Doctorate Program in Applied and Engineering Physics
Programa de trabalho/Working programme
Título do programa de trabalhos/Title of the working programme
Neuromorphic nano-optoelectronic circuits for signal processing
Domínio Científico Principal/Main Scientific Domain
Applied and Engineering Physics
Título do programa de trabalhos/Title of the working programme
Neuromorphic nano-optoelectronic circuits for signal processing
Domínio Científico Principal/Main Scientific Domain
Applied and Engineering Physics
Domínio Científico/Scientific Domain
Optoelectronics
1. Sumário/Abstract
To realize the enormous potential of artificial intelligence (AI) and machine
learning information processing systems must be able to deal with astonishingly
large amounts of data in real time and allow ultra-wideband information
exchange within and between machines/equipment and systems. The growing
demand for low energy consuming computing systems capable of ultrafast data
processing and ultra-wideband communications requires solutions based on
disruptive scientific concepts and technologies beyond the ones the current
semiconductor chipsets and architectures are able to deliver.
Neuromorphic technologies capable to mimic neuro-biological architectures
present in the human nervous system and brain seems to be the most promising
approaches to fulfil the requirements of AI and of the future information
and communication systems, due to their capability for incorporate real-time
learning, plasticity, problem-solving abilities and enabling evolutionary
changes.
Purely neuromorphic semiconductor electronic approaches, where billions
of transistors need to be arranged in much more advanced than today’s configurations
to work in parallel in what is called inter-neuron connections (like synapses
in the human central nervous system and brain), seems to have intrinsic
performance bottlenecks in terms of operation speed and interconnectivity.
Optoelectronic and photonic neuromorphic technologies offer much more versatile
solutions with significant performance gains, particularly in terms of speed
and amount of data processing, and energy consumption, since huge amounts
of parallel streams of data can be processed and carried by light signals
at different but close wavelengths, using a small fraction of the energy
needed by electrical pulses in present semiconductor chipset.
This work program aims the investigation of novel neuromorphic nano-optoelectronic
circuits that combine resonant tunnelling nanoelectronic structures with
photonic devices. The main focus will be the development of brain-inspired
(neuromorphic) compact optoelectronic circuits capable of emulate some of
the features of spiking neurons and dynamic synapses. We believe that brain-inspired
optoelectronic circuits will display considerable superior performances in
terms of speed, operating bandwidth and energy consumption to the purely
electronic neuromorphic signal processing solutions.
2. Estado da Arte/ State of the art
The so called industry 4.0 (also commonly referred to as the fourth industrial
revolution), particularly the pillars associated to the internet of everything
concept (“the intelligent connection of people, process, data and things”)
will give rise to a myriad of gadget-like devices and equipment whose full
potential operation will be dependent on the exchange of great amounts of
data and internet traffic levels many folds above the ones required today.
These demands for high information processing speed, parallel processing
and ultra-wide bandwidth, will require novel technological solutions with
tight energy consuming requirements. Moreover, many of these equipment and
machines will incorporate great levels of artificial intelligence (AI).
As consequence there is the need of development of highly efficient ultrafast
information processing schemes and ultrahigh bandwidth communication solutions
within the circuits/equipment blocks and between equipment’s and systems.
Brain-like (neuromorphic) inspired information processing technologies,
including computing and communication, seem to have all the requirements to
comply with the demands of ultrahigh speed and bandwidth. However, while the
implementation of AI systems using computer algorithms of neural networks
is emerging rapidly, the development of the hardware basic elements of an
artificial brain, specifically neuromorphic microchips, is just taking the
first steps.
Relying on the tremendous success of the microelectronics, it would be
expected that semiconductor electronics would be easiest approach towards
the implementation of neuromorphic systems. However, in order to achieve
this goal semiconductor electronics needs to overcome some bottleneck the
actual technologies are facing because of the fundamental physics limitations
associated to the electric field control of charge flows within current
semiconductor chipset implementations.
Light based brain-like (neuromorphic) information processing approach seems
to offer significant performance gains, since many parallel streams of data
can be processed and carried by light signals of different wavelengths using
a fraction of the energy than electrical pulses. Therefore, the scientific
and engineering communities foresee that light based brain-inspired solutions
that take advantage of lightwave characteristics (including electromagnetic
interference immunity and the enormous bandwidth available) will bring to
life disruptive technologies with considerable superior performance in terms
of operation speed, bandwidth and energy consumption [1,2]. Intense research
efforts are underway throughout the world towards the demonstration of light
based neuromorphic technologies capable of emulating the brain spike-encoded
basic information processing procedures [2,3].
