Coherent and Collective Processes in Micro- and Nano-Resonant Lattices under Non-Equilibrium Conditions
Abstract
Establishing and maintaining coherence between an array of active optical resonators has been a subject of intense research in the past few decades. So far, in optics, the majority of these efforts intends to develop light sources with superior properties in terms of emission wavelength, output radiance, and efficiency. However, lately, there has been a growing interest in investigating coherence formation in active/nonlinear arrays, as a means to find the ground state (global minimum) of various spin systems (XY, Ising, and Heisenberg models). This approach can be used to solve a variety of optimization problems (difficult to be tackled using standard computers) and as well as modeling the response of certain magnetic materials, including ferromagnetic, antiferromagnetic, and frustrated spin configurations. The objective of this project is to build a foundation for understanding the process of coherence formation in active nonlinear photonic networks under non-equilibrium conditions. In the past few years, there has been a rapid progress in the design and fabrication of nano- and micro-scale cavities. At the same time, a host of new concepts have entered into the field of optics from condensed matter physics and quantum field theory that provide entirely new strategies for engineering the spectra of photonic systems. The combination of these developments is expected to open up altogether new avenues for observing novel collective behaviors in active photonic lattices. Our goal here is to study these phenomena both theoretically and experimentally. The fundamental studies proposed here, are expected to lead to fully integrated photonic lattices capable of generating new states of light with higher efficiencies and tailored coherence properties. Such lattices may also be used as energy efficient and microscale platforms for emulating a range of complex magnetic materials and spin systems, or enabling a new type of photonic machine. These networks may be of interest for modeling social behaviors, financial markets, or to implement deep learning algorithms. These efforts can benefit various ONR related activities in directed energy applications, materials discovery, and future of computing.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 25, 2021
- Source ID
- N000142012522
Entities
People
- Mercedeh Khajavikhan
Organizations
- Office of Naval Research
- United States Navy
- University of Southern California