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Parametrically-Driven Nonlinear Optical Resonators and their Networks for Sensing and Computing


Roy, Arkadev (2023) Parametrically-Driven Nonlinear Optical Resonators and their Networks for Sensing and Computing. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/xsyc-6668.


New physics and novel applications in various fields ranging from biology, and spectroscopy, to manipulation of quantum systems are driven by the availability of coherent light sources including frequency combs in the visible and mid-infrared spectral regimes. Nonlinear optical systems, that are parametrically driven by technologically mature near-infrared lasers, are leveraged in this regard to access challenging wavelengths where conventional lasers may be unavailable. It is of paramount importance to miniaturize these systems and replace the traditional bulky setups thereby paving the way for a plethora of applications. Optical parametric oscillators are among the most prominent examples of such nonlinear systems and beyond their indispensable usage as light sources (both classical and quantum) their unique non-equilibrium dynamics can endow a wealth of functionalities absent in their linear counterparts. These properties can be engineered and utilized for realizing highly sensitive sensors as well as special-purpose computing hardware that may outperform conventional digital computers. A network of these coupled parametric oscillators can be made to interact leading to emergent behaviors that are not expected from the individual constituents.

In this work, we experimentally and theoretically study the dynamics of individual and coupled optical parametric oscillators towards sensing and computing applications. We explore a previously avoided regime of operation for generating ultra-short pulses from these parametrically driven nonlinear resonators that lead to extreme pulse compression. We engineer the nonlinear dynamics of these systems to realize all-optical spectral phase transitions (both first-order and second-order) that behave as highly-sensitive sensors. We show how these critical phenomena can be utilized to enhance the solution accuracy of physics-based solvers in finding optimum solutions to combinatorial optimization problems in the context of coherent Ising machines. We also realize optical parametric oscillators in integrated lithium-niobate nanophotonic platform and demonstrate a mid-infrared frequency comb source that is widely tunable over an octave accompanied by visible frequency comb generation. We develop a comprehensive description to investigate the noise properties of optical parametric oscillators that provide new insights into the phase noise behavior of optical parametric oscillators in their various operating regimes. Finally, we propose a system of parametrically driven resonators as a synthetic medium with highly reconfigurable interactions that can host a plethora of emergent phenomena ranging from topological behaviors to non-Hermitian dynamics. These networks of nonlinear resonators display intriguing dynamical properties in contrast to their static counterparts in condensed-matter physics with implications in quantum sensing and robust device functionality.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:optical parametric oscillators, nonlinear dynamics, coupled resonator networks, nonlinear optics, sensing, computing
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Electrical Engineering
Awards:Charles and Ellen Wilts Prize, 2023.
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Marandi, Alireza
Thesis Committee:
  • Vahala, Kerry J. (chair)
  • Wang, Lihong
  • Faraon, Andrei
  • Marandi, Alireza
Defense Date:7 April 2023
Non-Caltech Author Email:royarkadev1995 (AT)
Funding AgencyGrant Number
Army Research Office (ARO)W911NF-18-1-0285
Air Force Office of Scientific Research (AFOSR)FA9550-20-1-0040
Department of Defense (DOD)N00014-17-1-3030
Record Number:CaltechTHESIS:03142023-213121023
Persistent URL:
Related URLs:
URLURL TypeDescription 4 8 9 5 2 3
Roy, Arkadev0000-0001-5659-8388
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:15119
Deposited By: Arkadev Roy
Deposited On:14 Apr 2023 18:22
Last Modified:17 Oct 2023 16:10

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