Optimization of Sensor-Placement on Vehicles using Quantum-Classical Hybrid Methods

• URL: http://arxiv.org/abs/2206.14546v1
• Date: Wed, 29 Jun 2022 11:49:28 GMT
• Title: Optimization of Sensor-Placement on Vehicles using Quantum-Classical Hybrid Methods
• Authors: Sayantan Pramanik, Vishnu Vaidya, Gajendra Malviya, Sudhir Sinha, Shripad Salsingikar, M Girish Chandra, C V Sridhar, Godfrey Mathais, Vidyut Navelkar
• Abstract summary: Quantum Computers are expected to be able to solve certain optimization problems more "easily" in the future. This paper presents two formulations for quantum-enhanced solutions in a systematic manner.
• Score: 0.923687371636986
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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