Project Grant 2611810
- Federal Grant Award Summary Cornell University's Office of Sponsored Programs received a $500,000 Project Grant award (July 15, 2026 – June 30, 2030) from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CFDA 47.070) program. The collaborative research project, titled "Quantum Inference with Pauli Measurements: Fundamental Limits and Algorithms," supports investigator-initiated research in...
- Federal Project Grant Award Summary Cornell University received a $450,000 project grant from the National Science Foundation (NSF) Division of Physics under the Mathematical and Physical Sciences program (CFDA 47.049), awarded July 15, 2025, with completion scheduled for June 30, 2028. The project delivers advanced quantum simulation research and development services focused on expanding the capabilities of trapped-ion quantum processors. The primary research deliverable involves developing and...
- Federal Grant Award Summary Cornell University's Office of Sponsored Programs received a $363,649 Project Grant from the National Science Foundation (NSF) Division of Physics under the Mathematical and Physical Sciences program (CFDA 47.049), awarded July 1, 2025, with completion scheduled for June 30, 2028. The award supports theoretical, computational, and experimental research to develop advanced quantum control methods for fault-tolerant bosonic operations. Specifically, the research team...
- Federal Project Grant Award Summary Cornell University's Office of Sponsored Programs received a $437,479 Project Grant award from the National Science Foundation (NSF) Division of Physics under the Mathematical and Physical Sciences program (CFDA 47.049), effective August 1, 2026, through July 31, 2029. The award supports fundamental research on hybrid-variable topological quantum error correction (QEC), which addresses the challenge of protecting quantum information from environmental noise in...
- Federal Grant Award Summary Cornell University received a $479,482 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), effective October 1, 2025, through September 30, 2028. The award supports research and development of an ultra-low-power cryogenic complementary metal-oxide-semiconductor (CryoCMOS) integrated circuit architecture designed to control superconducting qubits with high-frequency...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded $499,999 to Stony Brook University on July 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct collaborative research on quantum inference using Pauli measurements. The project, slated for completion by June 30, 2030, will deliver fundamental research establishing the information-theoretic limits and practical...
- Federal Project Grant Award Summary Cornell University received a $548,598 CAREER grant from the National Science Foundation's Directorate for Engineering (CFDA 47.041) awarded May 1, 2026, with a performance period extending through April 30, 2031. The project focuses on developing scalable interface technologies for cryogenic quantum processors to address critical input/output bottlenecks limiting quantum system expansion. The primary deliverables include three key innovations: multiplexed...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded a Project Grant totaling $417,818 to The Regents of the University of Colorado (effective September 1, 2025, through August 31, 2028) to develop quantum machine learning (QML) systems that leverage quantum correlations to achieve greater computational efficiency than classical approaches. The research will deliver theoretical frameworks and practical implementations...
- Federal Project Grant Award Summary Cornell University's Office of Sponsored Programs received an $875,000 Project Grant from the U.S. Department of Energy Office of Science (CFDA 81.049) awarded August 1, 2025, with a completion date of July 31, 2027. The award supports research on programmable Floquet algorithms for materials research, specifically focused on enhanced qubit coherence and entangled state preparation on quantum hardware. The research will be conducted at Cornell's Ithaca, New...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Chemistry awarded $450,000 through the Mathematical and Physical Sciences program (CFDA 47.049) to Cornell University, with performance from April 1, 2026, through March 31, 2029. This collaborative research project, led by investigators at Cornell University (Nandini Ananth) and New York University (Mark Tuckerman and Norah Hoffmann), develops hardware-specific quantum algorithms for path integral-based quantum...
Cornell University's Office of Sponsored Programs received a $758,998 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), effective July 1, 2026, through June 30, 2029. The award supports theoretical research establishing the foundational principles of Quantum Boltzmann Machines (QBMs) as a framework for quantum machine learning. The research investigates core technical questions including the conditions under which QBMs avoid training difficulties observed in competing quantum approaches, the design of quantum analogs for established training algorithms, and the extension of generative modeling techniques to leverage both hidden and visible model components. The project employs analytical tools from quantum information theory, optimization theory, and machine learning theory to examine convergence properties, representational capabilities, and computational efficiency. The research deliverables encompass theoretical advances in quantum computing and machine learning methodologies with anticipated applications across science and engineering. Additional project components examine the relationship between Quantum Boltzmann Machines and tensor network methods, as well as the performance of advanced optimization techniques including second-order methods and natural gradient descent. The outcomes are intended to expand the range of problems addressable by advanced computing systems and contribute to national priorities in innovation, economic competitiveness, and secure information technologies, while supporting workforce development in quantum computing and artificial intelligence.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $759.0k | 6/30/26 |