HybridD-GM Model: a computational methodology for quantum computing simulations
Quantum computing is an emerging reality and a technological challenge that is being used as a complement to classical computing in specific areas. Some of the areas that benefit most from the development and application of quantum algorithms are mobility, health, energy, sustainability and the environment.
Our research aims, within the data fusion research area, to consolidate the Hybrid-GM model, designed as a computational model that focuses on the simulation of quantum computation and is designed to exploit the benefits of classical hybrid architecture to the full. This model provides an effective working framework for the study and development of quantum algorithms.
HybriD-GM Functions
• Carry out the integration between classical and quantum computing
• Build logical structures for quantum programming languages
The Hybrid-GM model stands out for its ability to carry out simulations of the Shor and Grover quantum algorithms. These algorithms are recognised for making significant advances in factoring integers and finding elements in unordered lists. HybriD-GM demonstrates significant improvements in performance compared to the previous version, D-GM, and other related work.
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HybriD-GM Functions
• Carry out the integration between classical and quantum computing
• Build logical structures for quantum programming languages
The Hybrid-GM model stands out for its ability to carry out simulations of the Shor and Grover quantum algorithms. These algorithms are recognised for making significant advances in factoring integers and finding elements in unordered lists. HybriD-GM demonstrates significant improvements in performance compared to the previous version, D-GM, and other related work.
More projects
