LPS Qubit Collaboratory (LQC)

The U.S. Army Research Office (ARO) in partnership with NSA’s Laboratory for Physical Science (LPS) is soliciting Incubator, Collaboration, and Fellowship research proposals for participation in the LPS Qubit Collaboratory (LQC). The mission of the LQC can be captured in three broad goals: 1) pursue disruptive fundamental research and enabling technologies with a focus on qubit development for quantum computing and other applications (such as sensing); 2) grow deep, collaborative partnerships to tackle the most difficult and relevant long-term problems in quantum information science and technology; and 3) build a quantum workforce of tomorrow through research experiences in government at LPS and at LQC partners. The LQC will offer a mechanism for collaborative research between LPS and academia, industry, FFRDCs, and Government Laboratories to advance foundational and transformative research on challenging problems that have hindered progress in quantum information processing and associated technologies. The goal of this BAA is to seek proposals that bring together expertise from the public and private sectors and their respective research infrastructures to advance solutions that may be best approached as a collaborative team. A Collaboratory is “a center without walls, in which the nation’s researchers can perform their research without regard to physical location, interacting with colleagues, accessing instrumentation, sharing data and computational resources, [and] accessing information in digital libraries. This BAA introduces LQC Research Thrusts (A.1.1) which are the technical areas of interest—which will be updated periodically—where partners of the LQC will pursue joint research with LPS through Incubator (A.1.2) and Collaboration (A.1.3) collaborative agreements. The LQC BAA also fulfills the Government’s overarching interest--through the proposed research and on-site research experiences--in creating and training a workforce in quantum science and technology, generating pathways of solutions that feed technology development, establishing partnerships, and creating transition opportunities. In further support of training through research, Section A.1.4 calls for Quantum Computing Research (QuaCR) Graduate and Postdoctoral Fellowships for US citizens working in areas of interest. Substantial progress on solving the most difficult and long-term...

i. The overall scientific and/or technical merits of the proposal. ii. The potential contributions of the effort to the Army mission and the extent to which the research effort will contribute to balancing the overall Army research program. iii. The qualifications, capabilities, and experience of the proposed PI, team leader, or other key personnel who are critical to achievement of the proposed objectives.

Match: none required (federal program listing). This program has MOE requirements, see funding agency for further details. Not Applicable

Fiscal year 2018: INTERNET OF BATTLEFIELD THINGS - The overall objective is to develop the fundamental understanding of dynamically-composable, adaptive, goal-driven Internet of Battlefield Things (IoBTs) to enable predictive analytics for intelligent command and control and battlefield services. DCIST -Develop the underpinning science to extend the reach, situational awareness, and operational effectiveness of Intelligent System/Soldier teams against dynamic threats in complex and contested environments and provide technical and operational superiority through fast, intelligent, resilient and collaborative behaviors. Fiscal year 2021: Develop Protein Crystal Polymer Hybrids; Listening to the Bioelectronic Signature of Cells; Corrosion Investigation and Modeling; Decoding Multisensory Information at Different Spatiotemporal Scales of Neuronal Resolution; Social Intelligent Agents; and Experimental Strain-Based Tissue Damage Analysis to Model Impact and Blast-Induced Traumatic Brain Injury Scenarios. Fiscal year 2023: Example 1: Texas Tech University was awarded a grant W911NF2410035 for effort titled �Using fNIRS to Predict and Diagnose the Cause of Performance Decrements in...