3. Objectivos/Objectives
The aim of the doctoral project is to develop brain-inspired neuromorphic
optoelectronic circuits capable of emulate some of the features of spiking
neurons and dynamic synapses, which are based in the integration of resonant
tunnelling diode (RTD) structures with optoelectronic devices. The realization
of the working program will comprehend the study of novel neuromorphic nano-optoelectronic
circuits that combine nanoelectronic devices [e.g. semiconductor double
barrier quantum well resonant tunnelling diodes structures (DBQW-RTDs)]
with photonic devices [e.g. micro/nano light emitting diodes (LEDs) and/or
micro/nano laser diodes (LDs)].
DBQW-RTDs are nanoscale semiconductor electronic devices with a highly-nonlinear
current-voltage characteristics showing ultra-broadband (from dc up to 2
THz) negative differential conductance (NDC), or electrical gain, at room
temperature. These properties allow their operation as excitable systems.
Moreover, the addition of light absorbing and confining layers to the DBQW-RTD
structures adds new functionalities to the device including optical modulation
(RTD-OM) and photo-detection (RTD-PD) which might lead to the implementation
of very fast electronic and optoelectronic circuits, such as optoelectronic
oscillators, whose operation can be controlled by both electrical and light
signals.
Preliminary work on RTD/RTD-PD structures indicates that when integrated
with optoelectronic devices such as light sources (such as LEDs or LDs)
they allow the implementation of circuits with advanced properties including
their operation as optoelectronic excitable dynamic systems with interesting
neuromorphic functionalities. RTD/RTD-PD-LED/LD circuits can operate in
several modes, including (2): i) Bistable; ii) Self-sustained oscillations;
iii) Excitable dynamics; and v) Neural inhibition dynamics. Of particular
importance is the operation as an excitable system.
In the excitable regime appropriate perturbations (electrical and/or optical)
can trigger neuron-like excitable electrical spikes with around 1 V of amplitude
that can directly modulates LEDs/LDs, which generate neuron-like optical
pulses. The neuron-like electrical/optical spike pulses can then be used
to drive other identical neuromorphic circuits forming neural networks where
the different delays between circuits are used to control the functionalities
of individual devices/circuits such as resonators firing.
We believe that such brain-inspired compact neuromorphic optoelectronic
circuits will display considerable superior performances in terms of speed,
operating bandwidth and energy consumption when compared with neuromorphic
electronic signal processing solutions. The operation principle of the RTD-(PD)-LED/LD
neuromorphic photonic circuits under consideration takes advantage of the
RTD nonlinear non-monotonic current-voltage (I-V) characteristic, which
shows significant negative differential conductance (NDC) from dc up to
terahertz frequencies. For more details see [3].
4. Descrição detalhada/Detailed description
The work targets the investigation of neuromorphic nano-optoelectronic
devices and circuits based on the integration of RTDs with LEDs and/or LDs
aiming the development of brain-inspired circuits capable of emulate spiking
neurons and dynamic synapses. To achieve a level of knowledge that can lead
to the development and implementation of above described neuromorphic nano-optoelectronic
devices and circuits it is necessary to understand the operation principles
and the functionalities of their basic building blocks. This will require
knowledge (and benefits from the progresses) in multiple fields including
biology, physics, mathematics, photonics, computer science, electrical engineering,
and networks.
The work will start with the studies towards the familiarization of neuronal
properties and behaviours, particularly the ones associated to spiking neurons
and dynamic synapses. In parallel, the candidate will become familiar with
the principles of operation of RTDs/RTD-PDs and of prototype LEDs and LDs,
and with the relevant microelectronic integration techniques. At the same
time, the candidate will also acquire expertise to be able to use existing
numerical models and simulation packages of the devices currently implemented
using MATLAB. Particular attention will be given to the investigation of
dynamics of Fitzhugh-Nagumo excitable like systems with delayed coupling.
Description of the work plan tasks:
Task 1: State of the art and relevant physical and mathematical models
The activities will start with a thoroughly study of the concepts associated
to photonic and optoelectronic approaches towards the implementation of
neuromorphic information processing systems, including RTD implementation
technologies and RTD operation principle, light emitting diodes and laser
diodes structures and operation principles. Particular attention will be
given to study of the physical and mathematical models of the generation
and transmission of a stimulus through the human nervous system, including
the FitzHugh–Nagumo and Hodgkin–Huxley equations which models in a detailed
manner activation and deactivation dynamics of a spiking neuron. The work
will include the improvement of the exiting numerical models/simulation packages
of the devices and the circuits, and the development of new numerical models/simulation
packages capable to describe coupled resonators. MATLAB or other similar
numerically oriented programming language package will be used. Several RTD-LED
epi-layer structure designs will be investigated with the help of modelling
and simulation tools of advanced nanostructures and quantum transport simulators
such as Wingreen and nanoHub packages.
