374 research outputs found
Analog readout for optical reservoir computers
Reservoir computing is a new, powerful and flexible machine learning
technique that is easily implemented in hardware. Recently, by using a
time-multiplexed architecture, hardware reservoir computers have reached
performance comparable to digital implementations. Operating speeds allowing
for real time information operation have been reached using optoelectronic
systems. At present the main performance bottleneck is the readout layer which
uses slow, digital postprocessing. We have designed an analog readout suitable
for time-multiplexed optoelectronic reservoir computers, capable of working in
real time. The readout has been built and tested experimentally on a standard
benchmark task. Its performance is better than non-reservoir methods, with
ample room for further improvement. The present work thereby overcomes one of
the major limitations for the future development of hardware reservoir
computers.Comment: to appear in NIPS 201
High performance photonic reservoir computer based on a coherently driven passive cavity
Reservoir computing is a recent bio-inspired approach for processing
time-dependent signals. It has enabled a breakthrough in analog information
processing, with several experiments, both electronic and optical,
demonstrating state-of-the-art performances for hard tasks such as speech
recognition, time series prediction and nonlinear channel equalization. A
proof-of-principle experiment using a linear optical circuit on a photonic chip
to process digital signals was recently reported. Here we present a photonic
implementation of a reservoir computer based on a coherently driven passive
fiber cavity processing analog signals. Our experiment has error rate as low or
lower than previous experiments on a wide variety of tasks, and also has lower
power consumption. Furthermore, the analytical model describing our experiment
is also of interest, as it constitutes a very simple high performance reservoir
computer algorithm. The present experiment, given its good performances, low
energy consumption and conceptual simplicity, confirms the great potential of
photonic reservoir computing for information processing applications ranging
from artificial intelligence to telecommunicationsComment: non
All-optical Reservoir Computing
Reservoir Computing is a novel computing paradigm which uses a nonlinear
recurrent dynamical system to carry out information processing. Recent
electronic and optoelectronic Reservoir Computers based on an architecture with
a single nonlinear node and a delay loop have shown performance on standardized
tasks comparable to state-of-the-art digital implementations. Here we report an
all-optical implementation of a Reservoir Computer, made of off-the-shelf
components for optical telecommunications. It uses the saturation of a
semiconductor optical amplifier as nonlinearity. The present work shows that,
within the Reservoir Computing paradigm, all-optical computing with
state-of-the-art performance is possible
Emergence of collapsed snaking related dark and bright Kerr dissipative solitons with quartic-quadratic dispersion
We theoretically investigate the dynamics, bifurcation structure and
stability of dark localized states emerging in Kerr cavities in the presence of
second- and fourth-order dispersion. These states form through the locking of
uniform wave fronts, or domain walls, connecting two coexisting stable uniform
states. They undergo a generic bifurcation structure known as collapsed
homoclinic snaking. We characterize the robustness of these states by computing
their stability and bifurcation structure as a function of the main control
parameter of the system. Furthermore, we show that by increasing the dispersion
of fourth order, bright localized states can be also stabilized
Efficient Type II Second Harmonic Generation in an Indium Gallium Phosphide on insulator wire waveguide aligned with a crystallographic axis
We theoretically and experimentally investigate type II second harmonic
generation in III-V-on-insulator wire waveguides. We show that the propagation
direction plays a crucial role and that longitudinal field components can be
leveraged for robust and efficient conversion. We predict that the maximum
theoretical conversion is larger than that of type I second harmonic generation
for similar waveguide dimensions and reach an experimental conversion
efficiency of 12 %/W, limited by the propagation loss
26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017
This work was produced as part of the activities of FAPESP Research,\ud
Disseminations and Innovation Center for Neuromathematics (grant\ud
2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud
FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud
supported by a CNPq fellowship (grant 306251/2014-0)
Simple model for the study of period-doubling instabilities in the nonlinear ring cavity
info:eu-repo/semantics/publishe
Modulational instability, periodic waves and coupled black and white vector solitons in birefringent Kerr media
info:eu-repo/semantics/publishe
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