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MIT boffin: Big data won't compute? Try these handy quantum algorithms

All you need is that 300 qubit computer in your back drawer

Big Data? Check! Machine Learning? Check! Quantum computers? Check! Seth Lloyd, the self-dubbed "Quantum Mechanic", has ticked every box with a new (entirely theoretical) paper announcing a potential solution to problems unfeasible even before "the most powerful modern supercomputers".

The paper, titled "Quantum algorithms for topological and geometric analysis of data" was published in Nature Communications on Monday, proposes a theory as to how quantum computers may be used to solve the difficulties in big data analytics.

Written by Lloyd, who works at MIT, along with Silvano Garnerone of the University of Waterloo and Paolo Zanardi of the University of Southern California, the paper explains how algebraic topology could help to "reduce the impact of the inevitable distortions that arise every time someone collects data about the real world."

Topology is a branch of geometry which concentrates on the properties of space which are preserved despite any continuous deformation of that space.

The researcher quips that using the topological approach to looking for connections and holes "works whether it’s an actual physical hole, or the data represents a logical argument and there's a hole in the argument. This will find both kinds of holes."

This is far too difficult for conventional computers in all but the most mundane of situations, according to MIT.

Using conventional computers, that approach is too demanding for all but the simplest situations. Topological analysis "represents a crucial way of getting at the significant features of the data, but it’s computationally very expensive," according to Lloyd, who reckons his new quantum-based approach could "exponentially speed up such calculations."

Lloyd offers an example to illustrate that potential speedup: If you have a dataset with 300 points, a conventional approach to analyzing all the topological features in that system would require “a computer the size of the universe,” he says.

That is, it would take 2300 (two to the 300th power) processing units — approximately the number of all the particles in the universe. In other words, the problem is simply not solvable in that way.

The researchers' algorithm would be able to solve the same problem using a quantum computer of just 300 quantum bits. Such a device could be achieved in the next few years, at least according to Lloyd. ®

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