Quantum Computing, Inc. Awarded Contract by NASA to Support Phase Unwrapping Using Dirac-3 Photonic Optimization Solver

Business / Press Release December 19, 2024

HOBOKEN, NJ, December 17, 2024 -- Quantum Computing Inc. (“QCi” or the “Company”), an innovative, integrated photonics and quantum optics technology company, today announced that the Company has been awarded a prime contract by the National Aeronautics and Space Administration’s (“NASA”) Goddard Space Flight Center. This contract marks a pivotal step forward for QCi by applying its entropy quantum optimization machine, Dirac-3, to support NASA’s advanced imaging and data processing demands.

The contract will apply Dirac-3 to address the challenging phase unwrapping problem for optimally reconstructing images and extracting information from interferometric data generated by radar. QCi will support NASA in its mission to unwrap interferograms at full scale, ultimately enhancing their data quality and accuracy. QCi believes this project will highlight Dirac-3’s capabilities in providing superior solutions to non-deterministic polynomial time hard (NP-hard) problems, significantly improving solution quality and computational speed.

“QCi is proud to support NASA in this critical mission to process large volumes of interferometric imaging data more efficiently,” stated Dr. William McGann, Chief Executive Officer at QCi. “The project’s goal is to demonstrate how QCi’s Dirac-3 can address the phase unwrapping problem and allow NASA to compare the results and benefits of QCi’s quantum optimization technology with state-of-the-art algorithms running on classical computers.”

The outcome of this project, if successful, is expected to produce long-term benefits for NASA, particularly in optimizing big-data processing capabilities and could pave the way for similar applications in other fields where quantum solutions offer speed and quality advantages.

This contract underscores the Company’s commitment to advancing next-generation quantum and photonic technologies to tackle complex optimization and computational challenges.