arXiv subjects

Cheng Peng

Publications and source records attributed to Cheng Peng.

At least 217 records · Page 12Linked to original sources

arXiv2019

Dynamic exciton funneling by local strain control in a monolayer semiconductor

The ability to control excitons in semiconductors underlies numerous proposed applications, from excitonic circuits for computing and communications to polariton condensates to energy transport in photovoltaics. 2D semiconductors are particularly promising for room-temperature applications due to their large exciton binding energy. Their enormous stretchability gives rise to a strain-engineerable bandgap that has been used to induce static exciton flux in predetermined structures. However, dynamic control of exciton flux represents an outstanding challenge. Here, we introduce a method to tune the bandgap of suspended 2D semiconductors by applying a local strain gradient with a nanoscale tip. This strain allows us to locally and reversibly shift the exciton energy and to steer the exciton flux over micron-scale distances, as observed by wide-field imaging and time-resolved photoluminescence spectroscopy. We anticipate that the ability to strongly and dynamically modulate the bandgap of a semiconductor at the nanoscale not only marks an important experimental tool but will also open a broad range of new applications from information processing to energy conversion.

cond-mat.mes-hall↗

arXiv2019

A comparative study of immersed boundary method and interpolated bounce-back scheme for no-slip boundary treatment in the lattice Boltzmann method: Part I, laminar flows

The interpolated bounce-back scheme and the immersed boundary method are the two most popular algorithms in treating a no-slip boundary on curved surfaces in the lattice Boltzmann method. While those algorithms are frequently implemented in the numerical simulations involving complex geometries, such as particle-laden flows, their performances are seldom compared systematically over the same local quantities within the same context. In this paper, we present a systematic comparative investigation on some frequently used and most state-of-the-art interpolated bounce-back schemes and immersed boundary methods, based on both theoretical analyses and numerical simulations of four selected 2D and 3D laminar flow problems. Our analyses show that immersed boundary methods (IBM) typically yield a first-order accuracy when the regularized delta-function is employed to interpolate velocity from the Eulerian to Lagrangian mesh, and the resulting boundary force back to the Eulerian mesh. This first order in accuracy for IBM is observed for both the local velocity and hydrodynamic force/torque, apparently different from the second-order accuracy sometimes claimed in the literature. Another serious problem of immersed boundary methods is that the local stress within the diffused fluid-solid interface tends to be significantly underestimated. On the other hand, the interpolated bounce-back generally possesses a second-order accuracy for velocity, hydrodynamic force/torque, and local stress field. The main disadvantage of the interpolated bounce-back schemes is its higher level of fluctuations in the calculated hydrodynamic force/torque when a solid object moves across the grid lines. General guidelines are also provided for the necessary grid resolutions in the two approaches in order to accurately simulate flows over a solid particle.

physics.comp-ph↗

arXiv2019

A comparative study of immersed boundary method and interpolated bounce-back scheme for no-slip boundary treatment in the lattice Boltzmann method: Part II, turbulent flows

In the first part of this study, we compared the performances of two categories of no-slip boundary treatments, i.e., the interpolated bounce-back schemes and the immersed boundary methods in a series of laminar flow simulations within the lattice Boltzmann method. In this second part, these boundary treatments are further compared in the simulations of turbulent flows with complex geometry to provide a next-level assessment of these schemes. Two non-trivial turbulent flow problems, a fully developed turbulent pipe flow at a low Reynolds number, and a decaying homogeneous isotropic turbulent flow laden with a large number of resolved spherical particles are considered. The major problem of the immersed boundary method revealed by the present study is its incapability in computing the local velocity gradients inside the diffused interface, which can result in significantly underestimated dissipation rate and viscous diffusion locally near the particle surfaces. Otherwise, both categories of the no-slip boundary treatments are able to provide accurate results for most of turbulent statistics in both the carrier and dispersed phases, provided that sufficient grid resolutions are used.

physics.comp-ph↗

arXiv2019

Isotropy and spurious currents in pseudo-potential multiphase lattice Boltzmann models

The spurious currents observed in multiphase flow simulations with pseudo-potential lattice Boltzmann (LB) models are usually understood to be the result of the lack of isotropy of the model-generated interaction force between phases. Remedies have been proposed to utilize larger stencils to compute the interaction force with higher orders of isotropy. In this short communication, we point out the incompleteness in the current understanding and propose a new consistent implementation to more effectively suppress the spurious currents. We also demonstrate theoretically that certain low-level spurious currents cannot be eliminated by increasing isotropy if the local hydrostatic balance inside the diffuse interface is not established in the LB models.

physics.comp-ph↗

arXiv2019

Efficient Quantum Simulation for Thermodynamics of Infinite-size Many-body Systems in Arbitrary Dimensions

