QCi awarded NASA contract to apply Dirac-3 photonic optimisation solver
The company says its technology will improve the quality and accuracy of data obtained by radar, and hopes the project will produce long-term benefits for optimising big-data processing capabilities
Quantum Computing Inc. (QCi), an integrated photonics and quantum optics technology company, has announced that it has been awarded a prime contract by the NASA Goddard Space Flight Center. QCi says this contract marks a pivotal step forward by applying its entropy quantum optimisation 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 says it will support NASA in its mission to unwrap interferograms at full scale, ultimately enhancing their data quality and accuracy. The company 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 William McGann, CEO 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 optimisation 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 optimising big-data processing capabilities, and could pave the way for similar applications in other fields where quantum solutions offer speed and quality advantages.
The company says this contract underscores its commitment to advancing next-generation quantum and photonic technologies to tackle complex optimisation and computational challenges.
