Towards a Programmable Plasmonic Information Processor based on Graphene, 2D Materials, and Rare-Earth Atoms
Abstract
The world of quantum mechanics holds enormous potential to address unsolved problems in communications, computation, and precision measurements. Efforts are underway across the globe to develop such technologies in various physical systems, including atoms, superconductors, and topological states of matter. However, a central bottleneck lies in achieving greater control of light and matter at the discreteness of photons and electrons in an architecture capable of scaling to millions or billions of atom-like systems to achieve practical utility in error-corrected quantum information processing. Similar requirements also exist in proposed machine learning hardware architectures that may enable substantial speed-ups in training tasks by quantum entanglement (as in quantum machine learning proposals) or simply by making use of phase coherence in computing systems (as in proposed machine learning accelerators). The objective of this research proposal is to address the underlying technological gap- the current inability to realize coherent interactions between optical fields and atom-like systems in a scalable way. Our approach encompasses tightly integrated experimental (E) and theoretical (T) activities over a 5-year program period- Experiment- To overcome challenges related to excited state emitter decoherence and weak light-matter interactions, we propose (E1) the development of a light-matter interface based on atomically engineered plasmonic resonators with 2D material assembly, such as hexagonal boron nitride (hBN)-graphene-hBN, and nanopatterned silicon nitride (SiNx). We will explore (E2) the coupling of these resonators with rare-earth ions, known for their exceptionally long optical and spin coherence properties. Special attention will be given to erbium atoms due to their low-loss photon propagation in silicon optical fibers. Lastly, (E3) we will investigate the scalable integration of E1 and E2 into a photonic integrated circuit (PIC) architecture, utilizing cutting-edge silicon and silicon-nitride waveguides with modulators, detectors, and other essential components such as phase change materials (PCMs) or floating gate memories for non-volatile re-configurability. Theory- The theoretical component will concentrate on systematically modeling and optimizing the proposed platform, considering the unique properties of the materials and components utilized. This will include investigating the fundamental principles governing plasmon-mediated interactions with rare-earth ions and the linear dispersion of acoustic graphene surface plasmon polaritons (AGSPPs) in the PIC architecture. The computational approaches for modeling long-range optical interactions, guided topologically protected AGSPPs, and the implementation of weights, integration, summation, and triggering of firing neurons in artificial neural networks (ANNs) for AGSPPs will also be explored. The theoretical work will provide a robust foundation for guiding the program s experimental activities, driving innovation in the development of next-generation photonic devices and systems. We will seek to realize the following overarching device goals-capabilities- • Programmable light-matter interaction that could maintain coherence even at ambient temperature • High-density coherent light-matter interfaces enabled by the strong 2D plasmonic confinement • Single-photon-level nonlinearities enabled by the ultrastrong optical field concentration These goals, when realized, will resolve the bottleneck in constructing new computing paradigms that operate with and make use of the discreteness and coherence of quantum mechanics. By addressing the technological gap and realizing coherent interactions between optical fields and atom-like systems in a scalable way, our integrated experimental and theoretical approach has the potential to drive innovation in the development of next-generation photonic devices and systems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 06, 2024
- Source ID
- FA95502310472
Entities
People
- Michael Leuenberger
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Central Florida