Quantum computing: current and potential applications in digital agriculture.

Quantum computers use the properties of quantum physics to perform information storage and processing operations. The operation of these computers involves concepts such as entanglement and superposition, which endow them with a great processing power that even surpasses that of the most powerful current supercomputers, while consuming significantly lower amounts of energy. The different studies analyzed in this review article suggest that quantum computing will have a deep impact in areas such as finance, logistics, transportation, space and automotive technology, materials science, energy, pharmaceutical and healthcare industry, cybersecurity, and agriculture. In digital agriculture, several applications that could be executed more efficiently in quantum computers for data processing and understanding of biological processes were identified and exemplified. These applications are grouped here into the following four areas: bioinformatics, remote sensing, climate modeling, and smart farming. This article also explores the strategic importance of mastering quantum computing, highlights some advantages in relation to classical computing, and presents a mapping of the services already available, enabling institutions to undertake strategic planning for the incorporation of quantum computing into their development processes. Finally, the challenges for the implementation of quantum computing are highlighted, along with some ongoing initiatives aimed at furthering research at the forefront of knowledge in this area applied to digital agriculture.

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Bibliographic Details
Main Authors: SOUZA, K. X. S. de, BOLFE, E. L., LEITE, M. A. de A., BAMBINI, M. D., VISOLI, M. C., LUCHIARI JUNIOR, A., SILVA, F. R. da, ESQUERDO, J. C. D. M., YASSITEPE, J. E. de C. T.
Other Authors: KLEBER XAVIER SAMPAIO DE SOUZA, CNPTIA; EDSON LUIS BOLFE, CNPTIA; MARIA ANGELICA DE ANDRADE LEITE, CNPTIA; MARTHA DELPHINO BAMBINI, CNPTIA; MARCOS CEZAR VISOLI, CNPTIA; ARIOVALDO LUCHIARI JUNIOR, CNPTIA; FELIPE RODRIGUES DA SILVA, CNPTIA; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA; JULIANA ERIKA DE CARVALHO TEIXEIRA, CNPTIA.
Format: Artigo de periódico biblioteca
Language:por
Published: 2024-10-16
Subjects:Agricultura digital, Computação quântica, Ciência da computação, Geotecnologia, Quantum computing, Digital agriculture, Geotechnology, Agricultura de Precisão, Desenvolvimento Rural, Biotecnologia, Computer science, Precision agriculture, Rural development, Biotechnology,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1168099
https://doi.org/10.1590/S1678-3921.pab2024.v59.03753
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Summary:Quantum computers use the properties of quantum physics to perform information storage and processing operations. The operation of these computers involves concepts such as entanglement and superposition, which endow them with a great processing power that even surpasses that of the most powerful current supercomputers, while consuming significantly lower amounts of energy. The different studies analyzed in this review article suggest that quantum computing will have a deep impact in areas such as finance, logistics, transportation, space and automotive technology, materials science, energy, pharmaceutical and healthcare industry, cybersecurity, and agriculture. In digital agriculture, several applications that could be executed more efficiently in quantum computers for data processing and understanding of biological processes were identified and exemplified. These applications are grouped here into the following four areas: bioinformatics, remote sensing, climate modeling, and smart farming. This article also explores the strategic importance of mastering quantum computing, highlights some advantages in relation to classical computing, and presents a mapping of the services already available, enabling institutions to undertake strategic planning for the incorporation of quantum computing into their development processes. Finally, the challenges for the implementation of quantum computing are highlighted, along with some ongoing initiatives aimed at furthering research at the forefront of knowledge in this area applied to digital agriculture.