Quantum Computing Algorithms Computational (15 results)

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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Special Issue is mainly concerned with quantum algorithms, their mathematics from behind and the complexity issues arising from them. It comprises seven papers: Two of them are focused on improving the performance by means of quantum algor…ithms over the best instances of classical ones: 'A Fast Quantum Image Component Labeling Algorithm' [1] by Yan Li, Dapeng Hao, Yang Xu and Kinkeung Lai. 'Quantum Algorithms for Some Strings Problems Based on Quantum String Comparator' [2] by Kamil Khadiev, Artem Ilikaev and Jevgenijs Vihrovs. Another four papers deal with enhanced quantum algorithms: 'Progress towards Analytically Optimal Angles in Quantum Approximate Optimisation': [3] by Daniil Rabinovich, Richik Sengupta, Ernesto Campos, Vishwanathan Akshay and Jacob Biamonte. 'Quantum Weighted Fractional Fourier Transform' [4] by Tieyu Zhao, Tianyu Yang and Yingying Chi. 'On the Amplitude Amplification of Quantum States Corresponding to the Solutions of the Partition Problem' [5] by Mauro Mezzini, Jose J. Paulet, Fernando Cuartero, Hernan I. Cruz and Fernando L. Pelayo. 'On the Complexity of Finding the Maximum Entropy Compatible Quantum State' [6] by Serena Di Giorgio and Paulo Mateus. Last, but not least, one paper researched a classical operational research problem by means of quantum annealing: 'GPS: A New TSP Formulation for Its Generalizations Type QUBO' [7] by Saul Gonzalez-Bermejo, Guillermo Alonso-Linaje and Parfait Atchade-Adelomou. As Guest Editors of this Special Issue, we would like to thank the authors and reviewers who made this possible by promoting, spreading research on and supporting quantum computing.
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Buch. Condition: Neu. Quantum Computing Algorithms and Computational Complexity | Buch | Englisch | 2023 | MDPI AG | EAN 9783036577463 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.