Quantum Algorithm Developed

A quantum algorithm flourished by researchers led by City College of New York (CCNY) physicist Pouyan Ghaemi reported its capability to study a class of many-electron quantum systems using quantum computers. The research will appear in the December issue of PRX Quantum, a journal of the American Physical Society titled “Creating and Manipulating a Laughlin-Type ν=1/3 Fractional Quantum Hall State on a Quantum Computer with Linear Depth Circuits.”

Superconductivity

Ghaemi, assistant professor in CCNY’s Division of Science said that quantum physics is the fundamental theory of nature that guides the formation of molecules and the resulting matter around us. When we have a macroscopic number of quantum particles such as electrons present in metal interacting with each other, it is well known that a novel phenomenon emerges known as superconductivity.

Ease at Studying

According to Ghaemi, the study systems are ultimately limited for the large numbers of associating quantum particles and their novel properties to date. Ghaemi was confident as he spoke that their research has developed such a quantum algorithm which can use quantum computers study a class of many-electron quantum system.

The Google Quantum Computer
The Google Quantum Computer

Adding to this he also said that studying problems that are quite challenging to study using classical computers is now easier to study by making use of their algorithm which opens a new venue to use the new quantum devices. Further, follow-up studies are motivated by this algorithm and their results are new.  

Quantum Devices at Benefit

During the last few years, significant developments have been witnessed by quantum computers. So noting that Ghaemi said that the possible applications of the development of new quantum algorithms will contribute to realizing applications of quantum computers itself.

Improving quantum computing devices is the direct application of the tools provided by their algorithm. And when the quantum computers can be used for daily life applications, the algorithm’s direct real-life applications would eventually emerge. 

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