دسته بندی:

محاسبات کوانتومی - Quantum-Computing

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سال انتشار:

2022

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عنوان انگلیسی مقاله:

Quantum Computing for Applications in Data Fusion

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ترجمه فارسی عنوان مقاله:

محاسبات کوانتومی برای برنامه های کاربردی در ترکیب داده ها

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منبع:

ieee - ieee Transactions on Aerospace and Electronic Systems;2022;PP;99;10:1109/TAES:2022:3212026

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نویسنده:

Veit Stoos; Martin Ulmke; Felix Govaers

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چکیده انگلیسی:

Quantum computing promises significant improvements of computation capabilities in various fields such as machine learning and complex optimization problems. Rapid technological advancements suggest that adiabatic and gate base quantum computing may see practical applications in the near future. In this work, we adopt quantum computing paradigms to develop solvers for two well–known combinatorial optimization problems in information fusion and resource management: multi-target data association (MTDA) and weapon target assignment (WTA). These problems are NP-hard (non-)linear integer programming optimization tasks which become computationally expensive for large problem sizes. We derive the problem formulations adapted for the use in quantum algorithms and present solvers based on adiabatic quantum computing (AQC) and the Quantum Approximative Optimization Algorithm (QAOA). The feasibility of the models is demonstrated by numerical simulation and first experiments on quantum hardware.
Index Terms: adiabatic quantum computing | weapon-target assignment | data association | multi-target tracking | quantum gates | Ising model

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قیمت: رایگان

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توضیحات اضافی:

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