Robust Multiparticle Quantum Plasmonic Sensing

Louisiana State University, Baton Rouge LA

Investigators

Abstract

This project seeks to develop a new generation of quantum sensors that are not only highly sensitive but also scalable and robust under real-world conditions. Traditional quantum sensing technologies, while powerful, often rely on delicate quantum states that are easily disrupted by noise and loss, limiting their practical use outside controlled laboratory settings. This research takes a fundamentally different approach by designing quantum sensors that extract useful quantum features from classical light sources and operate effectively even in noisy or lossy environments. At the heart of this work is a novel sensing platform based on plasmonic nanostructures—metallic surfaces that can tightly confine light and support complex light–matter interactions. These structures will be paired with quantum protocols that enable the extraction of multiparticle quantum systems, even when the light fields originate from classical or partially coherent sources. The resulting sensors are expected to achieve sensitivity beyond the shot-noise limit, and resolve spatial features smaller than the wavelength of light. This makes them ideal for applications such as gas sensing and the detection of fragile biological samples, where strong illumination could cause damage. Beyond the scientific contributions, the project includes a strong educational component. Undergraduate and graduate students will receive hands-on training in quantum optics, nanofabrication, and data science. The PI’s lab will also engage a wider audience in the implications of quantum sensing and imaging. Demonstrations of quantum sensing techniques will be integrated into classroom instruction, fostering broader interest and understanding of quantum science. Technical Summary This project will establish a robust and scalable framework for quantum plasmonic sensing by developing multiparticle systems extracted from classical plasmonic waves. The central innovation lies in overcoming a longstanding limitation in quantum plasmonics: the intrinsic optical losses that typically degrade quantum coherence and sensitivity. Instead of avoiding these losses, the project introduces methods to distill and exploit quantum correlations from classical or thermal plasmonic fields using photon-number-resolving detection. This opens a new path toward implementing quantum sensing schemes in noisy, lossy, and realistic environments. The theoretical framework supporting the project includes modeling the density matrix of partially coherent plasmonic systems in the Fock basis and using projective measurements to isolate specific quantum subsystems. This approach will be combined with finite-difference time-domain simulations to design and optimize the nanostructures responsible for inducing and manipulating quantum statistical behavior in the sensing field. By addressing both fundamental and practical challenges in quantum plasmonics, this project will contribute to the development of scalable quantum technologies capable of operating in noisy, realistic environments. The outcome will be a robust, multiparticle quantum sensing platform that integrates classical sources, advanced detection, and engineered plasmonic interactions to push the boundaries of what is achievable in quantum-enhanced plasmonic 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.