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Quantum computing for several AGV scheduling models. [PDF]

open access: yesSci Rep
Tang L, Yang C, Wen K, Wu W, Guo Y.
europepmc   +1 more source

Quantum computing for finance

Nature Reviews Physics, 2023
Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum ...
Dylan Herman   +7 more
semanticscholar   +1 more source

Recent Advances in Quantum Computing for Drug Discovery and Development

IEEE Nanotechnology Magazine, 2023
Drug discovery and development is a time-consuming and cost-intensive process. Computer-aided drug design can speed up the timeline and reduce costs by decreasing the number of necessary biochemical experiments.
Pei-Hua Wang   +4 more
semanticscholar   +1 more source

Qubit Allocation for Distributed Quantum Computing

IEEE Conference on Computer Communications, 2023
With the advancements in quantum communication, optically connected quantum processors can form a distributed quantum computing system. Distributed quantum computing provides a scalable path to execute more complicated computational tasks that a single ...
Yingling Mao, Yu Liu, Yuanyuan Yang
semanticscholar   +1 more source

Quantum Computability

SIAM Journal on Computing, 1997
Summary: Some theoretical and (potentially) practical aspects of quantum computing are considered. Using the tools of transcendental number theory it is demonstrated that quantum Turing machines (QTM) with rational amplitudes are sufficient to define the class of bounded error quantum polynomial time (BQP) introduced by \textit{E.
Adleman, Leonard M.   +2 more
openaire   +2 more sources

Opportunities and Challenges of Quantum Computing for Engineering Optimization

Journal of Computing and Information Science in Engineering, 2023
Quantum computing as the emerging paradigm for scientific computing has attracted significant research attention in the past decade. Quantum algorithms to solve the problems of linear systems, eigenvalue, optimization, machine learning, and others have
Yan Wang, Jungin E. Kim, K. Suresh
semanticscholar   +1 more source

Materials challenges and opportunities for quantum computing hardware

Science, 2021
Combatting noise on the platform The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general,
Nathalie P. de Leon   +9 more
semanticscholar   +1 more source

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