arXiv subjects

Hao Zhang

Publications and source records attributed to Hao Zhang.

At least 1,243 records · Page 69Linked to original sources

arXiv2017

ZM-Net: Real-time Zero-shot Image Manipulation Network

Many problems in image processing and computer vision (e.g. colorization, style transfer) can be posed as 'manipulating' an input image into a corresponding output image given a user-specified guiding signal. A holy-grail solution towards generic image manipulation should be able to efficiently alter an input image with any personalized signals (even signals unseen during training), such as diverse paintings and arbitrary descriptive attributes. However, existing methods are either inefficient to simultaneously process multiple signals (let alone generalize to unseen signals), or unable to handle signals from other modalities. In this paper, we make the first attempt to address the zero-shot image manipulation task. We cast this problem as manipulating an input image according to a parametric model whose key parameters can be conditionally generated from any guiding signal (even unseen ones). To this end, we propose the Zero-shot Manipulation Net (ZM-Net), a fully-differentiable architecture that jointly optimizes an image-transformation network (TNet) and a parameter network (PNet). The PNet learns to generate key transformation parameters for the TNet given any guiding signal while the TNet performs fast zero-shot image manipulation according to both signal-dependent parameters from the PNet and signal-invariant parameters from the TNet itself. Extensive experiments show that our ZM-Net can perform high-quality image manipulation conditioned on different forms of guiding signals (e.g. style images and attributes) in real-time (tens of milliseconds per image) even for unseen signals. Moreover, a large-scale style dataset with over 20,000 style images is also constructed to promote further research.

cs.CV↗

arXiv2017

Strictly nonclassical behavior of a mesoscopic system

We experimentally demonstrate the strictly nonclassical behavior in a many-atom system using a recently derived criterion [E. Kot et al., Phys. Rev. Lett. 108, 233601 (2012)] that explicitly does not make use of quantum mechanics. We thereby show that the magnetic moment distribution measured by McConnell et al. [R. McConnell et al., Nature 519, 439 (2015)] in a system with a total mass of $2.6\times 10^5$ atomic mass units is inconsistent with classical physics. Notably, the strictly nonclassical behavior affects an area in phase space $10^3$ times larger than the Planck quantum $\hbar$.

quant-ph↗

arXiv2017

Atomically sharp 1D SbSeI, SbSI and SbSBr with high stability and novel properties for microelectronic, optoelectronic, and thermoelectric applications

In scaling of transistor dimensions with low source-to-drain currents, 1D semiconductors with certain electronic properties are highly desired. We discover three new 1D materials, SbSeI, SbSI and SbSBr with high stability and novel electronic properties based on first principles calculations. Both dynamical and thermal stability of these 1D materials are examined. The bulk-to-1D transition results in dramatic changes in band gap, effective mass and static dielectric constant due to quantum confinement, making 1D SbSeI a highly promising channel material for transistors with gate length shorter than 1 nm. Under small uniaxial strain, these materials are transformed from indirect into direct band gap semiconductors, paving the way for optoelectronic devices and mechanical sensors. Moreover, the thermoelectric performance of these materials is significantly improved over their bulk counterparts. Finally, we demonstrate the experimental feasibility of synthesizing such atomically sharp V-VI-VII compounds. These highly desirable properties render SbSeI, SbSI and SbSBr promising 1D materials for applications in future microelectronics, optoelectronics, mechanical sensors, and thermoelectrics.

cond-mat.mtrl-sci↗

arXiv2017

Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors

Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the past few years, depth sensors have become a standard device widely used by intelligent robots for 3D perception, which can also offer human skeletal data in 3D space. Several methods based on skeletal data were designed to enable robot awareness of human actions with satisfactory accuracy. However, previous methods treated all body parts and features equally important, without the capability to identify discriminative body parts and features. In this paper, we propose a novel simultaneous Feature And Body-part Learning (FABL) approach that simultaneously identifies discriminative body parts and features, and efficiently integrates all available information together to enable real-time robot awareness of human behaviors. We formulate FABL as a regression-like optimization problem with structured sparsity-inducing norms to model interrelationships of body parts and features. We also develop an optimization algorithm to solve the formulated problem, which possesses a theoretical guarantee to find the optimal solution. To evaluate FABL, three experiments were performed using public benchmark datasets, including the MSR Action3D and CAD-60 datasets, as well as a Baxter robot in practical assistive living applications. Experimental results show that our FABL approach obtains a high recognition accuracy with a processing speed of the order-of-magnitude of 10e4 Hz, which makes FABL a promising method to enable real-time robot awareness of human behaviors in practical robotics applications.

