arXiv subjects

Chong Wang

Publications and source records attributed to Chong Wang.

At least 361 records · Page 20Linked to original sources

arXiv2018

Bright Luminescent Surface States on the Edges of Wide-bandgap Two-dimensional Lead Halide Perovskite

Three-dimensional lead halide perovskites have surprised people for their defect-tolerant electronic and optical properties, two-dimensional lead halide layered structures exhibit even more puzzling phenomena: luminescent edge states in Ruddlesden-Popper perovskites and conflicting reports of highly luminescent versus non-emissive CsPb$_{\text{2}}$Br$_{\text{5}}$. In this work, we report the observation of bright luminescent surface states on the edges of CsPb$_{\text{2}}$Br$_{\text{5}}$ microplatelets. We prove that green surface emission makes wide-bandgap single crystal CsPb$_{\text{2}}$Br$_{\text{5}}$ highly luminescent. Using polarized Raman spectroscopy and atomic-resolution transmission electron microscopy, we further prove that polycrystalline CsPb$_{\text{2}}$Br$_{\text{5}}$ is responsible for the bright luminescence. We propose that these bright edge states originate from corner-sharing clusters of PbBr$_{\text{6}}$ in the distorted regions between CsPb$_{\text{2}}$Br$_{\text{5}}$ nanocrystals. Because metal halide octahedrons are building blocks of perovskites, our discoveries settle a long-standing controversy over the basic property of CsPb$_{\text{2}}$Br$_{\text{5}}$ and open new opportunities to understand, design and engineer perovskite solar cells and other optoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2018

Emergent Multi-flavor QED3 at the Plateau Transition between Fractional Chern Insulators: Applications to graphene heterostructures

Recent experiments in graphene heterostructures have observed Chern insulators - integer and fractional Quantum Hall states made possible by a periodic substrate potential. Here we study theoretically the competition between different Chern insulators, which can be tuned by the amplitude of the periodic potential, leads to a new family of quantum critical points described by QED$_3$-Chern-Simons theory. At these critical points, $N_f$ flavors of Dirac fermions interact through an emergent U$(1)$ gauge theory at Chern-Simons level $K$, and remarkably, the entire family (with any $N_f$ or $K$) can be realized at special values of the external magnetic field. Transitions between particle-hole conjugate Jain states realize "pure" QED$_3$ in which multiple flavors of Dirac fermion interact with a Maxwell U$(1)$ gauge field. The multi-flavor nature of the critical point leads to an emergent SU$(N_f)$ symmetry. Specifically, at the transition from a $ν=$1/3 to 2/3 quantum Hall state, the emergent SU(3) symmetry predicts an octet of charge density waves with enhanced susceptibilities, which is verified by DMRG numerical simulations on microscopic models applicable to graphene heterostructures. We propose experiments on Chern insulators that could resolve open questions in the study of 2+1 dimensional conformal field theories and test recent duality inspired conjectures.

cond-mat.str-el↗

arXiv2018

Attention-based Graph Neural Network for Semi-supervised Learning

Recently popularized graph neural networks achieve the state-of-the-art accuracy on a number of standard benchmark datasets for graph-based semi-supervised learning, improving significantly over existing approaches. These architectures alternate between a propagation layer that aggregates the hidden states of the local neighborhood and a fully-connected layer. Perhaps surprisingly, we show that a linear model, that removes all the intermediate fully-connected layers, is still able to achieve a performance comparable to the state-of-the-art models. This significantly reduces the number of parameters, which is critical for semi-supervised learning where number of labeled examples are small. This in turn allows a room for designing more innovative propagation layers. Based on this insight, we propose a novel graph neural network that removes all the intermediate fully-connected layers, and replaces the propagation layers with attention mechanisms that respect the structure of the graph. The attention mechanism allows us to learn a dynamic and adaptive local summary of the neighborhood to achieve more accurate predictions. In a number of experiments on benchmark citation networks datasets, we demonstrate that our approach outperforms competing methods. By examining the attention weights among neighbors, we show that our model provides some interesting insights on how neighbors influence each other.

stat.ML↗

arXiv2018

Dynamic Game-based Maintenance Scheduling of Integrated Electric and Natural Gas Grids with a Bilevel Approach

