Quantum Inspired Rapid Context (QuIRC): A Framework for Low-Latency, Context-Aware Data Stream Processing

ColdQuanta Inc., doing business as Infleqtion, proposes to develop a Machine Learning (ML) -enabled framework for general purpose low-latency data pre-processing that will facilitate real-time analysis and resource allocation for downstream tasking across a variety of domains. The novel Quantum Inspired Rapid Context (QuIRC) framework will utilize state-of-the-art ML techniques, enhanced by insights developed in the field of quantum information science, to provide unparalleled contextual awareness in the analysis of streaming data. QuIRC’s primary benefit for Navy end-users will be consummate capacity for near-real-time data stream analysis on field-deployed devices. QuIRC will enable the smart utilization of off-the-shelf models for any desired downstream task in a way that allows real-time software analysis to meet the needs of increasingly capable hardware and sensor systems. Initial QuIRC development will target effective data stream management of Radio Frequency (RF) data, allowing real-time methods for assured Position, Navigation, and Timing (PNT) to exhibit high performance – even while inundated with high-volume data streams from multiple sensors. QuIRC’s core capability is enabled by Infleqtion’s novel Contextual Machine Learning (CML) approach which enhances contextual awareness capabilities of time series models while yielding asymptotic resource advantages. This unique approach will be embedded into the QuIRC framework, which utilizes a tip-and-cue architecture, leveraging downstream model feedback to provide contextual awareness over incoming data streams. Key advantages of the QuIRC framework will include a bring-your-own-task architecture, support for multi-sensor multi-modal ecosystems, and native support for emerging quantum sensing technologies. Moreover, Infleqtion will employ its expertise in low-level optimization techniques to bring the QuIRC capability to the edge; QuIRC will be hosted on a lightweight embedded module, designed to be easily deployed alongside fielded sensor systems with minimal Size, Weight, Power, and Cost (SWaP-C). The proposed Phase I work will establish feasibility for the QuIRC approach and pave the way for integrated prototype development and pilot program activities in a potential Phase II effort. QuIRC’s capabilities will be readily applicable to any integrated sensor system, empowering broad adoption across multiple sectors ranging from the Department of Defense, Federal Agencies, and private sector markets