Yang Sun, Jiayang Wu, Mengxi Tan, Xingyuan Xu, Yang Li, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Applications of optical microcombs," Adv. Opt. Photon. 15, 86-175 (2023)
Optical microcombs represent a new paradigm for generating laser
frequency combs based on compact chip-scale devices, which have
underpinned many modern technological advances for both fundamental
science and industrial applications. Along with the surge in activity
related to optical microcombs in the past decade, their applications
have also experienced rapid progress: not only in traditional fields
such as frequency synthesis, signal processing, and optical
communications but also in new interdisciplinary fields spanning the
frontiers of light detection and ranging (LiDAR), astronomical
detection, neuromorphic computing, and quantum optics. This paper
reviews the applications of optical microcombs. First, an overview of
the devices and methods for generating optical microcombs is provided,
which are categorized into material platforms, device architectures,
soliton classes, and driving mechanisms. Second, the broad
applications of optical microcombs are systematically reviewed, which
are categorized into microwave photonics, optical communications,
precision measurements, neuromorphic computing, and quantum optics.
Finally, the current challenges and future perspectives are
discussed.
Data underlying the results presented in this paper are not publicly
available at this time but may be obtained from the authors upon
reasonable request.
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This value is taken from Fig. 4(a) in Ref. [225].
This value is taken from Figs. 2 and 3 in Ref. [225].
The demonstrated operation bandwidth was limited by the
oscilloscope.
Table 6.
Performance Comparison of Microcomb-Based Optical Communication
Systems
Operations per second, i.e., floating-point operations per
second.
Scalability and reconfigurability: Level 1, the synaptic
weights can hardly be reconfigured; Level 2, the synaptic
weights can be reconfigured, but the network structure
(i.e., the number of layers and neurons in each layer) can
hardly be reconfigured; Level 3, the synaptic weights and
network structure can be reconfigured.
Continuous-wave light source is used in the architecture as
the input data signal, and high-speed updating of the
input data is not demonstrated to achieve a high computing
speed.
Convolution operations per second here.
Table 9.
Comparison of Squeezed Light Generation Based on Optical
Microcombs
This value is taken from Fig. 4(a) in Ref. [225].
This value is taken from Figs. 2 and 3 in Ref. [225].
The demonstrated operation bandwidth was limited by the
oscilloscope.
Table 6.
Performance Comparison of Microcomb-Based Optical Communication
Systems
Operations per second, i.e., floating-point operations per
second.
Scalability and reconfigurability: Level 1, the synaptic
weights can hardly be reconfigured; Level 2, the synaptic
weights can be reconfigured, but the network structure
(i.e., the number of layers and neurons in each layer) can
hardly be reconfigured; Level 3, the synaptic weights and
network structure can be reconfigured.
Continuous-wave light source is used in the architecture as
the input data signal, and high-speed updating of the
input data is not demonstrated to achieve a high computing
speed.
Convolution operations per second here.
Table 9.
Comparison of Squeezed Light Generation Based on Optical
Microcombs
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