arXiv subjects

Xi Chen

Publications and source records attributed to Xi Chen.

At least 1,171 records · Page 65Linked to original sources

arXiv2016

High-temperature superconductivity in single-unit-cell FeSe films on anatase TiO2(001)

We report on the observation of high-temperature ($T_\textrm{c}$) superconductivity and magnetic vortices in single-unit-cell FeSe films on anatase TiO$_2$(001) substrate by using scanning tunneling microscopy. A systematic study and engineering of interfacial properties has clarified the essential roles of substrate in realizing the high-$T_\textrm{c}$ superconductivity, probably via interface-induced electron-phonon coupling enhancement and charge transfer. By visualizing and tuning the oxygen vacancies at the interface, we find their very limited effect on the superconductivity, which excludes interfacial oxygen vacancies as the primary source for charge transfer between the substrate and FeSe films. Our findings have placed severe constraints on any microscopic model for the high-$T_\textrm{c}$ superconductivity in FeSe-related heterostructures.

cond-mat.supr-con↗

arXiv2016

Experimental observation of topological Fermi arcs in type-II Weyl semimetal MoTe2

Weyl semimetal is a new quantum state of matter [1-12] hosting the condensed matter physics counterpart of relativisticWeyl fermion [13] originally introduced in high energy physics. The Weyl semimetal realized in the TaAs class features multiple Fermi arcs arising from topological surface states [10, 11, 14-16] and exhibits novel quantum phenomena, e.g., chiral anomaly induced negative mag-netoresistance [17-19] and possibly emergent supersymmetry [20]. Recently it was proposed theoretically that a new type (type-II) of Weyl fermion [21], which does not have counterpart in high energy physics due to the breaking of Lorentz invariance, can emerge as topologically-protected touching between electron and hole pockets. Here, we report direct spectroscopic evidence of topological Fermi arcs in the predicted type-II Weyl semimetal MoTe2 [22-24]. The topological surface states are confirmed by directly observing the surface states using bulk-and surface-sensitive angle-resolved photoemission spectroscopy (ARPES), and the quasi-particle interference (QPI) pattern between the two putative Fermi arcs in scanning tunneling microscopy (STM). Our work establishes MoTe2 as the first experimental realization of type-II Weyl semimetal, and opens up new opportunities for probing novel phenomena such as exotic magneto-transport [21] in type-II Weyl semimetals.

cond-mat.mes-hall↗

arXiv2016

Magnons and Phonons Optically Driven Out of Local Equilibrium in a Magnetic Insulator

Magnons are the energy quanta of fundamental spin excitations, namely spin waves, and they can make a considerable contribution to energy transport in some magnetic materials in a similar manner as lattice vibration waves or phonons. The coupling and possible non-equilibrium between magnons and other energy carriers have been used to explain several recently discovered thermally driven spin transport and energy conversion phenomena. Here, we report experiments in which local non-equilibrium between magnons and phonons in a single crystalline bulk magnetic insulator, Y3Fe5O12 (yttrium iron garnet, or YIG), has been created optically within a focused laser spot and probed directly with the use of micro-Brillouin light scattering (BLS). By analyzing the experimental results with a thermally induced magnon diffusion model, we obtain the magnon diffusion length of thermal magnons. By explicitly establishing non-equilibrium between magnons and phonons, our studies represent an important step toward a quantitative understanding of various spin-heat coupling phenomena.

cond-mat.mtrl-sci↗

arXiv2016

Knight shifts, nuclear spin-relaxation rates, and spin echo decay times in the pseudogap regime of the cuprates: Simulation and relation to experiment

We study the temperature and doping evolution of the NMR Knight shift, spin relaxation rate, and spin echo decay time in the pseudogap regime of the two-dimensional Hubbard model for parameters believed to be relevant to cuprate superconductors using cluster dynamical mean field theory. We recover the suppression of the Knight shift seen in experiment upon entering the pseudogap regime and find agreement between single and two-particle measures of the pseudogap onset temperature. The simulated spin-echo decay time shows a linear in T behavior at high T which flattens off as T is lowered, and increases as doping is increased. The relaxation rate shows a marked increase as T is lowered but no indication of a pseudogap on the Cu site, and a clear downturn on the O site, consistent with experimental results on single layer materials but different from double layer materials. The consistency of the simulated susceptibilities with experiment, along with similar agreement on the single-particle level and the absence of long-range order and symmetry breaking suggests that the pseudogap is well described by strong short-range correlation effects and that long-range order and multi-orbital effects are not required.