This paper proposes a dynamic game-based maintenance scheduling mechanism for the asset owners of the natural gas grid and the power grid by using a bilevel approach. In the upper level, the asset owners of the natural gas grid and the power grid schedule maintenance to maximize their own revenues. This level is modeled as a dynamic game problem, which is solved by the backward induction algorithm. In the lower level, the independent system operator (ISO) dispatches the system to minimize the loss of power load and natural gas load in consideration of the system operating conditions under maintenance plans from the asset owners in the upper level. This is modeled as a mixed integer linear programming problem. For the model of the natural gas grid, a piecewise linear approximation associated with the big-M approach is used to transform the original nonlinear model into the mixed integer linear model. Numerical tests on a 6-bus system with a 4-node gas grid show the effectiveness of the proposed model.

math.OC↗

arXiv2018

Topo-fermiology

The modern semiclassical theory of a Bloch electron in a magnetic field now encompasses the orbital magnetic moment and the geometric phase. These two notions are encoded in the Bohr-Sommerfeld quantization condition as a phase ($λ$) that is subleading in powers of the field; $λ$ is measurable in the phase offset of the de Haas-van Alphen oscillation, as well as of fixed-bias oscillations of the differential conductance in tunneling spectroscopy. In some solids and for certain field orientations, $λ/π$ are robustly integer-valued owing to the symmetry of the extremal orbit, i.e., they are the topological invariants of magnetotransport. Our comprehensive symmetry analysis identifies solids in any (magnetic) space group for which $λ$ is a topological invariant, as well as identifies the symmetry-enforced degeneracy of Landau levels. The analysis is simplified by our formulation of ten (and only ten) symmetry classes for closed, Fermi-surface orbits. Case studies are discussed for graphene, transition metal dichalchogenides, 3D Weyl and Dirac metals, and crystalline and $\mathbb{Z}_2$ topological insulators. In particular, we point out that a $π$ phase offset in the fundamental oscillation should \emph{not} be viewed as a smoking gun for a 3D Dirac metal.

cond-mat.mes-hall↗

arXiv2017

Realizing topological surface states in a lower-dimensional flat band

The anomalous surface states of symmetry protected topological (SPT) phases are usually thought to be only possible in conjunction with the higher dimensional topological bulk. However, it has recently been realized that a class of anomalous SPT surface states can be realized in the same dimension if symmetries are allowed to act in a nonlocal fashion. An example is the particle-hole symmetric half filled Landau level, which effectively realizes the anomalous surface state of a 3D chiral Topological Insulator (class AIII). A dual description in terms of Dirac composite fermions has also been discussed. Here we explore generalizations of these constructions to multicomponent quantum Hall states. Our results include a duality mapping of the bilayer case to composite bosons with Kramers degeneracy and the possibility of a particle hole symmetric integer quantum Hall state when the number of components is a multiple of eight. Next, we make a further extension by half filling other classes of topological bands and imposing particle hole symmetry. When applied to time-reversal invariant topological insulators we realize a different chiral class (CII) topological surface state. Notably, half-filling a 3D TI band allows for the realization of the surface of the otherwise inaccessible 4D topological insulator, which supports an anomalous 3D Dirac cone. Surface topological orders equivalent to the 3D Dirac cone (from the global anomaly standpoint) are constructed and connections to Witten's SU(2) anomaly are made. These observations may also be useful for numerical simulations of topological surface states and of Dirac fermions without fermion doubling.

cond-mat.str-el↗

arXiv2017

Topological Order from Disorder and the Quantized Hall Thermal Metal: Possible Applications to the $ν= 5/2$ State

