论文标题
使用量子古典混合方法在车辆上进行传感器置换优化
Optimization of Sensor-Placement on Vehicles using Quantum-Classical Hybrid Methods
论文作者
论文摘要
当以全面形式考虑具有不同限制的情况下，将传感器放置在车辆上的安全性和自主能力是一个复杂的优化问题。考虑到量子计算机预计将来能够更加“容易”地解决某些优化问题，因此该问题是BMW量子计算挑战挑战2021的一部分。本文，我们以系统的方式提出了两种用于量子增强溶液的配方。在此过程中，调用必要的简化以适应量子模拟器和硬件的当前功能。提出的结果和详尽的模拟研究的观察结果表明了建议的正确功能和实用性。
Placement of sensors on vehicles for safety and autonomous capability is a complex optimization problem when considered in the full-blown form, with different constraints. Considering that Quantum Computers are expected to be able to solve certain optimization problems more "easily" in the future, the problem was posted as part of the BMW Quantum Computing Challenge 2021. In this paper, we have presented two formulations for quantum-enhanced solutions in a systematic manner. In the process, necessary simplifications are invoked to accommodate the current capabilities of Quantum Simulators and Hardware. The presented results and observations from elaborate simulation studies demonstrate the correct functionality and usefulness of the proposals.
