Internet search engines provide us with search results in the form of websites containing required information and listed in the order of relevance. Search engines employ a set of mathematical calculations known as page ranking algorithm to determine the relevance of web pages in respect to the search criteria.
Current engines provide instantaneous results. As the internet continues to expand, the time and resources required to perform the algorithm increases. In order to improve the speed of search engines in the face of persevering internet expansion, scientists at the University of South California have demonstrated the use of quantum computing for this purpose.
Conventional computers employ data in the form of binary digits or bits with the bits representing one of two states, 0 or 1 at any given time. Quantum computers however employ quantum bits or qubits which exhibit a property called superposition wherein they represent 1 and 0 simultaneously. This property enables quantum computers to perform calculations with improved speed.
Research carried out by USC’s postdoctoral researcher Silvano Garnerone, Paolo Zanardi and Daniel Lidar attempts to demonstrate how quantum computing can be used to perform Google’s algorithmic calculations faster. Existing quantum computers are not large enough to handle Google’s calculations for the entire web. The researchers simulated the web with a few thousand pages. The results of the simulation showed that quantum computers can not only improve speed when the number of pages needed to be ranked increases, but can also produce a yes-or-no answer to show whether the page rank of a web page needs to be updated.
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