Task 2: Circuits implementation and characterization
The activities will also include detailed investigation of the operation
regimes of RTD circuits incorporating LEDs and LDs, both numerical/computational
and experimental, first using commercial LEDs and LDs, and then with prototype
designed to be integrated with RTDs. The work will then focus in the study
of circuits with time-delayed feedback mechanisms. The time-delayed feedback
implementation will consist of an optical delay line inserted off-chip,
typically using a low loss optical fibre, with a given time delay. This
delay line will provide a mechanism of reinjection of the fired optical pulses,
analogous to the autaptic neuron. This task will also comprehend the investigation
of the designs possibilities of micro/nano LEDs incorporating single (or
multiple) double barrier quantum well-like structures that show a light-current
characteristic that mimics the DBQW-RTD current-voltage characteristic non-linearities.
Task 3: Generation and propagation of neural spike
A thoroughly investigation of the firing dynamics of a single RTD-(PD)-LED/LD
resonator artificial neuron will be done. The investigation will comprehend
the generation of neural spike (when operating in the excitable regime)
combined with a mechanism of time-delayed feedback. RTD-PD-LED/LD operating
in the excitable dynamic regime combined with a mechanism of time-delayed
feedback will corresponds to the solid-state autaptic neuron configuration.
The work will include the study of the strategies that can allow the successful
implantation of circuit configurations that maximize efficiency and reduce
the energy consumption, therefore decreasing the amount of power dissipated
on a single die, without compromising their expected functionalities.
Task 4: Evaluation of interaction dynamics of artificial neurons
The task will comprehend the implementation and the detailed characterization
of the modes of operation of single and coupled nano-optoelectronic resonators
and the determination of operation conditions that allows the realization
of neuromorphic functions. The coupling between RTD-(PD)-LED/LD resonators
will be investigated in order to assess the practical feasibility of RTD-(PD)-LED/LD
based neural networks. The effects of competing phenomenon between gain
and loss when coupled RTD-(PD)-LED/LD resonators are operated in different
conditions will be evaluated. These studies will help us to understand how
to manipulate and fully tune the resonators excitation dynamics which are
critical for achieving high-level functions in neural networks.
Task 5: Thesis writing up
The final task will be the thesis writing up.
The above tasks do not necessarily follow a chronological order, with some
having activities that will be realized throughout all the period of the
work plan.
Interactions with other research centres/labs:
The project aims the investigation and development of novel neuromorphic
circuits capable of emulating certain brain/neural function based on the
integration of nanoelectronic devices with micro/nano photonic devices. The
research will be hosted by the CENTRA-SIM research labs at the Faculdade
de Ciências da Universidade de Lisboa. The work will benefit from and
reinforce the interaction of the supervisor research group with research
groups or researcher from the following institutions: Professor Edward Wasige
group from the Electronic and Nanoscale Engineering of School of Engineering,
University of Glasgow; Dr. Bruno Romeira, from the International Iberian
Nanotechnology Laboratory, Braga; Professor Paulo Monteiro from the Instituto
de Telecomunicações, Aveiro; and Dr. Tiago Alves from the Instituto
de Telecomunicações, Lisboa. It is also expected some degree
of interaction with researchers of the Grupo de Física Experimental,
Instituto de Plasmas e Fusão Nuclear (IPFN), Instituto Superior Tecnico,
Universidade de Lisboa.
5. Referências/References
[1] “Deep learning with coherent nanophotonic circuits,” Yichen Shen, Nicholas
C. Harris, Scott Skirlo, Mihika Prabhu, Tom Baehr-Jones, Michael Hochberg,
Xin Sun, Shijie Zhao, Hugo Larochelle, Dirk Englund & Marin Soljačić,
Nat. Photonics 11, 441–446 (2017),
[2] “Neuromorphic Photonics,” P. R. Prucnal, B. J. Shastri, and M. C. Teich;
CRC Press/Taylor and Francis Group. ISBN-13: 978-1498725224
[3] “Delay dynamics of neuromorphic optoelectronic nanoscale resonators:
Perspectives and applications,” B. Romeira, J. M. L. Figueiredo, and J.
Javaloyes, Chaos: An Interdisciplinary Journal of Nonlinear Science: 27,
114323 (2017).
Supervisor
Name: José Figueiredo
Institution: FC/U Lisboa
Email: jose.figueiredo@ciencias.ulisboa.pt
ORCID ID: http://orcid.org/0000-0001-5668-7073
12 Março 2018