on millions of computations at once - a single 250-qubit state contains more bits of information than there are atoms in the universe. The most basic piece of information that a typical computer understands is a bit. Much like a light that can be switched on or off, a bit can have only one of two values: "1" or "0". For qubits, they can hold a value of "1" or "0" as well as both values at the same time. Described as superposition, this is what allows quantum computers to perform millions of calculations at once.
The IBM boffins reported that one of the great challenges for scientists seeking to harness the power of quantum computing is controlling or removing quantum decoherence - the creation of errors in calculations caused by interference from factors such as heat, electromagnetic radiation, and materials defects. To deal with this problem, scientists have been experimenting for years to discover ways of reducing the number of errors and of lengthening the time periods over which the qubits retain their quantum mechanical properties. When this time is sufficiently long, error correction schemes become effective making it possible to perform long and complex calculations.
To address this issue IBM is focusing on using superconducting qubits that will allow a more facile transition to scale up and manufacturing.
IBM has recently been experimenting with a unique "three dimensional" superconducting qubit (3D qubit), an approach that was initiated at Yale University. Among the results, the IBM team has used a 3D qubit to extend the amount of time that the qubits retain their quantum states up to 100 microseconds - an improvement of 2 to 4 times upon previously reported records. This value reaches just past the minimum threshold to enable effective error correction schemes and suggests that scientists can begin to focus on broader engineering aspects for scalability.
In separate experiments, the group at IBM also demonstrated a more traditional "two-dimensional" qubit device and implemented a two-qubit logic operation - a controlled-NOT (CNOT) operation. Their operation showed a 95 per cent success rate. These numbers are on the cusp of effective error correction schemes and greatly facilitate future multi-qubit experiments.
Out of the labs and in the real world, quantum computers are likely to have widespread implications foremost for the field of data encryption where quantum computers could factor very large numbers like those used to decode and encode sensitive information. Other potential applications for quantum computing might include searching databases of unstructured information, performing a range of optimisation tasks and solving previously unsolvable mathematical problems. µ
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