cond-mat.str-el↗

arXiv2016

Scalable Bayesian modeling, monitoring and analysis of dynamic network flow data

Traffic flow count data in networks arise in many applications, such as automobile or aviation transportation, certain directed social network contexts, and Internet studies. Using an example of Internet browser traffic flow through site-segments of an international news website, we present Bayesian analyses of two linked classes of models which, in tandem, allow fast, scalable and interpretable Bayesian inference. We first develop flexible state-space models for streaming count data, able to adaptively characterize and quantify network dynamics efficiently in real-time. We then use these models as emulators of more structured, time-varying gravity models that allow formal dissection of network dynamics. This yields interpretable inferences on traffic flow characteristics, and on dynamics in interactions among network nodes. Bayesian monitoring theory defines a strategy for sequential model assessment and adaptation in cases when network flow data deviates from model-based predictions. Exploratory and sequential monitoring analyses of evolving traffic on a network of web site-segments in e-commerce demonstrate the utility of this coupled Bayesian emulation approach to analysis of streaming network count data.

stat.ME↗

arXiv2016

Experimental demonstration of spontaneous chirality in a nonlinear microresonator

Chirality is an important concept that describes the asymmetry property of a system, which usually emerges spontaneously due to mirror symmetry breaking. Such spontaneous chirality manifests predominantly as parity breaking in modern physics, which has been studied extensively, for instance, in Higgs physics, double-well Bose-Einstein condensates, topological insulators and superconductors. In the optical domain, spontaneous chiral symmetry breaking has been elusive experimentally, especially for micro- and nano-photonics which demands multiple identical subsystems, such as photonic nanocavities, meta-molecules and other dual-core settings. Here, for the first time, we observe spontaneous emergence of a chiral field in a single ultrahigh-Q whispering- gallery microresonator. This counter-intuitive effect arises due to the inherent Kerr nonlinearity-modulated coupling between clockwise (CW) and counterclockwise (CCW) propagating waves. At an ultra-weak input threshold of a few hundred microwatts, the initial chiral symmetry is broken spontaneously, and the CW-to-CCW output ratio reaches 20:1. The spontaneous chirality in microresonator holds great potential in studies of fundamental physics and applied photonic devices.

physics.optics↗

arXiv2016

Aerodynamic Heating in Hypersonic Boundary Layers:\ Role of Dilatational Waves

The evolution of multi-mode instabilities in a hypersonic boundary layer and their effects on aerodynamic heating are investigated. Experiments are conducted in a Mach 6 wind tunnel using Rayleigh-scattering flow visualization, fast-response pressure sensors, fluorescent temperature-sensitive paint (TSP), and particle image velocimetry (PIV). Calculations are also performed based on both parabolized stability equations (PSE) and direct numerical simulations (DNS). It is found that second-mode dilatational waves, accompanied by high-frequency alternating fluid compression and expansion, produce intense aerodynamic heating in a small region that rapidly heats the fluid passing through it. As a result, the surface temperature rapidly increases and results in an overshoot over the nominal transitional value. When the dilatation waves decay downstream, the surface temperature decreases gradually until transition is completed. A theoretical analysis is provided to interpret the temperature distribution affected by the aerodynamic heating.

physics.flu-dyn↗

arXiv2016

Similarity transformation for equilibrium flows, including effects of blowing and suction

A similarity transformation for the mean velocity profiles is obtained in sink flow turbulent boundary layers (TBL), including effects of blowing and suction. It is based on symmetry analysis which transforms the governing partial differential equations (for mean mass and momentum) into an ordinary differential equation and yields a new result including an exact, linear relation between the mean normal ($V$) and streamwise ($U$) velocities. A characteristic length is further introduced which, under a first order expansion in wall blowing/suction velocity, leads to the similarity transformation for $U$. This transformation is shown to be a group invariant under a generalized symmetry analysis and maps different $U$ profiles under different blowing/suction conditions into a (universal) profile under no blowing/suction. Its inverse transformation enables predictions of all mean quantities in the mean mass and momentum equations - $U$, $V$ and the Reynolds shear stress - in good agreement with direct numerical simulation (DNS) data.

physics.flu-dyn↗

arXiv2016

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

This paper describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that also maximizes the mutual information between a small subset of the latent variables and the observation. We derive a lower bound to the mutual information objective that can be optimized efficiently, and show that our training procedure can be interpreted as a variation of the Wake-Sleep algorithm. Specifically, InfoGAN successfully disentangles writing styles from digit shapes on the MNIST dataset, pose from lighting of 3D rendered images, and background digits from the central digit on the SVHN dataset. It also discovers visual concepts that include hair styles, presence/absence of eyeglasses, and emotions on the CelebA face dataset. Experiments show that InfoGAN learns interpretable representations that are competitive with representations learned by existing fully supervised methods.

