skip to main content


Title: Self-controlling photonic-on-chip networks with deep reinforcement learning
Abstract We present a novel photonic chip design for high bandwidth four-degree optical switches that support high-dimensional switching mechanisms with low insertion loss and low crosstalk in a low power consumption level and a short switching time. Such four-degree photonic chips can be used to build an integrated full-grid Photonic-on-Chip Network (PCN). With four distinct input/output directions, the proposed photonic chips are superior compared to the current bidirectional photonic switches, where a conventionally sizable PCN can only be constructed as a linear chain of bidirectional chips. Our four-directional photonic chips are more flexible and scalable for the design of modern optical switches, enabling the construction of multi-dimensional photonic chip networks that are widely applied for intra-chip communication networks and photonic data centers. More noticeably, our photonic networks can be self-controlling with our proposed Multi-Sample Discovery model, a deep reinforcement learning model based on Proximal Policy Optimization. On a PCN, we can optimize many criteria such as transmission loss, power consumption, and routing time, while preserving performance and scaling up the network with dynamic changes. Experiments on simulated data demonstrate the effectiveness and scalability of the proposed architectural design and optimization algorithm. Perceivable insights make the constructed architecture become the self-controlling photonic-on-chip networks.  more » « less
Award ID(s):
1650499
PAR ID:
10317242
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Scientific Reports
Volume:
11
Issue:
1
ISSN:
2045-2322
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Reconfigurability of photonic integrated circuits (PICs) has become increasingly important due to the growing demands for electronic–photonic systems on a chip driven by emerging applications, including neuromorphic computing, quantum information, and microwave photonics. Success in these fields usually requires highly scalable photonic switching units as essential building blocks. Current photonic switches, however, mainly rely on materials with weak, volatile thermo‐optic or electro‐optic modulation effects, resulting in large footprints and high energy consumption. As a promising alternative, chalcogenide phase‐change materials (PCMs) exhibit strong optical modulation in a static, self‐holding fashion, but the scalability of present PCM‐integrated photonic applications is still limited by the poor optical or electrical actuation approaches. Here, with phase transitions actuated by in situ silicon PIN diode heaters, scalable nonvolatile electrically reconfigurable photonic switches using PCM‐clad silicon waveguides and microring resonators are demonstrated. As a result, intrinsically compact and energy‐efficient switching units operated with low driving voltages, near‐zero additional loss, and reversible switching with high endurance are obtained in a complementary metal‐oxide‐semiconductor (CMOS)‐compatible process. This work can potentially enable very large‐scale CMOS‐integrated programmable electronic–photonic systems such as optical neural networks and general‐purpose integrated photonic processors.

     
    more » « less
  2. Abstract

    Microwave photonics uses light to carry and process microwave signals over a photonic link. However, light can instead be used as a stimulus to microwave devices that directly control microwave signals. Such optically controlled amplitude and phase-shift switches are investigated for use in reconfigurable microwave systems, but they suffer from large footprint, high optical power level required for switching, lack of scalability and complex integration requirements, restricting their implementation in practical microwave systems. Here, we report Monolithic Optically Reconfigurable Integrated Microwave Switches (MORIMSs) built on a CMOS compatible silicon photonic chip that addresses all of the stringent requirements. Our scalable micrometer-scale switches provide higher switching efficiency and require optical power orders of magnitude lower than the state-of-the-art. Also, it opens a new research direction on silicon photonic platforms integrating microwave circuitry. This work has important implications in reconfigurable microwave and millimeter wave devices for future communication networks.

     
    more » « less
  3. The extraordinary optical properties of single-layer graphene have spurred the development of a variety of photonic components. We have previously demonstrated a scalable and versatile platform to facilitate the integration of graphene and other 2-D materials with chalcogenide glass-based planar photonics. In this paper, we detail the design criteria and optimization guidelines towards high-performance graphene-integrated thermo-optic (TO) switches based on the chalcogenide glass-on-graphene platform. Notably, absorption loss of graphene can be reduced to < 20 dB/cm when it is sandwiched inside photonic structures capitalizing on the anisotropic absorption property of graphene. We quantify energy efficiency of the TO switch, showing that the choice of cladding materials plays a critical role in improving device efficiency. Furthermore, we report a record TO switching efficiency of 10 nm/mW via judicious engineering of the overlap between optical mode and thermal profile.

     
    more » « less
  4. Capmany, José (Ed.)
    This paper adopts advanced monolithic silicon-photonics integrated-circuits manufacturing capabilities to realize system-on-chip photonic-electronic linear-algebra accelerators for self-attention computation in various applications of deep-learning neural networks and Large Language Models. With the features of holistic co-design approaches, optical comb-based broadband modulations, and consecutive matrix-multiplication architecture, the system/circuit/device-level simulations of the proposed accelerator can achieve 2.14-TMAC/s/mm2 computation density and 27.9-fJ/MAC energy efficiency with practical considerations of power/area overhead due to photonic-electronic on-chip conversions, integrations, and calibrations. 
    more » « less
  5. Recent decades have seen significant advancements in integrated photonics, driven by improvements in nanofabrication technology. This field has been developed from integrated semiconductor lasers and low-loss waveguides to optical modulators, enabling the creation of sophisticated optical systems on a chip-scale capable of performing complex functions such as optical sensing, signal processing, and metrology. The tight confinement of optical modes in photonic waveguides further enhances the optical nonlinearity, leading to a variety of nonlinear optical phenomena such as optical frequency combs, second-harmonic generation, and supercontinuum generation. Active tuning of photonic circuits not only is crucial for offsetting variations caused by fabrication in large-scale integration but also serves as a fundamental component in programmable photonic circuits. Piezoelectric actuation in photonic devices offers a low-power, high-speed solution and is essential in the design of future photonic circuits due to its compatibility with materials such as Si and Si3N4, which do not exhibit electro-optic effects. Here, we provide a detailed review of the latest developments in piezoelectric tuning and modulation by examining various piezoelectric materials, actuator designs tailored to specific applications, and the capabilities and limitations of current technologies. In addition, we explore the extensive applications enabled by piezoelectric actuators, including tunable lasers, frequency combs, quantum transducers, and optical isolators. These innovative ways of managing photon propagation and frequency on-chip are expected to be highly sought after in the future advancements of advanced photonic chips for both classical and quantum optical information processing and computing.

     
    more » « less