Although numerical studies modeling the quantum hall effect at filling fraction $5/2$ predict either the Pfaffian (Pf) or its particle hole conjugate, the anti-Pfaffian (aPf) state, recent experiments appear to favor a quantized thermal hall conductivity with quantum number $K=5/2$ , rather than the value $K=7/2$ or $K=3/2$ expected for the Pf or aPF state, respectively. While a particle hole symmetric topological order (the PH-Pfaffian) would be consistent with the experiments, this state is believed to be energetically unfavorable in a homogenous system. Here we study the effects of disorder that are assumed to locally nucleate domains of Pf and aPf. When the disorder is relatively weak and the size of domains is relatively large, we find that when the electrical Hall conductance is on the quantized plateau with $σ_{xy} = (5/2)(e^2/h)$, the value of $K$ can be only 7/2 or 3/2, with a possible first-order-like transition between them as the magnetic field is varied. However, for sufficiently strong disorder an intermediate state might appear, which we analyze within a network model of the domain walls. Predominantly, we find a thermal metal phase, where $K$ varies continuously and the longitudinal thermal conductivity is non-zero, while the electrical Hall conductivity remains quantized at $(5/2)e^2/h$. However, in a restricted parameter range we find a thermal insulator with $K=5/2$, a disorder stabilized phase which is adiabatically connected to the PH-Pfaffian. We discuss a possible scenario to rationalize these special values of parameters.

cond-mat.str-el↗

arXiv2017

Deconfined quantum critical points: symmetries and dualities

The deconfined quantum critical point (QCP), separating the Néel and valence bond solid phases in a 2D antiferromagnet, was proposed as an example of $2+1$D criticality fundamentally different from standard Landau-Ginzburg-Wilson-Fisher {criticality}. In this work we present multiple equivalent descriptions of deconfined QCPs, and use these to address the possibility of enlarged emergent symmetries in the low energy limit. The easy-plane deconfined QCP, besides its previously discussed self-duality, is dual to $N_f = 2$ fermionic quantum electrodynamics (QED), which has its own self-duality and hence may have an O(4)$\times Z_2^T$ symmetry. We propose several dualities for the deconfined QCP with ${\mathrm{SU}(2)}$ spin symmetry which together make natural the emergence of a previously suggested $SO(5)$ symmetry rotating the Néel and VBS orders. These emergent symmetries are implemented anomalously. The associated infra-red theories can also be viewed as surface descriptions of 3+1D topological paramagnets, giving further insight into the dualities. We describe a number of numerical tests of these dualities. We also discuss the possibility of "pseudocritical" behavior for deconfined critical points, and the meaning of the dualities and emergent symmetries in such a scenario.

cond-mat.str-el↗

arXiv2017

Giant Enhancement of Intrinsic Spin Hall Conductivity in $β$ Tungsten via Substitutional Doping

A key challenge in manipulating the magnetization in heavy-metal/ferromagnetic bilayers via the spin-orbit torque is to identify materials that exhibit an efficient charge-to-spin current conversion. Ab initio electronic structure calculations reveal that the intrinsic spin Hall conductivity (SHC) for pristine $β$-W is about sixty percent larger than that of $α$-W. More importantly, we demonstrate that the SHC of $β$-W can be enhanced via Ta alloying. This is corroborated by spin Berry curvature calculations of W$_{1-x}$Ta$_x$ ($x$ $\sim$ 12.5%) alloys which show a giant enhancement of spin Hall angle of up to $\approx$ $-0.5$. The underlying mechanism is the synergistic behavior of the SHC and longitudinal conductivity with Fermi level position. These findings, not only pave the way for enhancing the intrinsic spin Hall effect in $β$-W, but also provide new guidelines to exploit substitutional alloying to tailor the spin Hall effect in various materials.

cond-mat.mtrl-sci↗

arXiv2017

Bubble Assemblies in Ternary Systems with Long Range Interaction

A nonlocal diffuse interface model is used to study bubble assemblies in ternary systems. As model parameters vary, a large number of morphological phases appear as stable stationary states. One open question related to the polarity direction of double bubble assemblies is answered numerically. Moreover, the average size of bubbles in a single bubble assembly depends on the sum of the minority constituent areas and the long range interaction coefficients. One identifies the ranges for area fractions and the long range interaction coefficients for double bubble assemblies.

cond-mat.soft↗

arXiv2017

Adaptive inversion algorithm for 1.5 um visibility lidar incorporating in situ Angstrom wavelength exponent

