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Quantum Computing

Scientists Working On Bringing Quantum Computer Properties to Classic Computers

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A group of Scientists from Linköping University have been able to demonstrate how a quantum computer works, and they were able to simulate the properties of it in a classical computer. 

“Our results should be highly significant in determining how to build quantum computer,” Professor Jan-Åke Larsson said. 

Sweden, Europe, and other parts of the world have been investing large resources and focusing research to create superfast powerful quantum computers. Within ten years, a Swedish quantum computer is expected to be built, and the EU has deemed quantum technology as one of its major projects. 

Currently, we have few useful algorithms that can be used for quantum computers. Even though that’s the case, this type of technology will be extremely important in simulations of biological, chemical, and physical systems. Many of these are too complex for the most powerful computers that we have now. In a computer, a bit can take the value of one or zero, but a quantum bit is able to take all values in between. This means that quantum computers don’t need to take so many operations for each calculation that is done. 

Professor Jan-Åke Larsson and his doctoral student Niklas Johansson, from the Division for Information Coding at the Department of Electrical Engineering,  Linköping University, have figured out much of why a quantum computer is more powerful than a classic one. They have also looked into what happens within a quantum computer. 

The results from the research has been published in the scientific journal Entropy.

“We have shown that the major difference is that quantum computers have two degrees of freedom for each bit. By simulating an additional degree of freedom in a classical computer, we can run some of the algorithms at the same speed as they would achieve in a quantum computer,” says Jan-Åke Larsson.

The team has created a simulation tool called Quantum Simulation Logic, or QSL. It allows them to simulate the operation of a quantum computer on a classical computer. The Quantum Simulation Logic has one specific property, and it is the only property, that a quantum computer has and a classical computer does not. That is one extra degree of freedom for each bit that is part of the calculation. 

“Thus, each bit has two degrees of freedom: it can be compared with a mechanical system in which each part has two degrees of freedom — position and speed. In this case, we deal with computation bits — which carry information about the result of the function, and phase bits — which carry information about the structure of the function,” Jan-Åke Larsson explains.

The QSL tool has been used by the team in order to study some of the quantum algorithms that are responsible for managing the structure of the function. Many of those algorithms are as fast in the simulations as they would be in a quantum computer. 

“The result shows that the higher speed in quantum computers comes from their ability to store, process and retrieve information in one additional information-carrying degree of freedom. This enables us to better understand how quantum computers work. Also, this knowledge should make it easier to build quantum computers, since we know which property is most important for the quantum computer to work as expected,” says Jan-Åke Larsson.

The team has also built a physical version with electronic components. They used gates that are similar to the ones in quantum computers, and a toolkit simulates how the quantum computer works. This can allow students and others to simulate and understand how quantum cryptography and quantum teleportation works, among other aspects of quantum computers. 

This new research can add to the increasing crossover between quantum computing and artificial intelligence. One of these crossovers is feature mapping. Other research conducted by IBM Research, MIT, and Oxford scientists has shown that as quantum computers become more powerful, they will be able to perform feature mapping on highly complex data structures, something classical computers can’t do. Feature mapping is important within machine learning, and it can lead to more effective AI that could identify patterns in data that classical computers are unable to detect. 

As more and more research takes place in these fields, there will be increasingly more crossover in the two important areas. 


Alex McFarland is an AI journalist and writer exploring the latest developments in artificial intelligence. He has collaborated with numerous AI startups and publications worldwide.