153 research outputs found
Pavlov's dog associative learning demonstrated on synaptic-like organic transistors
In this letter, we present an original demonstration of an associative
learning neural network inspired by the famous Pavlov's dogs experiment. A
single nanoparticle organic memory field effect transistor (NOMFET) is used to
implement each synapse. We show how the physical properties of this dynamic
memristive device can be used to perform low power write operations for the
learning and implement short-term association using temporal coding and spike
timing dependent plasticity based learning. An electronic circuit was built to
validate the proposed learning scheme with packaged devices, with good
reproducibility despite the complex synaptic-like dynamic of the NOMFET in
pulse regime
Temporal intensity correlation of light scattered by a hot atomic vapor
We present temporal intensity correlation measurements of light scattered by
a hot atomic vapor. Clear evidence of photon bunching is shown at very short
time-scales (nanoseconds) imposed by the Doppler broadening of the hot vapor.
Moreover, we demonstrate that relevant information about the scattering
process, such as the ratio of single to multiple scattering, can be deduced
from the measured intensity correlation function. These measurements confirm
the interest of temporal intensity correlation to access non-trivial spectral
features, with potential applications in astrophysics
Negative Differential Resistance, Memory and Reconfigurable Logic Functions based on Monolayer Devices derived from Gold Nanoparticles Functionalized with Electro-polymerizable Thiophene-EDOT Units
We report on hybrid memristive devices made of a network of gold
nanoparticles (10 nm diameter) functionalized by tailored
3,4(ethylenedioxy)thiophene (TEDOT) molecules, deposited between two planar
electrodes with nanometer and micrometer gaps (100 nm to 10 um apart), and
electropolymerized in situ to form a monolayer film of conjugated polymer with
embedded gold nanoparticles (AuNPs). Electrical properties of these films
exhibit two interesting behaviors: (i) a NDR (negative differential resistance)
behavior with a peak/valley ratio up to 17, and (ii) a memory behavior with an
ON/OFF current ratio of about 1E3 to 1E4. A careful study of the switching
dynamics and programming voltage window is conducted demonstrating a
non-volatile memory. The data retention of the ON and OFF states is stable
(tested up to 24h), well controlled by the voltage and preserved when repeating
the switching cycles (800 in this study). We demonstrate reconfigurable Boolean
functions in multiterminal connected NP molecule devices.Comment: Full manuscript, figures and supporting information, J. Phys. Chem.
C, on line, asap (2017
A versatile source of polarisation entangled photons for quantum network applications
We report a versatile and practical approach for generating high-quality
polarization entanglement in a fully guided-wave fashion. Our setup relies on a
high-brilliance type-0 waveguide generator producing paired photon at a telecom
wavelength associated with an advanced energy-time to polarisation transcriber.
The latter is capable of creating any pure polarization entangled state, and
allows manipulating single photon bandwidths that can be chosen at will over
five orders of magnitude, ranging from tens of MHz to several THz. We achieve
excellent entanglement fidelities for particular spectral bandwidths, i.e. 25
MHz, 540 MHz and 100 GHz, proving the relevance of our approach. Our scheme
stands as an ideal candidate for a wide range of network applications, ranging
from dense division multiplexing quantum key distribution to heralded optical
quantum memories and repeaters.Comment: 5 figure
Polarization entangled photon-pair source based on quantum nonlinear photonics and interferometry
We present a versatile, high-brightness, guided-wave source of polarization
entangled photons, emitted at a telecom wavelength. Photon-pairs are generated
using an integrated type-0 nonlinear waveguide, and subsequently prepared in a
polarization entangled state via a stabilized fiber interferometer. We show
that the single photon emission wavelength can be tuned over more than 50 nm,
whereas the single photon spectral bandwidth can be chosen at will over more
than five orders of magnitude (from 25 MHz to 4 THz). Moreover, by performing
entanglement analysis, we demonstrate a high degree of control of the quantum
state via the violation of the Bell inequalities by more than 40 standard
deviations. This makes this scheme suitable for a wide range of quantum optics
experiments, ranging from fundamental research to quantum information
applications. We report on details of the setup, as well as on the
characterization of all included components, previously outlined in F. Kaiser
et al. (2013 Laser Phys. Lett. 10, 045202).Comment: 16 pages, 7 figure
AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators
An adaptive inference method for crossbar (AIDX) is presented based on an
optimization scheme for adjusting the duration and amplitude of input voltage
pulses. AIDX minimizes the long-term effects of memristance drift on artificial
neural network accuracy. The sub-threshold behavior of memristor has been
modeled and verified by comparing with fabricated device data. The proposed
method has been evaluated by testing on different network structures and
applications, e.g., image reconstruction and classification tasks. The results
showed an average of 60% improvement in convolutional neural network (CNN)
performance on CIFAR10 dataset after 10000 inference operations as well as
78.6% error reduction in image reconstruction.Comment: This paper is submitted to IEEE Transactions Circuits and Systems II:
Express Brief
Negative differential resistance and non-volatile memory in hybrid redox organic/nanoparticle devices
International audienc
Modeling and Experimental Demonstration of a Hopfield Network Analog-to-Digital Converter with Hybrid CMOS/Memristor Circuits
The purpose of this work was to demonstrate the feasibility of building recurrent artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memristor circuits. To do so, we modeled a Hopfield network implementing an analog-to-digital converter (ADC) with up to 8 bits of precision. Major shortcomings affecting the ADC's precision, such as the non-ideal behavior of CMOS circuitry and the specific limitations of memristors, were investigated and an effective solution was proposed, capitalizing on the in-field programmability of memristors. The theoretical work was validated experimentally by demonstrating the successful operation of a 4-bit ADC circuit implemented with discrete Pt/TiO2−x/Pt memristors and CMOS integrated circuit components.National Science Foundation CCF-1028378Air Force Office of Scientific Research FA9550-12-1-0038Ministerio de EconomÃa y Competitividad TEC2012-37868-C04-0
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