In this work we propose to simulate many-body thermodynamics of infinite-size quantum lattice models in one, two, and three dimensions, in terms of few-body models of only O(10) sites, which we coin as quantum entanglement simulators (QES's). The QES is described by a temperature-independent Hamiltonian, with the boundary interactions optimized by the tensor network methods to mimic the entanglement between the bulk and environment in a finite-size canonical ensemble. The reduced density matrix of the physical bulk then gives that of the infinite-size canonical ensemble under interest. We show that the QES can, for instance, accurately simulate varieties of many-body phenomena, including finite-temperature crossover and algebraic excitations of the one-dimensional spin liquid, the phase transitions and low-temperature physics of the two- and three-dimensional antiferromagnets, and the crossovers of the two-dimensional topological system. Our work provides an efficient way to explore the thermodynamics of intractable quantum many-body systems with easily accessible systems.

cond-mat.str-el↗

arXiv2019

Generative Tensor Network Classification Model for Supervised Machine Learning

Tensor network (TN) has recently triggered extensive interests in developing machine-learning models in quantum many-body Hilbert space. Here we purpose a generative TN classification (GTNC) approach for supervised learning. The strategy is to train the generative TN for each class of the samples to construct the classifiers. The classification is implemented by comparing the distance in the many-body Hilbert space. The numerical experiments by GTNC show impressive performance on the MNIST and Fashion-MNIST dataset. The testing accuracy is competitive to the state-of-the-art convolutional neural network while higher than the naive Bayes classifier (a generative classifier) and support vector machine. Moreover, GTNC is more efficient than the existing TN models that are in general discriminative. By investigating the distances in the many-body Hilbert space, we find that (a) the samples are naturally clustering in such a space; and (b) bounding the bond dimensions of the TN's to finite values corresponds to removing redundant information in the image recognition. These two characters make GTNC an adaptive and universal model of excellent performance.

cs.LG↗

arXiv2019

Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure

The resemblance between the methods used in quantum-many body physics and in machine learning has drawn considerable attention. In particular, tensor networks (TNs) and deep learning architectures bear striking similarities to the extent that TNs can be used for machine learning. Previous results used one-dimensional TNs in image recognition, showing limited scalability and flexibilities. In this work, we train two-dimensional hierarchical TNs to solve image recognition problems, using a training algorithm derived from the multi-scale entanglement renormalization ansatz. This approach introduces mathematical connections among quantum many-body physics, quantum information theory, and machine learning. While keeping the TN unitary in the training phase, TN states are defined, which encode classes of images into quantum many-body states. We study the quantum features of the TN states, including quantum entanglement and fidelity. We find these quantities could be properties that characterize the image classes, as well as the machine learning tasks.

stat.ML↗

arXiv2018

Thermodynamics of Spin-1/2 Kagomé Heisenberg Antiferromagnet: Algebraic Paramagnetic Liquid and Finite-Temperature Phase Diagram

Quantum fluctuations from frustration can trigger quantum spin liquids (QSLs) at zero temperature. However, it is unclear how thermal fluctuations affect a QSL. We employ state-of-the-art tensor network-based methods to explore the ground state and thermodynamic properties of the spin-1/2 kagome Heisenberg antiferromagnet (KHA). Its ground state is shown to be consistent with a gapless QSL by observing the absence of zero-magnetization plateau as well as the algebraic behaviors of susceptibility and specific heat at low temperatures, respectively. We show that there exists an \textit{algebraic paramagnetic liquid} (APL) that possesses both the paramagnetic properties and the algebraic behaviors inherited from the QSL. The APL is induced under the interplay between quantum fluctuations from geometrical frustration and thermal fluctuations. By studying the temperature-dependent behaviors of specific heat and magnetic susceptibility, a finite-temperature phase diagram in a magnetic field is suggested, where various phases are identified. This present study gains useful insight into the thermodynamic properties of the spin-1/2 KHA with or without a magnetic field and is helpful for relevant experimental studies.

cond-mat.str-el↗

arXiv2018

Chiral Algebras of Two-Dimensional SYK Models

We study chiral algebras in the $\bar{Q}$-cohomology of two dimensional SYK models with extended supersymmetry. In a special limit discovered in arXiv:1805.09325, we are able to construct explicitly a "vertical" single-particle higher-spin algebra that is bilinear in the fundamental fields. This algebra can be regarded as the counterpart, when going away from criticality, of the infrared emergent higher-spin symmetry of the $\mathcal{N}=(0,2)$ SYK model. Moreover, a second "horizontal" single-particle higher-spin algebra appears in this limit. Together with the vertical algebra they generate a stringy algebra with a "higher spin square" structure that is believed to appear in the tensionless limit of string theory. On the other hand, we do not find single-particle higher-spin algebra away from the special limit, which is consistent with the result in arXiv:1805.09325. Our analysis is carried out for each individual realization of the random couplings and for finite $N$ (and $M$), which in particular indicates that the conclusion in arXiv:1805.09325 is robust to $1/N$ corrections.

