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NOBEL PRIZE 2026

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NSFDirectorate for Mathematical and Physical Sciences

Towards Fourth Generation Quantum Sensors

Active
Institution
University of Pittsburgh, PA
Principal investigator
Junyu Liu
Funding
$600K
Duration
2026–2029
Open portfolio

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Abstract

Quantum sensors use the rules of quantum physics to make measurements with exceptional precision. They are expected to play important roles in timekeeping, navigation, environmental monitoring, imaging, and tests of fundamental physics. This project will develop the scientific foundations for a new generation of quantum sensors that can be connected to quantum processors, guided by machine learning, and linked across quantum networks. The work will help explain when quantum sensors can provide genuine advantages over conventional measurement methods, especially when experiments have limited data, noise, and realistic hardware constraints. By advancing basic science in quantum information and precision measurement, training students in quantum sensing, machine learning, and quantum computing, and supporting outreach activities at the University of Pittsburgh, the project will contribute to the national interest by promoting scientific progress and strengthening the future quantum workforce. The project will build a theoretical framework for "fourth-generation" quantum sensors: processor-assisted, learning-enhanced, and networked sensing systems. A central goal is to develop and apply resolvable expressive capacity, a learning-theoretic measure of how many sensing tasks or parameter features can be reliably resolved from finite experimental data. The research will apply this framework to ensemble and alternating-current quantum sensing, quantum illumination, quantum radar and lidar, Hamiltonian learning, and distributed sensor networks such as quantum-assisted telescope arrays and long-baseline imaging systems. The project will combine methods from quantum metrology, quantum statistical learning theory, classical shadows, quantum information theory, and finite-sample analysis to identify regimes where quantum processors, entanglement, and quantum networks improve sensing performance. It will also develop theory-guided designs for possible future demonstrations in nitrogen-vacancy-center and optomechanical platforms, providing practical guidance for experiments while clarifying the fundamental origins of quantum advantage in sensing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Junyu LiuPI
  • Kaushik P SeshadreesanCo-PI

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Directorate for Mathematical and Physical Sciences01002627DB NSF RESEARCH & RELATED ACTIVITQIS - Quantum Information Scie, OFFICE OF MULTIDISCIPLINARY ACuniversityworkforcemethodsphysicscapacityenvironmentalperformancehamiltonianalternatingconnected

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