114 research outputs found
A controllable two-membrane-in-the-middle cavity optomechanical system
We report an optomechanical system with two dielectric membranes inside a
Fabry-Perot cavity. The cavity resonant frequencies are measured in such a
two-membrane-in-the-middle system, which show an interesting
band-structure-like diagram. This system exhibits great controllability on the
parameters of the system. The positions and angles of each membrane can be
manipulated on demand by placing two membranes inside the cavity separately.
The eigenfrequencies of the vibrational modes of the membranes can also be
tuned individually with piezoelectricity. This scheme could be
straightforwardly extended to multiple-membrane-in-the-middle systems, where
more than two membranes are involved. Such a well controllable multiple
membrane optomechanical system provides a promising platform for studying
nonlinear and quantum dynamical phenomena in multimode optomechanics with
distinct mechanical oscillators
Coherent manipulation of spin wave vector for polarization of photons in an atomic ensemble
We experimentally demonstrate the manipulation of two-orthogonal components
of a spin wave in an atomic ensemble. Based on Raman two-photon transition and
Larmor spin precession induced by magnetic field pulses, the coherent rotations
between the two components of the spin wave is controllably achieved.
Successively, the two manipulated spin-wave components are mapped into two
orthogonal polarized optical emissions, respectively. By measuring Ramsey
fringes of the retrieved optical signals, the \pi/2-pulse fidelity of ~96% is
obtained. The presented manipulation scheme can be used to build an arbitrary
rotation for qubit operations in quantum information processing based on atomic
ensembles
Correlation of Influenza Virus Excess Mortality with Antigenic Variation: Application to Rapid Estimation of Influenza Mortality Burden
The variants of human influenza virus have caused, and continue to cause, substantial morbidity and mortality. Timely and accurate assessment of their impact on human death is invaluable for influenza planning but presents a substantial challenge, as current approaches rely mostly on intensive and unbiased influenza surveillance. In this study, by proposing a novel host-virus interaction model, we have established a positive correlation between the excess mortalities caused by viral strains of distinct antigenicity and their antigenic distances to their previous strains for each (sub)type of seasonal influenza viruses. Based on this relationship, we further develop a method to rapidly assess the mortality burden of influenza A(H1N1) virus by accurately predicting the antigenic distance between A(H1N1) strains. Rapid estimation of influenza mortality burden for new seasonal strains should help formulate a cost-effective response for influenza control and prevention
Quantum Interference of Stored Coherent Spin-wave Excitations in a Two-channel Memory
Quantum memories are essential elements in long-distance quantum networks and
quantum computation. Significant advances have been achieved in demonstrating
relative long-lived single-channel memory at single-photon level in cold atomic
media. However, the qubit memory corresponding to store two-channel spin-wave
excitations (SWEs) still faces challenges, including the limitations resulting
from Larmor procession, fluctuating ambient magnetic field, and
manipulation/measurement of the relative phase between the two channels. Here,
we demonstrate a two-channel memory scheme in an ideal tripod atomic system, in
which the total readout signal exhibits either constructive or destructive
interference when the two-channel SWEs are retrieved by two reading beams with
a controllable relative phase. Experimental result indicates quantum coherence
between the stored SWEs. Based on such phase-sensitive storage/retrieval
scheme, measurements of the relative phase between the two SWEs and Rabi
oscillation, as well as elimination of the collapse and revival of the readout
signal, are experimentally demonstrated
DCANet: Dual Convolutional Neural Network with Attention for Image Blind Denoising
Noise removal of images is an essential preprocessing procedure for many
computer vision tasks. Currently, many denoising models based on deep neural
networks can perform well in removing the noise with known distributions (i.e.
the additive Gaussian white noise). However eliminating real noise is still a
very challenging task, since real-world noise often does not simply follow one
single type of distribution, and the noise may spatially vary. In this paper,
we present a new dual convolutional neural network (CNN) with attention for
image blind denoising, named as the DCANet. To the best of our knowledge, the
proposed DCANet is the first work that integrates both the dual CNN and
attention mechanism for image denoising. The DCANet is composed of a noise
estimation network, a spatial and channel attention module (SCAM), and a CNN
with a dual structure. The noise estimation network is utilized to estimate the
spatial distribution and the noise level in an image. The noisy image and its
estimated noise are combined as the input of the SCAM, and a dual CNN contains
two different branches is designed to learn the complementary features to
obtain the denoised image. The experimental results have verified that the
proposed DCANet can suppress both synthetic and real noise effectively. The
code of DCANet is available at https://github.com/WenCongWu/DCANet
The Emerging of Hydrovoltaic Materials as a Future Technology: A Case Study for China
Water contains tremendous energy in various forms, but very little of this energy has yet been harvested. Nanostructured materials can generate electricity by water-nanomaterial interaction, a phenomenon referred to as hydrovoltaic effect, which potentially extends the technical capability of water energy harvesting. In this chapter, starting by describing the fundamental principle of hydrovoltaic effect, including water-carbon interactions and fundamental mechanisms of harvesting water energy with nanostructured materials, experimental advances in generating electricity from water flows, waves, natural evaporation, and moisture are then reviewed. We further discuss potential applications of hydrovoltaic technologies, analyze main challenges in improving the energy conversion efficiency and scaling up the output power, and suggest prospects for developments of the emerging technology, especially in China
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