Quantum: Claims Solving 3,854-Variable Optimization Problem in 6 Minutes for BMW – High-Performance Computing News Analysis | insideHPC – insideHPC

LEESBURG, Va., July 20, 2021 Quantum Computing Inc. (QCI) today announced it has solved an optimization problem with over 3,800 variables in six minutes by applying a new quantum hardware technology called Entropy Quantum Computing (EQC) to the BMW Vehicle Sensor Placement challenge. The problem consisted of 3,854 variables and more than 500 constraints. In comparison, todays Noisy Intermediate Scale Quantum (NISQ) computers can process approximately 127 variables for a problem of similar complexity.

The 2021BMW GroupandAmazon Web Services (AWS)Quantum Computing Challenge included a Vehicle Sensor Placement use case that challenged participants to find optimal configurations of sensors for a given vehicle that would provide maximum coverage (i.e. detect obstacles in different driving scenarios) at minimum cost. Although QCI placed as a 2021 finalist, its 2022 acquisition of quantum photonics systems company QPhoton provided a powerful suite of new quantum hardware technologies, including EQC. As a result, QCI today presented BMW with a 2022 solution: a superior sensor configuration consisting of 15 sensors yielding 96% coverage using QCIs quantum hardware and software.

The EQC ran over 70x faster than QCIs 2021 hybrid DWave implementation. While the speed itself is notable, the stability of the system allowed the Company to run the problem repeatedly and iteratively, demonstrating its usefulness for business applications.

We are very proud to have achieved what we believe to be an important landmark result in the evolution of quantum, said Bob Liscouski, CEO of QCI. We believe that this proves that innovative quantum computing technologies can solve real business problemstoday. Whats even more significant is the complexity of the problem solved. This wasnt just a rudimentary problem to show that quantum solutions will be feasible someday; this was a very real and significant problem whose solution can potentially contribute to accelerating the realization of the autonomous vehicle industry today.

Historically, commercially-available QPU architectures have only been able to process problems with minimal variable sizes, due to the limited number of qubits available to represent problem variables. These systems also sometimes suffer from significant errors in processing as well as stability and calibration issues, further limiting their commercial viability in todays market. In contrast, QCIs EQC can process computations over a many-variable space, with coherence, thus providing powerful quantum solutions to real-world problems.

EQC operates on the most fundamental principles of quantum physics, especially its measurement postulate, wherein the wave function of a quantum system will collapse to a certain eigenstate due to its interaction with a measurement apparatus or, broadly speaking, the surrounding environment. However, while existing quantum computing architectures must operate on closed quantum systems under extreme requirements to calm the effects of the environment, EQC operates on open quantum systems, carefully coupling a quantum system to an engineered environment, so that its quantum state is collapsed to represent a problemsdesirable solution.

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Quantum: Claims Solving 3,854-Variable Optimization Problem in 6 Minutes for BMW - High-Performance Computing News Analysis | insideHPC - insideHPC

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