As the internet continues to expand with almost unimaginable amounts of data, a Google backed study has shown how search algorithms can keep up in the future – with the use of quantum computers.
With the switch to IPv6 this week the number of IP addresses which can be assigned now reaches into the trillions, highlighting the huge amount of information which is coming online at a rapid rate.
This means that search engines such as Google will increasingly have mind-bogglingly large amounts of information to process when serving up search results, a mammoth computational task.
We have all come to expect this to happen instantly, with relevant search results ranked in order of importance. As the search gets more complicated it also threatens to slow this down.
A team at the University of South Carolina says that to meet such high demands using Google’s famous PageRank system, it may be necessary to use quantum computing to give the algorithm a boost.
Quantum computing, using quantum bits of information which unlike traditional computing bits can exist in states of ‘one’, ‘zero’ or ‘both’, offers access to exponentially faster processing.
One of the commonly discussed potential applications could be unhackable encryption coding, and plenty of labs and tech firms around the world are developing quantum computing.
According to the researchers, such lightning fast computational speeds could also benefit search algorithms like PageRank, and the team has developed a simulation to discover whether this would work.
The researchers, funded in part by a Google faculty research award, created a simulation of a few thousand web pages that find out if, in principle, the PageRank algorithm would return the most important web pages even quicker.
According to the results of the simulation, which looked at the way quantum computing would deal with a web of thousands of pages, the results showed that PageRank would be vastly improved. The rate at which this would improve would speed up as more pages were ranked.