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AQUA - White Paper

# AQUA - White Paper - [email protected] white paper December 9 2008...

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AQUA @home white paper December 9, 2008 Dr. Geordie Rose Founder and Chief Technology Officer D-Wave Systems Inc. [email protected]

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ABOUT D-WAVE D-Wave is developing a new class of high- performance computing system designed to solve complex optimization problems, with an initial emphasis on machine learning applications. D-Wave systems are architected around an innovative processor that uses a computational model known as adiabatic quantum computing (AQC). These processors exploit quantum effects to solve optimization problems in a new way. They are fabricated using superconducting metals instead of semiconductors and are operated at ultra-low temperatures in a magnetic vacuum. www.dwavesys.com © Copyright 2008 | D-Wave Systems Inc. | www.dwavesys.com
INTRODUCTION An algorithm is a prescription for solving a problem. 1 An example is provided in the Wikipedia entry on algorithms, where the problem to be solved is getting a broken lamp to work (see Figure 1). In this case, a sequence of steps is followed, with the problem-solving tactics at each step depicted in a flowchart. Usually it is straightforward to evaluate how well a proposed algorithm works. One way to do this is by counting how many steps it takes to solve a problem of a given size. Some algorithms are better than others. In the lamp example in Figure 1, a perfectly valid algorithm could require a trip to Siberia between checking that the lamp was plugged in and checking if the bulb was burned out. The addition of the Siberia leg doesn’t affect the outcome of the algorithm—the lamp still gets fixed. This modified lamp fixing algorithm would still generally be viewed as inferior to the original. Sometimes a newly discovered prescription for solving a problem is clearly superior to all the others that have preceded it. When this happens, the incumbent approaches are often abandoned and everyone who shares the problem in question gets an immediate and sometimes spectacular performance boost. 2 In the lamp scenario, imagine everyone used the “visit Siberia” version, until some brilliant computer scientist pointed out you could omit this step and still get your lamp fixed. Most would immediately switch to the better approach. Sometimes it is very difficult to tell whether a particular algorithm could be made better. Over the past two decades a lot of progress has been made in understanding one type of limitation to how good algorithms can be. It turns out that the laws of physics set limits on how efficiently problems can be solved. 1 An interesting article about algorithms: http://www.crmbuyer.com/story/33488.html 2 A famous example of this involves algorithms for factoring; see http://dwave.wordpress.com/2007/08/27/algorithms-vs- hardware-the-throwdown/ for references.

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