cs.CV↗

arXiv2017

Sequence-based Multimodal Apprenticeship Learning For Robot Perception and Decision Making

Apprenticeship learning has recently attracted a wide attention due to its capability of allowing robots to learn physical tasks directly from demonstrations provided by human experts. Most previous techniques assumed that the state space is known a priori or employed simple state representations that usually suffer from perceptual aliasing. Different from previous research, we propose a novel approach named Sequence-based Multimodal Apprenticeship Learning (SMAL), which is capable to simultaneously fusing temporal information and multimodal data, and to integrate robot perception with decision making. To evaluate the SMAL approach, experiments are performed using both simulations and real-world robots in the challenging search and rescue scenarios. The empirical study has validated that our SMAL approach can effectively learn plans for robots to make decisions using sequence of multimodal observations. Experimental results have also showed that SMAL outperforms the baseline methods using individual images.

cs.RO↗

arXiv2017

Characterization of the previous normal-dose CT scan induced nonlocal means regularization method for low-dose CT image reconstruction

Repeated computed tomography (CT) scans are required in some clinical applications such as image-guided radiotherapy and follow-up observations over a time period. To optimize the radiation dose utility, a normal-dose (or full-dose) CT scan is often first performed to set up reference, followed by a series of low-dose scans. Using the previous normal-dose scan to improve follow-up low-dose scans reconstruction has drawn great interests recently, such as the previous normal-dose induced nonlocal means (ndiNLM) regularization method. However, one major concern with this method is that whether it would introduce false structures or miss true structures when the previous normal-dose image and current low-dose image have different structures (e.g., a tumor could be present, grow, shrink or absent in either image). This study aims to investigate the performance of the ndiNLM regularization method in the above mentioned situations. A patient with lung nodule for biopsy was recruited to this study. A normal-dose scan was acquired to set up biopsy operation, followed by a few low-dose scans during needle intervention toward the nodule. We used different slices to mimic different possible cases wherein the previous normal-dose image and current low-dose image have different structures. The experimental results characterize performance of our ndiNLM regularization method.

physics.med-ph↗

arXiv2017

Heavy Higgs Bosons at Low $\tan β$: from the LHC to 100 TeV

We present strategies to search for heavy neutral Higgs bosons decaying to top quark pairs, as often occurs at low $\tan β$ in type II two Higgs doublet models such as the Higgs sector of the MSSM. The resonant production channel is unsatisfactory due to interference with the SM background. We instead propose to utilize same-sign dilepton signatures arising from the production of heavy Higgs bosons in association with one or two top quarks and subsequent decay to a top pair. We find that for heavier neutral Higgs bosons the production in association with one top quark provides greater sensitivity than production in association with two top quarks. We obtain current limits at the LHC using Run I data at 8 TeV and forecast the sensitivity of a dedicated analysis during Run II at 14 TeV. Then we perform a detailed BDT study for the 14 TeV LHC and a future 100 TeV collider.

hep-ph↗

arXiv2017

UStore: A Distributed Storage With Rich Semantics

Today's storage systems expose abstractions which are either too low-level (e.g., key-value store, raw-block store) that they require developers to re-invent the wheels, or too high-level (e.g., relational databases, Git) that they lack generality to support many classes of applications. In this work, we propose and implement a general distributed data storage system, called UStore, which has rich semantics. UStore delivers three key properties, namely immutability, sharing and security, which unify and add values to many classes of today's applications, and which also open the door for new applications. By keeping the core properties within the storage, UStore helps reduce application development efforts while offering high performance at hand. The storage embraces current hardware trends as key enablers. It is built around a data-structure similar to that of Git, a popular source code versioning system, but it also synthesizes many designs from distributed systems and databases. Our current implementation of UStore has better performance than general in-memory key-value storage systems, especially for version scan operations. We port and evaluate four applications on top of UStore: a Git-like application, a collaborative data science application, a transaction management application, and a blockchain application. We demonstrate that UStore enables faster development and the UStore-backed applications can have better performance than the existing implementations.