As one of the most popular applications of lidar systems, the atmospheric visibility is defined to be inversely proportional to the atmospheric extinction coefficient at 0.55 um. Since the laser at 1.5 um shows the highest maximum permissible exposure in the wavelength ranging from 0.3 um to 10 um, the eye-safe 1.5 um lidar can be deployed in urban areas. In such a case, the measured extinction coefficient at 1.5 um should be converted to that at 0.55 um for visibility retrieval. Although several models have been established since 1962, the accurate wavelength conversion remains a challenge. An adaptive inversion algorithm for 1.5 um visibility lidar is proposed and demonstrated by using the in situ Angstrom wavelength exponent, which is derived from either a sun photometer or an aerosol spectrometer. The impact of the particle size distribution of atmospheric aerosols and the Rayleigh backscattering of atmospheric molecules are taken into account. In comparison, the Angstrom wavelength exponent derived from the sun photometer is 7.7% higher than that derived from the aerosol spectrometer. Then, using 1.5 um visibility lidar, the visibility with a temporal resolution of 5 min is detected over 48 hours in Hefei (31.83 N, 117.25 E). The average visibility error between the new method and a visibility sensor (Vaisala, PWD52) is 5.2% with the R-square value of 0.96, while the relative error between another reference visibility lidar at 532 nm and the visibility sensor is 6.7% with the R-square value of 0.91. All results agree with each other well, demonstrating the accuracy and stability of the algorithm.

physics.ao-ph↗

arXiv2017

Largely tunable band structures of few-layer InSe by uniaxial strain

Due to the strong quantum confinement effect, few-layer γ-InSe exhibits a layer-dependent bandgap, spanning the visible and near infrared regions, and thus recently draws tremendous attention. As a two-dimensional material, the mechanical flexibility provides an additional tuning knob for the electronic structure. Here, for the first time, we engineer the band structures of few-layer and bulk-like InSe by uniaxial tensile strain, and observe salient shift of photoluminescence (PL) peaks. The shift rate of the optical gap is approximately 90-100 meV per 1% strain for 4- to 8-layer samples, which is much larger than that for the widely studied MoS2 monolayer. Density functional calculations well reproduce the observed layer-dependent bandgaps and the strain effect, and reveal that the shift rate decreases with increasing layer number for few-layer InSe. Our study demonstrates that InSe is a very versatile 2D electronic and optoelectronic material, which is suitable for tunable light emitters, photo-detectors and other optoelectronic devices.

cond-mat.mes-hall↗

arXiv2017

Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification

Knowledge distillation is a potential solution for model compression. The idea is to make a small student network imitate the target of a large teacher network, then the student network can be competitive to the teacher one. Most previous studies focus on model distillation in the classification task, where they propose different architects and initializations for the student network. However, only the classification task is not enough, and other related tasks such as regression and retrieval are barely considered. To solve the problem, in this paper, we take face recognition as a breaking point and propose model distillation with knowledge transfer from face classification to alignment and verification. By selecting appropriate initializations and targets in the knowledge transfer, the distillation can be easier in non-classification tasks. Experiments on the CelebA and CASIA-WebFace datasets demonstrate that the student network can be competitive to the teacher one in alignment and verification, and even surpasses the teacher network under specific compression rates. In addition, to achieve stronger knowledge transfer, we also use a common initialization trick to improve the distillation performance of classification. Evaluations on the CASIA-Webface and large-scale MS-Celeb-1M datasets show the effectiveness of this simple trick.

cs.CV↗

arXiv2017

How to Train Triplet Networks with 100K Identities?

Training triplet networks with large-scale data is challenging in face recognition. Due to the number of possible triplets explodes with the number of samples, previous studies adopt the online hard negative mining(OHNM) to handle it. However, as the number of identities becomes extremely large, the training will suffer from bad local minima because effective hard triplets are difficult to be found. To solve the problem, in this paper, we propose training triplet networks with subspace learning, which splits the space of all identities into subspaces consisting of only similar identities. Combined with the batch OHNM, hard triplets can be found much easier. Experiments on the large-scale MS-Celeb-1M challenge with 100K identities demonstrate that the proposed method can largely improve the performance. In addition, to deal with heavy noise and large-scale retrieval, we also make some efforts on robust noise removing and efficient image retrieval, which are used jointly with the subspace learning to obtain the state-of-the-art performance on the MS-Celeb-1M competition (without external data in Challenge1).