hep-th↗

arXiv2018

Bayesian Persuasive Driving

In the autonomous driving area, interaction between vehicles is still a piece of puzzle which has not been fully resolved. The ability to intelligently and safely interact with other vehicles can not only improve self driving quality but also be beneficial to the global driving environment. In this paper, a Bayesian persuasive driving algorithm based on optimization is proposed, where the ego vehicle is the persuader (information sender) and the surrounding vehicle is the persuadee (information receiver). In the persuasion process, the ego vehicle aims at changing the surrounding vehicle's posterior belief of the world state by providing certain information via signaling in order to achieve a lower cost for both players. The information received by the surrounding vehicle and its belief of the world state are described by Gaussian distributions. Simulation results in several common traffic scenarios are provided to demonstrate the proposed algorithm's capability of handling interaction situations involving surrounding vehicles with different driving characteristics.

math.OC↗

arXiv2018

Bond relaxation, electronic and magnetic behavior of 2D metals structures Y on Li(110) surface

We investigated the bond, electronic and magnetic behavior of adsorption Yttrium atoms on Lithium (110) surface using a combination of Bond-order-length-strength(BOLS) correlation and density-functional theory(DFT). We found that adsorption Y atoms on Li(110) surfaces form two-dimensional (2D) geometric structures of hexagon, nonagon, solid hexagonal, quadrangle and triangle. The consistent with the magnetic moment are 6.66μB, 5.54μB, 0.28μB, 1.04μB, 2.81μB, respectively. In addition, this work could pave the way for design new 2D metals electronic and magnetic properties.

cond-mat.mtrl-sci↗

arXiv2018

Controlling phase diagram of finite spin-$1/2$ chains by tuning boundary interactions

Searching for simple models that possess non-trivial controlling properties is one of the central tasks in the field of quantum technologies. In this work, we construct a quantum spin-$1/2$ chain of finite size, termed as controllable spin wire (CSW), in which we have $\hat{S}^{z} \hat{S}^{z}$ (Ising) interactions with a transverse field in the bulk, and $\hat{S}^{x} \hat{S}^{z}$ and $\hat{S}^{z} \hat{S}^{z}$ couplings with a canted field on the boundaries. The Hamiltonians on the boundaries, dubbed as tuning Hamiltonians (TH's), bear the same form as the effective Hamiltonians emerging in the so-called `quantum entanglement simulator' that is originally proposed for mimicking infinite models. We show that tuning the TH's (parametrized by $α$) can trigger non-trivial controlling of the bulk properties, including the degeneracy of energy/entanglement spectra, and the response to the magnetic field $h_{bulk}$ in the bulk. A universal point dubbed as $α^s$ emerges. For $α> α^s$, the ground-state diagram versus $h_{bulk}$ consists of three `phases', which are NeéL and polarized phases, and an emergent pseudo-magnet phase, distinguished by entanglement and magnetization. For $α< α^s$, the phase diagram changes completely, with no step-like behaviors to distinguish phases. Due to its controlling properties and simplicity, the CSW could potentially serve in future the experiments for developing quantum devices.

cond-mat.str-el↗

arXiv2018

Electronic structure and bond relaxation at Na/Ta(110) interfaces and 1D-chain and 2D-ring Ta metal structures on Na(110)

We investigated the mechanism of Na/Ta(110) and Ta/Na(110) interfaces using a combination of bond band barrier (BBB) and zone selective electron spectroscopy (ZES) correlation. We found that 7/9 ML and 8/9 ML Ta metal on a Na(110) surface form one dimensional (1D) chain and two dimensional (2D) ring structures, respectively. Moreover, we show that on Na(110), the Ta-induced Na(110) surface binding energy (BE) shifts are dominated by quantum entrapment. On the contrary, on a Ta(110) surface, the Na-induced Ta(110) surface BE shifts are dominated by polarization. Thus, the BBB and ZES strategy could potentially be used for designing 1D and 2D metals with desired structures and properties.

physics.comp-ph↗

arXiv2018

Twin-plane-partitions and $\mathcal{N}=2$ affine Yangian

The universal enveloping algebra of ${\cal W}_{1+\infty}$ is isomorphic to the affine Yangian of $\mathfrak{gl}_1$. We study the ${\cal N}=2$ supersymmetric version of this correspondence, and identify the full set of defining relations of the supersymmetric affine Yangian. These relations can be deduced by demanding that the algebra has a representation on twin-plane-partitions, which we construct by gluing pairs of plane partitions. We define the action of the algebra on these twin-plane-partitions explicitly.

