1,440 research outputs found
A quantum Bose-Hubbard model with evolving graph as toy model for emergent spacetime
We present a toy model for interacting matter and geometry that explores
quantum dynamics in a spin system as a precursor to a quantum theory of
gravity. The model has no a priori geometric properties, instead, locality is
inferred from the more fundamental notion of interaction between the matter
degrees of freedom. The interaction terms are themselves quantum degrees of
freedom so that the structure of interactions and hence the resulting local and
causal structures are dynamical. The system is a Hubbard model where the graph
of the interactions is a set of quantum evolving variables. We show
entanglement between spatial and matter degrees of freedom. We study
numerically the quantum system and analyze its entanglement dynamics. We
analyze the asymptotic behavior of the classical model. Finally, we discuss
analogues of trapped surfaces and gravitational attraction in this simple
model.Comment: 23 pages, 6 figures; updated to published versio
Quantum materials for energy-efficient neuromorphic computing
Neuromorphic computing approaches become increasingly important as we address
future needs for efficiently processing massive amounts of data. The unique
attributes of quantum materials can help address these needs by enabling new
energy-efficient device concepts that implement neuromorphic ideas at the
hardware level. In particular, strong correlations give rise to highly
non-linear responses, such as conductive phase transitions that can be
harnessed for short and long-term plasticity. Similarly, magnetization dynamics
are strongly non-linear and can be utilized for data classification. This paper
discusses select examples of these approaches, and provides a perspective for
the current opportunities and challenges for assembling quantum-material-based
devices for neuromorphic functionalities into larger emergent complex network
systems
Threshold Switching and Self-Oscillation in Niobium Oxide
Volatile threshold switching, or current controlled negative
differential resistance (CC-NDR), has been observed in a range of
transition metal oxides. Threshold switching devices exhibit a
large non-linear change in electrical conductivity, switching
from an insulating to a metallic state under external stimuli.
Compact, scalable and low power threshold switching devices are
of significant interest for use in existing and emerging
technologies, including as a selector element in high-density
memory arrays and as solid-state oscillators for hardware-based
neuromorphic computing.
This thesis explores the threshold switching in amorphous NbOx
and the properties of individual and coupled oscillators based on
this response. The study begins with an investigation of
threshold switching in Pt/NbOx/TiN devices as a function device
area, NbOx film thickness and temperature, which provides
important insight into the structure of the self-assembled
switching region. The devices exhibit combined threshold-memory
behaviour after an initial voltage-controlled forming
process, but exhibit symmetric threshold switching when the RESET
and SET currents are kept below a critical value. In this mode,
the threshold and hold voltages are shown to be independent of
the device area and film thickness, and the threshold power,
while independent of device area, is shown to decrease with
increasing film thickness. These results are shown to be
consistent with a structure in which the threshold switching
volume is confined, both laterally and vertically, to the region
between the residual memory filament and the electrode, and where
the memory filament has a core-shell structure comprising a
metallic core and a semiconducting shell. The veracity of this
structure is demonstrated by comparing experimental results with
the predictions of a resistor network model, and detailed finite
element simulations.
The next study focuses on electrical self-oscillation of an NbOx
threshold switching device incorporated into a Pearson-Anson
circuit configuration. Measurements confirm stable operation of
the oscillator at source voltages as low as 1.06 V, and
demonstrate frequency control in the range from 2.5 to 20.5 MHz
with maximum frequency tuning range of 18 MHz/V. The oscillator
exhibit three distinct oscillation regimes: sporadic spiking,
stable oscillation and damped oscillation. The oscillation
frequency, peak-to-peak amplitude and frequency are shown to be
temperature and voltage dependent with stable oscillation
achieved for temperatures up to ∼380 K. A physics-based
threshold switching model with inclusion of device and circuit
parameters is shown to explain the oscillation waveform and
characteristic.
The final study explores the oscillation dynamics of capacitively
coupled Nb/Nb2O5 relaxation oscillators. The coupled system
exhibits rich collective behaviour, from weak coupling to
synchronisation, depending on the negative differential
resistance response of the individual devices, the operating
voltage and the coupling capacitance. These coupled oscillators
are shown to exhibit stable frequency and phase locking states at
source voltages as low as 2.2 V with MHz frequency tunable range.
The numerical simulation of the coupled system highlights the
role of source voltage, and circuit and device capacitance in
controlling the coupling modes and dynamics
Operating Coupled VO-Based Oscillators for Solving Ising Models
Coupled nano-oscillators are attracting increasing interest because of their potential to perform computation efficiently, enabling new applications in computing and information processing. The potential of phase transition devices for such dynamical systems has recently been recognized. This paper investigates the implementation of coupled VO2-based oscillator networks to solve combinatorial optimization problems. The target problem is mapped to an Ising model, which is solved by the synchronization dynamics of the system. Different factors that impact the probability of the system reaching the ground state of the Ising Hamiltonian and, therefore, the optimum solution to the corresponding optimization problem, are analyzed. The simulation-based analysis has led to the proposal of a novel Second-Harmonic Injection Locking (SHIL) schedule. Its main feature is that SHIL signal amplitude is repeatedly smoothly increased and decreased. Reducing SHIL strength is the mechanism that enables escaping from local minimum energy states. Our experiments show better results in terms of success probability than previously reported approaches. An experimental Oscillatory Ising Machine (OIM) has been built to validate our proposal.</p
A Model of an Oscillatory Neural Network with Multilevel Neurons for Pattern Recognition and Computing
The current study uses a novel method of multilevel neurons and high order
synchronization effects described by a family of special metrics, for pattern
recognition in an oscillatory neural network (ONN). The output oscillator
(neuron) of the network has multilevel variations in its synchronization value
with the reference oscillator, and allows classification of an input pattern
into a set of classes. The ONN model is implemented on thermally-coupled
vanadium dioxide oscillators. The ONN is trained by the simulated annealing
algorithm for selection of the network parameters. The results demonstrate that
ONN is capable of classifying 512 visual patterns (as a cell array 3 * 3,
distributed by symmetry into 102 classes) into a set of classes with a maximum
number of elements up to fourteen. The classification capability of the network
depends on the interior noise level and synchronization effectiveness
parameter. The model allows for designing multilevel output cascades of neural
networks with high net data throughput. The presented method can be applied in
ONNs with various coupling mechanisms and oscillator topology.Comment: 26 pages, 24 figure
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