Quantum Computing Starts Yielding Real Applications
London, UK - 15th December 2009, 21:35 GMT
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Google has recently announced that it is successfully investigating the use of Quantum Algorithms to run its next generation of faster applications. So far, Google search services run in warehouses filled with conventional computers. As pointed out by ATCA in our briefings over the last few years, Quantum Computing and Quantum Algorithms have the potential to make search problems much easier to solve –- so it is no surprise that Google finds it extremely important to get involved in this emerging area of Quantum Technology with the potential to bring about asymmetric disruptive change, garnering a massive first mover competitive advantage over its rivals.
Quantum Computers point to much faster processing, by exploiting the principle of quantum superposition: that a particle such as an ion, electron or photon can be in two different states at the same time. While each basic "binary digit" or "bit" of data in a conventional computer can be either a 1 or a 0 at any given time, a Qubit can be both at once! Classical computers use what is known as a von Neumann architecture, in which data is fetched from memory and processed according to rules defined in a program to generate results that are then stored step by step. It is essentially a sequential process, though multiple versions of it can run in parallel to speed things up!
Way back in 2007, a Canadian company called D-Wave claimed it demonstrated a Quantum Computer, although the jury is still out because no other research labs in the world -- despite their large budgets and talented scientists -- have been able to produce a fully functional Quantum Computer yet. D-Wave developed an on-chip array of Quantum bits – or Qubits – encoded in magnetically coupled superconducting loops. D-Wave’s investors include Goldman Sachs and Draper Fisher Jurvetson.
Hartmut Neven, Head of Google's Image Recognition team, has revealed that the firm has been quietly developing a Quantum Algorithm application over the last three years that can identify particular objects in a database of stills or video. The team adapted Quantum adiabatic algorithms, discovered by Edward Farhi and collaborators at MIT, for the D-Wave chip so that it could learn to recognise cars in photos, and reported at the Neural Information Processing Systems summit in Vancouver, Canada, recently that they have succeeded. Using 20,000 photographs of street scenes, half of which contained cars and half of which didn't, they trained the algorithm to recognise what cars look like by hand-labelling all the cars with boxes drawn around them. After that training, the quantum algorithm was set loose on a second set of 20,000 photos, again with half containing cars. It sorted the images with cars from those without faster than an algorithm on a conventional computer could, in fact, faster than anything running in a Google data centre at present. The team appears to have perfected a simulated annealing system that is well suited to searching images for well-defined objects. Normally this costs too much to have a computer do it in real time. However if Google and D-Wave can get it working then common searches can be pre-calculated and the results stored in databases for fast retrieval!
There has been some dispute over whether D-Wave's Chimera chip is actually a Quantum Computer. Hartmut Neven at Google acknowledges, "It is not easy to demonstrate that a multi-Qubit system such as the D-Wave chip exhibits the desired quantum behaviour, and physicists are still in the process of characterising it." However, while questions remain over the exact capabilities of D-Wave's hardware, future developments are likely to centre on different Quantum Computing hardware. For example, it is widely accepted that trapped ions are the most successful implementation of Quantum Technology.
The mi2g Intelligence Unit and the ATCA Research and Analysis Wing (RAW) expect more and more government agencies and companies around the world to pursue research in Quantum Computing and Quantum Algorithms in the coming few years due to their vast potential not only in search applications but also for a multiplicity of other complex problem solving capabilities.
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