hep-th↗

arXiv2018

The supersymmetric affine Yangian

The affine Yangian of $\mathfrak{gl}_1$ is known to be isomorphic to ${\cal W}_{1+\infty}$, the $W$-algebra that characterizes the bosonic higher spin -- CFT duality. In this paper we propose defining relations of the Yangian that are relevant for the ${\cal N}=2$ superconformal version of ${\cal W}_{1+\infty}$. Our construction is based on the observation that the ${\cal N}=2$ superconformal ${\cal W}_{1+\infty}$ algebra contains two commuting bosonic ${\cal W}_{1+\infty}$ algebras, and that the additional generators transform in bi-minimal representations with respect to these two algebras. The corresponding affine Yangian can therefore be built up from two affine Yangians of $\mathfrak{gl}_1$ by adding in generators that transform appropriately.

hep-th↗

arXiv2018

$\mathcal{N}=(0,2)$ SYK, Chaos and Higher-Spins

We study a 2-dimensional SYK model with $\mathcal{N}=(0,2)$ supersymmetry. The model describes $N$ chiral supermultiplets and $M$ Fermi supermultiplets with a $(q+1)$-field interaction. We solve the model analytically and numerically in the $N\gg 1$, $M\gg 1$ limit with $μ\equiv \frac{M}{N}$ being a free parameter. Two distinct higher-spin symmetries emerge when the $μ$ parameter approaches the two ends of its range. This is verified by the appearance of conserved higher-spin operators and the vanishing of chaotic behaviors in the two limits. Therefore this model provides a manifest realization of the widely believed connection between SYK-like models and higher-spin theories. In addition, as the parameter $μ$ varies we find the largest Lyapunov exponent of this model to be slightly larger than that in models with non-chiral supersymmetry. A tensor model without random couplings that shares the same infrared physics is also introduced.

hep-th↗

arXiv2018

Probing the Ultimate Plasmon Confinement Limits with a Van der Waals heterostructure

The ability to confine light into tiny spatial dimensions is important for applications such as microscopy, sensing and nanoscale lasers. While plasmons offer an appealing avenue to confine light, Landau damping in metals imposes a trade-off between optical field confinement and losses. We show that a graphene-insulator-metal heterostructure can overcome that trade-off, and demonstrate plasmon confinement down to the ultimate limit of the lengthscale of one atom. This is achieved by far-field excitation of plasmon modes squeezed into an atomically thin hexagonal boron nitride dielectric h-BN spacer between graphene and metal rods. A theoretical model which takes into account the non-local optical response of both graphene and metal is used to describe the results. These ultra-confined plasmonic modes, addressed with far-field light excitation, enables a route to new regimes of ultra-strong light-matter interactions.

cond-mat.mes-hall↗

arXiv2018

View Selection with Geometric Uncertainty Modeling

Estimating positions of world points from features observed in images is a key problem in 3D reconstruction, image mosaicking,simultaneous localization and mapping and structure from motion. We consider a special instance in which there is a dominant ground plane $\mathcal{G}$ viewed from a parallel viewing plane $\mathcal{S}$ above it. Such instances commonly arise, for example, in aerial photography. Consider a world point $g \in \mathcal{G}$ and its worst case reconstruction uncertainty $\varepsilon(g,\mathcal{S})$ obtained by merging \emph{all} possible views of $g$ chosen from $\mathcal{S}$. We first show that one can pick two views $s_p$ and $s_q$ such that the uncertainty $\varepsilon(g,\{s_p,s_q\})$ obtained using only these two views is almost as good as (i.e. within a small constant factor of) $\varepsilon(g,\mathcal{S})$. Next, we extend the result to the entire ground plane $\mathcal{G}$ and show that one can pick a small subset of $\mathcal{S'} \subseteq \mathcal{S}$ (which grows only linearly with the area of $\mathcal{G}$) and still obtain a constant factor approximation, for every point $g \in \mathcal{G}$, to the minimum worst case estimate obtained by merging all views in $\mathcal{S}$. Finally, we present a multi-resolution view selection method which extends our techniques to non-planar scenes. We show that the method can produce rich and accurate dense reconstructions with a small number of views. Our results provide a view selection mechanism with provable performance guarantees which can drastically increase the speed of scene reconstruction algorithms. In addition to theoretical results, we demonstrate their effectiveness in an application where aerial imagery is used for monitoring farms and orchards.

cs.CV↗