cs.LG↗

arXiv2016

Improved Techniques for Training GANs

We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework. We focus on two applications of GANs: semi-supervised learning, and the generation of images that humans find visually realistic. Unlike most work on generative models, our primary goal is not to train a model that assigns high likelihood to test data, nor do we require the model to be able to learn well without using any labels. Using our new techniques, we achieve state-of-the-art results in semi-supervised classification on MNIST, CIFAR-10 and SVHN. The generated images are of high quality as confirmed by a visual Turing test: our model generates MNIST samples that humans cannot distinguish from real data, and CIFAR-10 samples that yield a human error rate of 21.3%. We also present ImageNet samples with unprecedented resolution and show that our methods enable the model to learn recognizable features of ImageNet classes.

cs.LG↗

arXiv2016

Quantum phase transition, universality and scaling behaviors in the spin-1/2 Heisenberg model with ferromagnetic and antiferromagnetic competing interactions on honeycomb lattice

The quantum phase transition, scaling behaviors, and thermodynamics in the spin-1/2 quantum Heisenberg model with antiferromagnetic coupling $J>0$ in armchair direction and ferromagnetic interaction $J'<0$ in zigzag direction on a honeycomb lattice are systematically studied using the continuous-time quantum Monte Carlo method. By calculating the Binder ratio $Q_{2}$ and spin stiffness $ρ$ in two directions for various coupling ratio $α=J'/J$ under different lattice sizes, we found that a quantum phase transition from the dimerized phase to the stripe phase occurs at the quantum critical point $α_c=-0.93$. Through the finite-size scaling analysis on $Q_{2}$, $ρ_{x}$ and $ρ_{y}$, we determined the critical exponent related to the correlation length $ν$ to be 0.7212(8), implying that this transition falls into a classical Heisenberg O(3) universality. A zero magnetization plateau is observed in the dimerized phase, whose width decreases with increasing $α$. A phase diagram in the coupling ratio $α$-magnetic field $h$ plane is obtained, where four phases, including dimerized, stripe, canted stripe and polarized phases are identified. It is also unveiled that the temperature dependence of the specific heat $C(T)$ for different $α$'s intersects precisely at one point, similar to that of liquid $^{3}$He under different pressures and several magnetic compounds under various magnetic fields. The scaling behaviors of $Q_{2}$, $ρ$ and $C(T)$ are carefully analyzed. The susceptibility is well compared with the experimental data to give the magnetic parameters of both compounds.

cond-mat.str-el↗

arXiv2016

Prediction of a Two-dimensional Sulfur Nitride (S3N2) Solid for Nanoscale Optoelectronic Applications

Two-dimensional materials have attracted tremendous attention for their fascinating electronic, optical, chemical and mechanical properties. However, the band gaps of most 2D materials reported are smaller than 2.0 eV, which greatly restricted their optoelectronic applications in blue and ultraviolet range of the spectrum. Here, we propose a new stable sulfur nitride (S3N2) 2D crystal that is a covalent network composed solely of S-N σ bonds. S3N2 crystal is dynamically stable as confirmed by the computed phonon spectrum and ab initio molecular dynamics simulations in the NPT ensemble. Hybrid density functional calculations show that 2D S3N2 crystal is a wide, direct band-gap (3.17 eV) semiconductor with good hole mobility. These fascinating electronic properties could pave the way for its optoelectronic applications such as blue or ultra-violet light-emitting diodes (LEDs) and photodetectors.

cond-mat.mtrl-sci↗

arXiv2016

Predictions of canonical wall bounded turbulent flows via a modified $k-ω$ equation

A major challenge in computation of engineering flows is to derive and improve turbulence models built on turbulence physics. Here, we present a physics-based modified $k-ω$ equation for canonical wall bounded turbulent flows (boundary layer, channel and pipe), predicting both mean velocity profile (MVP) and streamwise mean kinetic energy profile (SMKP) with high accuracy over a wide range of Reynolds number ($Re$). The result builds on a multi-layer quantification of wall flows, which allows a significant modification of the $k-ω$ equation. Three innovations are introduced: First, an adjustment of the Karman constant to 0.45 is set for the overlap region with a logarithmic MVP. Second, a wake parameter models the turbulent transport near the centerline. Third, an anomalous dissipation factor represents the effect of a meso layer in the overlap region. Then, a highly accurate (above 99\%) prediction of MVPs is obtained in Princeton pipes, improving the original model prediction by up to 10\%. Moreover, the entire SMKP, including the newly observed outer peak, is predicted. With a slight change of the wake parameter, the model also yields accurate predictions for channels and boundary layers.