cs.DB↗

arXiv2017

Space-Time Representation of People Based on 3D Skeletal Data: A Review

Spatiotemporal human representation based on 3D visual perception data is a rapidly growing research area. Based on the information sources, these representations can be broadly categorized into two groups based on RGB-D information or 3D skeleton data. Recently, skeleton-based human representations have been intensively studied and kept attracting an increasing attention, due to their robustness to variations of viewpoint, human body scale and motion speed as well as the realtime, online performance. This paper presents a comprehensive survey of existing space-time representations of people based on 3D skeletal data, and provides an informative categorization and analysis of these methods from the perspectives, including information modality, representation encoding, structure and transition, and feature engineering. We also provide a brief overview of skeleton acquisition devices and construction methods, enlist a number of public benchmark datasets with skeleton data, and discuss potential future research directions.

cs.CV↗

arXiv2017

Energy Transport Property of Charged Particles with Time-Dependent Damping Force via Manifold-Based Analysis Approach

This paper deals with the energy transport properties of charged particles with time-dependent damping force. Based on the proposed nonlinear dimensionless mapping,the stability and dynamical evolution of the particle system is analyzed with the help of manifold-based analysis approach.It has been found that the particle system possesses two types of energy asymptotic behaviors. More significantly, the underlying mechanism of an "energy barrier" is uncovered,i.e., one generalized invariant spanning curve emerges in the dissipative particle system. These results will be useful to enrich the energy transport behavior knowledge of the particle system.

nlin.CD↗

arXiv2017

The anisotropic ultrahigh hole mobility in strain-engineering two-dimensional penta-SiC$_2$

Using the first-principles calculations based on density functional theory, we systematically investigate the strain-engineering (tensile and compressive strain) electronic, mechanical and transport properties of monolayer penta-SiC$_2$. By applying an in-plane tensile or compressive strain, it is easy to modulate the electronic band structure of monolayer penta-SiC$_2$, which subsequently changes the effective mass of carriers. Furthermore, the obtained electronic properties are predicted to change from indirectly semiconducting to metallic. More interestingly, at room temperature, uniaxial strain can enhance the hole mobility of penta-SiC$_2$ along a particular direction by almost three order in magnitude, $i.e.$ from 2.59 $\times10^3 cm^2/V s$ to 1.14 $\times10^6 cm^2/V s$ (larger than the carrier mobility of graphene, 3.5 $\times10^5 cm^2/V s$), with little influence on the electron mobility. The high carrier mobility of monolayer penta-SiC$_2$ may lead to many potential applications in high-performance electronic and optoelectronic devices

cond-mat.mtrl-sci↗

arXiv2016

Unexpected phonon-transport properties of stanene among 2D group-IV materials from \textit{ab initio}

It has been argued that stanene has lowest lattice thermal conductivity among 2D group-IV materials because of largest atomic mass, weakest interatomic bonding, and enhanced ZA phonon scattering due to the breaking of an out-of-plane symmetry selection rule. However, we show that although the lattice thermal conductivity $κ$ for graphene, silicene and germanene decreases monotonically with decreasing Debye temperature, unexpected higher $κ$ is observed in stanene. By enforcing all the invariance conditions in 2D materials and including Ge $3d$ and Sn $4d$ electrons as valence electrons for germanene and stanene respectively, the lattice dynamics in these materials are accurately described. A large acoustic-optical gap and the bunching of the acoustic phonon branches significantly reduce phonon scattering in stanene, leading to higher thermal conductivity than germanene. The vibrational origin of the acoustic-optical gap can be attributed to the buckled structure. Interestingly, a buckled system has two competing influences on phonon transport: the breaking of the symmetry selection rule leads to reduced thermal conductivity, and the enlarging of the acoustic-optical gap results in enhanced thermal conductivity. The size dependence of thermal conductivity is investigated as well. In nanoribbons, the $κ$ of silicene, germanene and stanene is much less sensitive to size effect due to their short intrinsic phonon mean free paths. This work sheds light on the nature of phonon transport in buckled 2D materials.

cond-mat.mes-hall↗

arXiv2016

Double Higgs production at the 14 TeV LHC and the 100 TeV pp-collider

We consider effective Higgs boson couplings, including both the CP-even and CP-odd couplings, that affect Higgs boson pair production in this study. Through the partial wave analysis, we find that the process $gg\to hh$ is dominated by the $s$-wave component even at a 100~TeV $pp$-collider. Making use of the $s$-wave kinematics, we propose a cut efficiency function to mimic the collider simulation and obtain the potential of measuring Higgs effective couplings at the 14~TeV LHC with an integrated luminosity of $3000~{\rm fb}^{-1}$ and at a 100 TeV $pp$-collider. Analytical expressions of the $2σ$ exclusion limits at the LHC and the $5σ$ discovery bands at the 100 TeV machine are given.

