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Harnessing Quantum Computers for Efficient Optimization in Chemical Engineering
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Author(s): C. Sushama (Mohan Babu University, India), R. V. V. Krishna (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India), V. Satyanarayana (Aditya College of Engineering and Technology, Jawaharlal Nehru Technological University, Kakinada, India)and T. Ganesan (Koneru Lakshmaiah Education Foundation, India)
Copyright: 2024
Pages: 17
Source title:
Real-World Challenges in Quantum Electronics and Machine Computing
Source Author(s)/Editor(s): Christo Ananth (Samarkand State University, Uzbekistan), T. Ananth Kumar (IFET College of Engineering, India)and Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq)
DOI: 10.4018/979-8-3693-4001-1.ch006
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Abstract
Quantum computing (QC) has made it possible for optimization and machine learning to get better. These improvements could have big effects on many areas, like medicine, technology, communication, and finance. There will probably soon be a huge rise in the use of QC in the chemistry, pharmaceutical, and bio-molecular fields. Improvements in quantum hardware and software have sped up the process of putting QC into action. It is very important to find real-life chemical engineering problems that cutting-edge quantum methods could help solve, no matter if they are used in computers today or in the future. The authors go over some basic QC ideas while also talking about the problems with current quantum computers. There is also an outline of quantum algorithms that, when used with current quantum computers, could help chemical engineers with machine learning and optimization. There are also plans for future quantum devices because this research looks into linked uses that could use quantum algorithms run on them.
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