cs.CV↗

arXiv2017

Observation of Unusual Magnetoelastic Effects in a Quasi-1D Spiral Magnet

We present a systematic study of spin and lattice dynamics in the quasi-one-dimensional spiral magnet CuBr2, using Raman scattering in conjunction with infrared and neutron spectroscopy. Along with the development of spin correlations upon cooling, we observe a rich set of broad Raman bands at energies that correspond to phonon-dispersion energies near the one-dimensional magnetic wave vector. The low-energy bands further exhibit a distinct intensity maximum at the spiral magnetic ordering temperature. We attribute these unusual observations to two possible underlying mechanisms: (1) formation of hybrid spin-lattice excitations, and/or (2) "quadrumerization" of the lattice caused by spin-singlet entanglement in competition with the spiral magnetism.

cond-mat.str-el↗

arXiv2017

Particle-Hole Symmetry in the Fermion-Chern-Simons and Dirac Descriptions of a Half-Filled Landau Level

It is well known that there is a particle-hole symmetry for spin-polarized electrons with two-body interactions in a partially filled Landau level, which becomes exact in the limit where the cyclotron energy is large compared to the interaction strength, so one can ignore mixing between Landau levels. This symmetry is explicit in the description of a half-filled Landau level recently introduced by D. T. Son, using Dirac fermions, but it was thought to be absent in the older fermion-Chern- Simons approach, developed by Halperin, Lee, and Read and subsequent authors. We show here, however, that when properly evaluated, the Halperin, Lee, Read (HLR) theory gives results for long-wavelength low-energy physical properties, including the Hall conductance in the presence of impurities and the positions of minima in the magnetoroton spectra for fractional quantized Hall states close to half-filling, that are identical to predictions of the Dirac formulation. In fact, the HLR theory predicts an emergent particle-hole symmetry near half filling, even when the cyclotron energy is finite.

cond-mat.str-el↗

arXiv2017

Scaffolding Networks: Incremental Learning and Teaching Through Questioning

We introduce a new paradigm of learning for reasoning, understanding, and prediction, as well as the scaffolding network to implement this paradigm. The scaffolding network embodies an incremental learning approach that is formulated as a teacher-student network architecture to teach machines how to understand text and do reasoning. The key to our computational scaffolding approach is the interactions between the teacher and the student through sequential questioning. The student observes each sentence in the text incrementally, and it uses an attention-based neural net to discover and register the key information in relation to its current memory. Meanwhile, the teacher asks questions about the observed text, and the student network gets rewarded by correctly answering these questions. The entire network is updated continually using reinforcement learning. Our experimental results on synthetic and real datasets show that the scaffolding network not only outperforms state-of-the-art methods but also learns to do reasoning in a scalable way even with little human generated input.

cs.CL↗

arXiv2017

Emergent particle-hole symmetry in spinful bosonic quantum Hall systems

When a fermionic quantum Hall system is projected into the lowest Landau level, there is an exact particle-hole symmetry between filling fractions $ν$ and $1-ν$. We investigate whether a similar symmetry can emerge in bosonic quantum Hall states, where it would connect states at filling fractions $ν$ and $2-ν$. We begin by showing that the particle-hole conjugate to a composite fermion `Jain state' is another Jain state, obtained by reverse flux attachment. We show how information such as the shift and the edge theory can be obtained for states which are particle-hole conjugates. Using the techniques of exact diagonalization and infinite density matrix renormalization group, we study a system of two-component (i.e., spinful) bosons, interacting via a $δ$-function potential. We first obtain real-space entanglement spectra for the bosonic integer quantum Hall effect at $ν=2$, which plays the role of a filled Landau level for the bosonic system. We then show that at $ν=4/3$ the system is described by a Jain state which is the particle-hole conjugate of the Halperin (221) state at $ν=2/3$. We show a similar relationship between non-singlet states at $ν=1/2$ and $ν=3/2$. We also study the case of $ν=1$, providing unambiguous evidence that the ground state is a composite Fermi liquid. Taken together our results demonstrate that there is indeed an emergent particle-hole symmetry in bosonic quantum Hall systems.

cond-mat.str-el↗