Quantum Computing in 2020: A Systematic Review of Algorithms, Hardware Development, and Practical Applications

Mohan Harish Maturi; Snehal Satish; Karthik Meduri; Geeta Sandeep Nadella

doi:10.36676/urr.v7.i10.1427

Authors

Mohan Harish Maturi Department of Information Technology, University of the Cumberlands, Williamsburg, 40769, KY, USA https://orcid.org/0009-0003-3335-7516
Snehal Satish Department of Information Technology, University of the Cumberlands, Williamsburg, 40769, KY, USA https://orcid.org/0009-0005-5494-8467
Karthik Meduri Department of Information Technology, University of the Cumberlands, Williamsburg, 40769, KY, USA https://orcid.org/0009-0007-6056-7577
Geeta Sandeep Nadella Department of Information Technology, University of the Cumberlands, Williamsburg, 40769, KY, USA https://orcid.org/0000-0001-7126-5186

DOI:

https://doi.org/10.36676/urr.v7.i10.1427

Keywords:

Quantum Computing, Hardware Development, Practical Applications 2020

Abstract

Quantum computing is the developing field at the intersection of computer science and physics with quantum mechanics principles to solve complex problems far outside the abilities of traditional computers. This systematic review analyzes key progress in quantum developments, hardware development, and practical applications in 2020. In terms of algorithms, significant progress was made in cross-quantum conventional methods such as the Variation-Quantum-Eigen solver (VQE) and Quantum-Approximate-Upgrading-Algorithms (QAOA) and alongside breakthroughs in quantum machine-learnings. The hardware front and improvements in qubit stability, error correction, and portability marked the pivotal year for quantum processors, with companies like IBM and Google in charge. Practical applications in cryptography, drug discovery, and optimization remain largely experimental, and industries are increasingly exploring quantum potential. The review also identifies ongoing challenges, including qubit coherence, error rates, and scalability, while outlining future research directions. These challenges in 2020 laid the strong foundation for quantum computing's transition from theoretical promise to practical reality.

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