arXiv subjects

Xuan Hu

Publications and source records attributed to Xuan Hu.

22 records · Page 2Linked to original sources

arXiv2019

Exploiting Dual-Gate Ambipolar CNFETs for Scalable Machine Learning Classification

Ambipolar carbon nanotube based field-effect transistors (AP-CNFETs) exhibit unique electrical characteristics, such as tri-state operation and bi-directionality, enabling systems with complex and reconfigurable computing. In this paper, AP-CNFETs are used to design a mixed-signal machine learning (ML) classifier. The classifier is designed in SPICE with feature size of 15 nm and operates at 250 MHz. The system is demonstrated based on MNIST digit dataset, yielding 90% accuracy and no accuracy degradation as compared with the classification of this dataset in Python. The system also exhibits lower power consumption and smaller physical size as compared with the state-of-the-art CMOS and memristor based mixed-signal classifiers.

cs.ET↗

arXiv2019

Skyrmion Logic System for Large-Scale Reversible Computation

Computational reversibility is necessary for quantum computation and inspires the development of computing systems in which information carriers are conserved as they flow through a circuit. While conservative logic provides an exciting vision for reversible computing with no energy dissipation, the large dimensions of information carriers in previous realizations detract from the system efficiency, and nanoscale conservative logic remains elusive. We therefore propose a non-volatile reversible computing system in which the information carriers are magnetic skyrmions, topologically-stable magnetic whirls. These nanoscale quasiparticles interact with one another via the spin-Hall and skyrmion-Hall effects as they propagate through ferromagnetic nanowires structured to form cascaded conservative logic gates. These logic gates can be directly cascaded in large-scale systems that perform complex logic functions, with signal integrity provided by clocked synchronization structures. The feasibility of the proposed system is demonstrated through micromagnetic simulations of Boolean logic gates, a Fredkin gate, and a cascaded full adder. As skyrmions can be transported in a pipelined and non-volatile manner at room temperature without the motion of any physical particles, this skyrmion logic system has the potential to deliver scalable high-speed low-power reversible Boolean and quantum computing.

cond-mat.mes-hall↗

arXiv2019

Direct Observation of Infrared Plasmonic Fano Antiresonances by a Nanoscale Electron Probe

In this Letter, we exploit recent breakthroughs in monochromated aberration-corrected scanning transmission electron microscopy (STEM) to resolve infrared plasmonic Fano antiresonances in individual nanofabricated disk-rod dimers. Using a combination of electron energy-loss spectroscopy (EELS) and theoretical modeling, we investigate and characterize a subspace of the weak coupling regime between quasi-discrete and quasi-continuum localized surface plasmon resonances where infrared plasmonic Fano antiresonances appear. This work illustrates the capability of STEM instrumentation to experimentally observe nanoscale plasmonic responses that were previously the domain only of higher resolution infrared spectroscopies.

cond-mat.mes-hall↗

arXiv2019

Shape-based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron

Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Previous proposals for spintronic artificial neurons required external stimuli to perform the leaking functionality, one of the three fundamental functions of a leaky integrate-and-fire (LIF) neuron. The use of this external magnetic field or electrical current stimulus results in either a decrease in energy efficiency or an increase in fabrication complexity. In this work, we modify the shape of previously demonstrated three-terminal magnetic tunnel junction neurons to perform the leaking operation without any external stimuli. The trapezoidal structure causes shape-based DW drift, thus intrinsically providing the leaking functionality with no hardware cost. This LIF neuron therefore promises to advance the development of spintronic neural network crossbar arrays.

physics.app-ph↗