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دسته بندی:
محاسبات کوانتومی - Quantum-Computing
سال انتشار:
2022
عنوان انگلیسی مقاله:
Quantum Computing for Applications in Data Fusion
ترجمه فارسی عنوان مقاله:
محاسبات کوانتومی برای برنامه های کاربردی در ترکیب داده ها
منبع:
ieee - ieee Transactions on Aerospace and Electronic Systems;2022;PP;99;10:1109/TAES:2022:3212026
نویسنده:
Veit Stoos; Martin Ulmke; Felix Govaers
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
قیمت: رایگان
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