Humanity continues to generate ever-larger sets of data, from space exploration to gene mapping. Artificial intelligence systems can help dealing with this influx of new information.
However, even the most powerful supercomputers existing today are becoming inefficient in processing the big data. Quantum computers are becoming a trendy new approach to solving this issue.
A team of researchers at the University of Southern California, the University of Waterloo and MIT are working on a project to develop quantum computers for processing big amount of data. Their theoretical proposal is described in an article published in the journal Nature Communications.
The paper's lead author, Seth Lloyd, explains in the report that the key to the new method consists in algebraic topology. According to Lloyd, this will reduce the impact of distortions arising when someone collects data about the real world.
Basic features of the data in a topological description are considered the same no matter how much they are distorted, compressed or stretched. These fundamental topological attributes can help reconstruct the underlying patterns in the real world represented by the influx of data. The topological approach to looking for connections works no matter what kind of data set is being analyzed.
This approach would be too demanding if using conventional computers, being very expensive computationally. However, the new quantum computing approach could greatly speed up processing data and calculations.
There are many important big data sets where the quantum topological calculations could be implementing. For instance, the topological analysis can be applied to data sets generated by functional MRI or electro-encephalography in order to understand the complex interconnections in the brain.
The same approach could be applied to social networks, to the world's economy, or many other systems that involves long range transport of information or goods. According to the website Phys.org, citing Professor Lloyd, quantum computer devices could be developed in the next few years.
