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Chinese Physicists Show Quantum Computers' Machine Learning Potential to Handle Big Data

| Apr 04, 2015 07:31 AM EDT

Lu Chaoyang, one of the Chinese physicists studying the potential of quantum computers in machine learning

A team of Chinese physicists at the University of Science and Technology of China has recently demonstrated that quantum computers can replace conventional computers to handle big data through an experiment that showed that machine learning is possible using a photonic quantum processor.

According to a report by technologynewschina.com, the team of Chinese scientists published their findings in a paper on the scientific journal "Physical Review Letters," where they discussed and proved the potential power and correctness of quantum machine learning.

In technical terms, machine learning is a branch of artificial intelligence that refers to the study of algorithms that empower a computer and enables it to learn and improve its performance based on existing data.

Machine learning is now commonly used in fields such as robotics, computer science, medical diagnosis and financial analysis. The algorithms of machine learning are also used to design spam filters.

The scientists, however, said that large amounts of electronic data created and produced in the past years have presented some challenges to classical computing.

"It is estimated that every year it [electronic data] grows exponentially by 40 percent," Lu Chaoyang, one of the Chinese physicists, was quoted as saying.

"If it is to continue, then in about 2020, the chip size will shrink down to the atomic level where quantum mechanics rule. Thus, the speed-up of classical computation power faces a major challenge. Today, we may still be good running machine learning and other computational tasks with our good old classical computers, but we might need to think of other ways in the long run."

In 2013, Seth Lloyd, a Massachusetts Institute of Technology professor and his fellows have published a paper which presented the idea of quantum algorithms for machine learning, showing its exponential speed as an alternative way over traditional algorithms.

According to Seth, this speed can be achieved through the quantum state of superposition in which a quantum bit is represented by 1 and 0 at the same time, unlike in classical computing where a bit of data has a single value, either 1 or 0.

Lu said that through the quantum state of superposition, a single quantum object can perform a calculation on two numbers simultaneously, two quantum objects can handle 4 numbers, 3 objects for 8 and 20 objects for over one million numbers.

The Chinese scientist added that with such speed, a computing task that will take years to complete in a classical computer will only take a quantum computer about one second.

"The ability . . . on quantum computers may provide a useful quantum toolkit for dealing with the 'big data'," the Chinese scientists said in their paper.

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