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Unveiling Advanced Computational Applications in Quantum Computing: A Comprehensive Review

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Authors: J H Markna, T P Palatia, Smeetraj Gohel, Bharat Kataria

Year

2023

Paper ID

11731

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

178

Citations

6

Abstract

The field of advanced computing applications could experience a significant impact from quantum computing, which is a rapidly developing field with the potential to revolutionize numerous areas of science and technology. In this review, we explore into the various ways in which complex computational problems could be tackled by utilizing quantum computers, including machine learning, optimization, and simulation. One potential application of quantum computers is in machine learning, where they could be used to improve the accuracy and efficiency of algorithms. Complex optimization problems, such as those encountered in logistics and finance, can be addressed using quantum computers as well. Furthermore, the utilization of quantum computers could enable the simulation of intricate systems, such as molecules and materials, leading to significant applications in fields like Physics and Material Technology. Although quantum computers are currently in the early stages of development, they possess the potential to propel numerous areas of science and technology forward in a significant manner. Further research and development are needed to fully realize the potential of quantum computing in the field of advanced computing applications.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • The field of advanced computing applications could experience a significant impact from quantum computing, which is a rapidly developing field with the potential to...

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Current Paper #11731 #69038 Physically Constrained Ensemble... #69034 Hardware-aware Low-latency Quan... #69023 Scalable Quantum Algorithms for... #69003 QBugLM: An Agentic Benchmarking...

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