physics.flu-dyn↗

arXiv2016

Bulk flow scaling for turbulent channel and pipe flows

We report a theory deriving bulk flow scaling for canonical wall-bounded flows. The theory accounts for the symmetries of boundary geometry (flat plate channel versus circular pipe) by a variational calculation for a large-scale energy length, which characterizes its bulk flow scaling by a simple exponent, i.e. $m=4$ for channel and 5 for pipe. The predicted mean velocity shows excellent agreement with several dozen sets of quality empirical data for a wide range of the Reynolds number (Re), with a universal bulk flow constant $κ\approx0.45$. Predictions for dissipation and turbulent transport in the bulk flow are also given, awaiting data verification.

physics.flu-dyn↗

arXiv2016

Experimental Observation of the Quantum Anomalous Hall Effect in a Magnetic Topological Insulator

The quantized version of the anomalous Hall effect has been predicted to occur in magnetic topological insulators, but the experimental realization has been challenging. Here, we report the observation of the quantum anomalous Hall (QAH) effect in thin films of Cr-doped (Bi,Sb)2Te3, a magnetic topological insulator. At zero magnetic field, the gate-tuned anomalous Hall resistance reaches the predicted quantized value of h/e^2,accompanied by a considerable drop of the longitudinal resistance. Under a strong magnetic field, the longitudinal resistance vanishes whereas the Hall resistance remains at the quantized value. The realization of the QAH effect may lead to the development of low-power-consumption electronics.

cond-mat.mes-hall↗

arXiv2016

Benchmarking Deep Reinforcement Learning for Continuous Control

Recently, researchers have made significant progress combining the advances in deep learning for learning feature representations with reinforcement learning. Some notable examples include training agents to play Atari games based on raw pixel data and to acquire advanced manipulation skills using raw sensory inputs. However, it has been difficult to quantify progress in the domain of continuous control due to the lack of a commonly adopted benchmark. In this work, we present a benchmark suite of continuous control tasks, including classic tasks like cart-pole swing-up, tasks with very high state and action dimensionality such as 3D humanoid locomotion, tasks with partial observations, and tasks with hierarchical structure. We report novel findings based on the systematic evaluation of a range of implemented reinforcement learning algorithms. Both the benchmark and reference implementations are released at https://github.com/rllab/rllab in order to facilitate experimental reproducibility and to encourage adoption by other researchers.

cs.LG↗

arXiv2016

Analytic prediction for planar turbulent boundary layers

Analytic predictions of mean velocity profile (MVP) and streamwise ($x$) development of related integral quantities are presented for flows in channel and turbulent boundary layer (TBL), based on a symmetry analysis of eddy length and total stress. Specific predictions are the friction velocity $u_τ$: ${ U_e/u_τ}\approx 2.22\ln Re_x+2.86-3.83\ln(\ln Re_x)$; the boundary layer thickness $δ_e$: $x/δ_e \approx 7.27\ln Re_x-5.18-12.52\ln(\ln Re_x)$; the momentum thickness Reynolds number: $Re_x/Re_θ=4.94[{(\ln {{\mathop{\rm Re}\nolimits} _θ } + 1.88)^2} + 1]$, all in good agreement with empirical data.

physics.flu-dyn↗

arXiv2016

Experimental realization of stimulated Raman shortcut-to-adiabatic passage with cold atoms

Accurate control of a quantum system is a fundamental requirement in many areas of modern science ranging from quantum information processing to high-precision measurements. A significantly important goal in quantum control is to prepare a desired state as fast as possible with sufficiently high fidelity allowed by available resources and experimental constraints. Stimulated Raman adiabatic passage (STIRAP) is a robust way to realize high-fidelity state transfer but it requires a sufficiently long operation time to satisfy the adiabatic criteria. We here theoretically propose and then experimentally demonstrate a shortcut-to-adiabatic protocol to speed up the STIRAP. By modifying the shapes of the Raman pulses, we experimentally realize a fast and high-fidelity stimulated Raman shortcut-to-adiabatic passage that is robust against control parameter variations. The all-optical, robust, and fast protocol demonstrated here provides an efficient and practical way to control quantum systems.

quant-ph↗