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Study of quantum computation: applications, challenges and opportunities

Χελιώτης, Κίμων-Κωνσταντίνος Φ., Χελιώτης, Κίμων-Κωνσταντίνος Φ.

Jan 1, 20250 citations

Quantum Computing and Visualization Research Challenges and Opportunities

E. Wes Bethel, Roel Van Beeumen, Talita Perciano

Quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC hardware platforms, and growing interest in learning how to design useful methods that leverage this emerging technology for practical applications. From the perspective of the field of visualization, this article examines research challenges and opportunities along the path from initial feasibility to practical use of QC platforms applied to meaningful problems.Quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC hardware platforms, and growing interest in learning how to design useful methods that leverage this emerging technology for practical applications. From the perspective of the field of visualization, this article examines research challenges and opportunities along the path from initial feasibility to practical use of QC platforms applied to meaningful problems.

quant-pharXiv:2601.07872IEEE Computer Graphics and ApplicationsJan 13, 20261 citation

Quantum Computing: Promises and Challenges

Stefano Patarnello

Springer eBooksJan 1, 20230 citations

The Opportunities and Challenges of Quantum Computing

Fuquan Zhang

With the study of quantum computing in the computer field in recent years, quantum computing and quantum algorithms have gradually been taken seriously by people in the industry.Whether it is the development of quantum computers or the release of quantum cloud platforms, or machine learning, quantum awareness, Quantum simulation and other aspects have provided some help.This article is about the role of quantum computing in the field of computer science, as well as opportunities and challenges.

Biomedical Journal of Scientific & Technical ResearchJul 6, 20184 citations

Quantum Computing: Applications and Challenges

Habiba Drias, Farouk Yalaoui

Information systems engineering and managementJan 1, 20249 citations

Harnessing Quantum Computing for Energy Materials: Opportunities and Challenges

Seongmin Kim, In-Saeng Suh, Travis S. Humble +3 more

Developing high-performance materials is critical for diverse energy applications to increase efficiency, improve sustainability and reduce costs. Classical computational methods have enabled important breakthroughs in energy materials development, but they face scaling and time-complexity limitations, particularly for high-dimensional or strongly correlated material systems. Quantum computing (QC) promises to offer a paradigm shift by exploiting quantum bits with their superposition and entanglement to address challenging problems intractable for classical approaches. This perspective discusses the opportunities in leveraging QC to advance energy materials research and the challenges QC faces in solving complex and high-dimensional problems. We present cases on how QC, when combined with classical computing methods, can be used for the design and simulation of practical energy materials. We also outline the outlook for error-corrected, fault-tolerant QC capable of achieving predictive accuracy and quantum advantage for complex material systems.Developing high-performance materials is critical for diverse energy applications to increase efficiency, improve sustainability and reduce costs. Classical computational methods have enabled important breakthroughs in energy materials development, but they face scaling and time-complexity limitations, particularly for high-dimensional or strongly correlated material systems. Quantum computing (QC) promises to offer a paradigm shift by exploiting quantum bits with their superposition and entanglement to address challenging problems intractable for classical approaches. This perspective discusses the opportunities in leveraging QC to advance energy materials research and the challenges QC faces in solving complex and high-dimensional problems. We present cases on how QC, when combined with classical computing methods, can be used for the design and simulation of practical energy materials. We also outline the outlook for error-corrected, fault-tolerant QC capable of achieving predictive accuracy and quantum advantage for complex material systems.

quant-pharXiv:2601.16816ACS Energy LettersJan 26, 20264 citations

Quantum computing: challenges and opportunities.

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