hep-ph↗

arXiv2016

Transitionless intra-cavity quantum state transfer in optomechanical systems

Quantum state transfer between cavities is crucial for quantum information processing and quantum computation in optomechanical systems. Here, we present the first scheme for the transitionless intra-cavity quantum state transfer based on transitionless quantum driving (TQD) algorithm in optomechanical systems. We also present a physically feasible system for the TQD process based on largely detuned optomechanical cavity. With the Gaussian time-dependence coupling strengths, our scheme can achieve the perfect quantum state transfer with no undesired transition and reduce the dependence of accurately controlling evolution time and interval of coupling strengths. Our computational results show that the TQD process can be accomplished with no need of the mechanical oscillator in its ground state and is also robust to the mechanical dissipation.

quant-ph↗

arXiv2016

Entanglement concentration of microwave photons based on Kerr effect in circuit QED

In recent years, superconducting qubits show great potential in quantum computation. Hence, microwave photons become very interesting qubits for quantum information processing assisted by superconducting quantum computation. Here, we present the first protocol for the entanglement concentration on microwave photons, resorting to the cross-Kerr effect in circuit quantum electrodynamics (QED). Two superconducting transmission line resonators (TLRs) coupled to superconducting molecule with the N-type level structure induce the effective cross-Kerr effect for realizing the quantum nondemolition (QND) measurement on microwave photons. With this device, we present a two-qubit polarization parity QND detector on the photon states of the superconducting TLRs, which can be used to concentrate efficiently the nonlocal non-maximally entangled states of microwave photons assisted by several linear microwave elements. This protocol has a high efficiency and it may be useful for solid-state quantum information processing assisted by microwave photons.

quant-ph↗

arXiv2016

Syzygies Probing Scattering Amplitudes

We propose a new efficient algorithm to obtain the locally minimal generating set of the syzygies for an ideal, i.e. a generating set whose proper subsets cannot be generating sets. Syzygy is a concept widely used in the current study of scattering amplitudes. This new algorithm can deal with more syzygies effectively because a new generation of syzygies is obtained in each step and the irreducibility of this generation is also verified in the process. This efficient algorithm can also be applied in getting the syzygies for the modules. We also show a typical example to illustrate the potential application of this method in scattering amplitudes, especially the Integral-By-Part(IBP) relations of the characteristic two-loop diagrams in the Yang-Mills theory.

hep-th↗

arXiv2016

Stability and Strength of Atomically Thin Borophene from First Principles Calculations

A new two-dimensional (2D) material, borophene (2D boron sheet), has been grown successfully recently on single crystal Ag substrates by two parallel experiments [Mannix \textit{et al., Science}, 2015, \textbf{350}, 1513] [Feng \textit{et al., Nature Chemistry}, 2016, \textbf{advance online publication}]. Three main structures have been proposed ($β_{12}$, $χ_3$ and striped borophene). However, the stability of three structures is still in debate. Using first principles calculations, we examine the dynamical, thermodynamical and mechanical stability of $β_{12}$, $χ_3$ and striped borophene. Free-standing $β_{12}$ and $χ_3$ borophene is dynamically, thermodynamically, and mechanically stable, while striped borophene is dynamically and thermodynamically unstable due to high stiffness along $a$ direction. The origin of high stiffness and high instability in striped borophene along $a$ direction can both be attributed to strong directional bonding. This work provides a benchmark for examining the relative stability of different structures of borophene.

cond-mat.mtrl-sci↗

arXiv2016

Piezo Voltage Controlled Planar Hall Effect Devices

The electrical control of the magnetization switching in ferromagnets is highly desired for future spintronic applications. Here we report on hybrid piezoelectric (PZT) /ferromagnetic (Co2FeAl) devices in which the planar Hall voltage in the ferromagnetic layer is tuned solely by piezo voltages. The change of planar Hall voltage is associated with magnetization switching through 90 in the plane under piezo voltages. Room temperature magnetic NOT and NOR gates are demonstrated based on the piezo voltage controlled Co2FeAl planar Hall effect devices without the external magnetic field. Our demonstration may lead to the realization of both information storage and processing using ferromagnetic materials.

cond-mat.mes-hall↗