250 research outputs found
Magneto-transport in high g-factor, low-density two-dimensional electron systems confined in In_0.75Ga_0.25As/In_0.75Al_0.25As quantum wells
We report magneto-transport measurements on high-mobility two-dimensional
electron systems (2DESs) confined in In_0.75Ga_0.25As/In_0.75Al_0.25As single
quantum wells. Several quantum Hall states are observed in a wide range of
temperatures and electron densities, the latter controlled by a gate voltage
down to values of 1.10^11 cm^-2. A tilted-field configuration is used to induce
Landau level crossings and magnetic transitions between quantum Hall states
with different spin polarizations. A large filling factor dependent effective
electronic g-factor is determined by the coincidence method and cyclotron
resonance measurements. From these measurements the change in
exchange-correlation energy at the magnetic transition is deduced. These
results demonstrate the impact of many-body effects in tilted-field
magneto-transport of high-mobility 2DESs confined in
In_0.75Ga_0.25As/In_0.75Al_0.25As quantum wells. The large tunability of
electron density and effective g-factor, in addition, make this material system
a promising candidate for the observation of a large variety of spin-related
phenomena.Comment: 7 pages, 5 figure
Work-in-Progress: Quantized NNs as the Definitive solution for inference on low-power ARM MCUs?
High energy efficiency and low memory footprint are the key requirements for the deployment of deep learning based analytics on low-power microcontrollers. Here we present work-in-progress results with Q-bit Quantized Neural Networks (QNNs) deployed on a commercial Cortex-M7 class microcontroller by means of an extension to the ARM CMSIS-NN library. We show that i) for Q=4 and Q=2 low memory footprint QNNs can be deployed with an energy overhead of 30% and 36% respectively against the 8-bit CMSIS-NN due to the lack of quantization support in the ISA; ii) for Q=1 native instructions can be used, yielding an energy and latency reduction of 3c3.8
7 with respect to CMSIS-NN. Our initial results suggest that a small set of QNN-related specialized instructions could improve performance by as much as 7.5
7 for Q=4, 13.6
7 for Q=2 and 6.5
7 for binary NNs
Anti-crossings of spin-split Landau levels in an InAs two-dimensional electron gas with spin-orbit coupling
We report tilted-field transport measurements in the quantum-Hall regime in
an InAs/In_0.75Ga_0.25As/In_0.75Al_0.25As quantum well. We observe
anti-crossings of spin-split Landau levels, which suggest a mixing of spin
states at Landau level coincidence. We propose that the level repulsion is due
to the presence of spin-orbit and of band-non-parabolicity terms which are
relevant in narrow-gap systems. Furthermore, electron-electron interaction is
significant in our structure, as demonstrated by the large values of the
interaction-induced enhancement of the electronic g-factor.Comment: 4 pages, 3 figure
Electron-phonon coupling in the two phonon mode ternary alloy quantum well
We have investigated the infrared transmission of a two-dimensional (2DEG)
electron gas confined in a single
quantum well in order to study the electron optical phonon interaction in a two
phonon mode system. Infrared transmission experiments have been performed in
both the perpendicular Faraday (PF) and tilted Faraday (TF) configurations for
which the growth axis of the sample is tilted with respect to the incident
light propagation direction and to the magnetic field direction. The
experimental results lead to question the validity of the concept of polaron
mass in a real material.Comment: 7 pages, 3 figure
Two-dimensional electron gas formation in undoped In[0.75]Ga[0.25]As/In[0.75]Al[0.25]As quantum wells
We report on the achievement of a two-dimensional electron gas in completely
undoped In[0.75]Al[0.25]As/In[0.75]Ga[0.25]As metamorphic quantum wells. Using
these structures we were able to reduce the carrier density, with respect to
reported values in similar modulation-doped structures. We found experimentally
that the electronic charge in the quantum well is likely due to a deep-level
donor state in the In[0.75]Al[0.25]As barrier band gap, whose energy lies
within the In[0.75]Ga[0.25]As/In[0.75]Al[0.25]As conduction band discontinuity.
This result is further confirmed through a Poisson-Schroedinger simulation of
the two-dimensional electron gas structure.Comment: 17 pages, 6 figures, to be published in J. Vac. Sci. Technol.
Natural versus anthropic influence on north adriatic coast detected by geochemical analyses
This study focused on the geochemical and sedimentological characterization of recent sediments from two marine sites (S1 and E1) located in the North Adriatic Sea, between the Po River prodelta and the Rimini coast. Major and trace metal concentrations reflect the drainage area of the Po River and its tributaries, considered one of the most polluted areas in Europe. Sediment geochemistry of the two investigated sites denote distinct catchment areas. High values of Cr, Ni, Pb and Zn detected in sediments collected in the Po River prodelta (S1 site) suggest the Po River supply, while lower levels of these elements characterize sediments collected in front of the Rimini coast (E1 site), an indication of Northern Apennines provenance. Historical trends of Pb and Zn reconstructed from the sedimentary record around the E1 site document several changes that can be correlated with the industrialization subsequent to World War II, the implementation of the environmental policy in 1976 and the effects of the Comacchio dumping at the end of 1980. At the S1 site, the down core distributions of trace elements indicate a reduction of contaminants due to the introduction of the Italian Law 319/76 and the implementation of anti-pollution policies on automotive Pb (unleaded fuels) in the second half of the 1980s
Multi-Color Imaging of Magnetic Co/Pt Multilayers
We demonstrate for the first time the realization of a spatial resolved two color, element-specific imaging experiment at the free-electron laser facility FERMI. Coherent imaging using Fourier transform holography was used to achieve direct real space access to the nanometer length scale of magnetic domains of Co/Pt heterostructures via the element-specific magnetic dichroism in the extreme ultraviolet spectral range. As a first step to implement this technique for studies of ultrafast phenomena we present the spatially resolved response of magnetic domains upon femtosecond laser excitation
Benthic foraminifera as indicators of hydrologic and environmental conditions in the Ross Sea (Antarctica)
This study, present data on benthic foraminiferal assemblages from four box cores collected in different areas of the Ross Sea during the 2005 oceanographic cruise in the framework of the Italian Antarctic Research National Programme (PNRA)
Neuraghe: Exploiting CPU-FPGA synergies for efficient and flexible CNN inference acceleration on zynQ SoCs
Deep convolutional neural networks (CNNs) obtain outstanding results in tasks that require human-level understanding of data, like image or speech recognition. However, their computational load is significant, motivating the development of CNN-specialized accelerators. This work presents NEURAghe, a flexible and efficient hardware/software solution for the acceleration of CNNs on Zynq SoCs. NEURAghe leverages the synergistic usage of Zynq ARM cores and of a powerful and flexible Convolution-Specific Processor deployed on the reconfigurable logic. The Convolution-Specific Processor embeds both a convolution engine and a programmable soft core, releasing the ARM processors from most of the supervision duties and allowing the accelerator to be controlled by software at an ultra-fine granularity. This methodology opens the way for cooperative heterogeneous computing: While the accelerator takes care of the bulk of the CNN workload, the ARM cores can seamlessly execute hard-to-accelerate parts of the computational graph, taking advantage of the NEON vector engines to further speed up computation. Through the companion NeuDNN SW stack, NEURAghe supports end-to-end CNN-based classification with a peak performance of 169GOps/s and an energy efficiency of 17GOps/W. Thanks to our heterogeneous computing model, our platform improves upon the state-of-the-art, achieving a frame rate of 5.5 frames per second (fps) on the end-to-end execution of VGG-16 and 6.6fps on ResNet-18
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