The exercise was to perform an optimized placement of vehicle sensors as part of a Quantum Computing Challenge sponsored by BMW and Amazon Web Services (AWS). The problem required optimizing the placement of sensors on automobiles to reach the highest coverage at the minimum cost and the problem was configured as an optimization problem that included 3,854 variables and 500 constraints. Quantum Computing Inc. (QCI) had previously provided a solution last year using a D-Wave quantum annealer and a Variational Analog Quantum Oracle (VAQO) approach that required over 7 hours of D-Wave runtime and several hundred sensors.

But the breakthrough in this recent announcement is that QCI has provided a solution that provided similar coverage with only 15 sensors and 6 minutes of processor runtime. The key is a new type of quantum technology called Entropy Quantum Computing (EQC) that QCI obtained through their recent acquisition of Qphoton, a photonic quantum startup spun out of research by Dr. Yuping Huang from the Stevens Institute of Technology in New Jersey. Although the engineering details of the EQC have not been released, we do know it is packaged in a desktop size box and runs at room temperature. It uses photonic technology to take a problem that is submitted through a Hamiltonian matrix and relaxes the system to a ground state using a controlled interaction with the environment. This ground state can be captured and analyzed to provide the solution to the problem. QCI has pointed out that while most quantum processors try to isolate the processor from the external environment by using magnetic shielding, dilution refrigerators, high vacuums, etc., QCI’s approach carefully couples an engineered environment to help collapse the quantum state. We are hopeful that more information about this Entropy Quantum Computing concept will be disclosed by QCI in the future; perhaps once they have submitted patent applications to protect the IP.

For more information about the EQC and how QCI applied this technology to the BMW sensor placement problem, you can view a news release available on their website here, a web page that describes the EQC with a video discussing how they applied it to the BMW problem here, and a final report that describes their solution here.

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