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Ke Wang

Publications and source records attributed to Ke Wang.

At least 505 records · Page 28Linked to original sources
arXiv2021

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- IV. Radio Recombination Lines and evolution of star formation efficiencies

We report detection of radio recombination line (RRL) H$_{40α}$ toward 75 sources, with data obtained from ACA observations in the ATOMS survey of 146 active Galactic star forming regions. We calculated ionized gas mass and star formation rate with H40U line emission. The mass of ionized gas is significantly smaller than molecular gas mass, indicating that ionized gas is negligible in the star forming clumps of the ATOMS sample. The star formation rate (SFR$_{{\rm H}_{40α}}$) estimated with RRL H$_{40α}$ agrees well with that (SFR$_{\rm L_{bol}}$) calculated with the total bolometric luminosity (L$_{\rm bol}$) when SFR $\gtrsim 5 {\rm M_\odot My}r^{-1}$, suggesting that millimeter RRLs could well sample the upper part of the initial mass function (IMF) and thus be good tracers for SFR. We also study the relationships between L$_{\rm bol}$ and the molecular line luminosities (L0mol) of CS J=2-1 and HC$_3$N J=11-10 for all the 146 ATOMS sources. The Lbol-L0mol correlations of both the CS J=2-1 and HC3N J=11-10 lines appear approximately linear and these transitions have success in predicting L$_{\rm bol}$ similar to that of more commonly used transitions. The L$_{\rm bol}$-to-L$_{\rm mol}$ ratios or SFR-to-mass ratios (star formation efficiency; SFE) do not change with galactocentric distances (R$_{\rm GC}$). Sources with H$_{40α}$ emission (or H$_{\rm II}$ regions) show higher L$_{\rm bol}$-to-L$_{\rm mol}$ than those without H$_{40α}$ emission, which may be an evolutionary effect.

astro-ph.GA↗
arXiv2021

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- VI. On the formation of the "L" type filament in G286.21+0.17

Filaments play an important role in star formation, but the formation process of filaments themselves is still unclear. The high-mass star forming clump G286.21+0.17 (G286 for short) that contains an "L" type filament was thought to undergo global collapse. Our high resolution ALMA band 3 observations resolve the gas kinematics of G286 and reveal two sub-clumps with very different velocities inside it. We find that the "blue profile" (an indicator of gas infall) of HCO+ lines in single dish observations of G286 is actually caused by gas emission from the two sub-clumps rather than gas infall. We advise great caution in interpreting gas kinematics (e.g., infall) from line profiles toward distant massive clumps in single dish observations. Energetic outflows are identified in G286 but the outflows are not strong enough to drive expansion of the two sub-clumps. The two parts of the "L" type filament ("NW-SE" and "NE-SW" filaments) show prominent velocity gradients perpendicular to their major axes, indicating that they are likely formed due to large-scale compression flows. We argue that the large-scale compression flows could be induced by the expansion of nearby giant HII regions. The "NW-SE" and "NE-SW" filaments seem to be in collision, and a large amount of gas has been accumulated in the junction region where the most massive core G286c1 forms.

astro-ph.GA↗
arXiv2021

Fast Online Optimization for Terrain-Blind Bipedal Robot Walking with a Decoupled Actuated SLIP Model

We present a highly reactive controller which enables bipedal robots to blindly walk over various kinds of uneven terrains while resisting pushes. The high level motion planner does fast online optimization for footstep locations and Center of Mass (CoM) height using the decoupled actuated Spring Loaded Inverted Pendulum (aSLIP) model. The decoupled aSLIP model simplifies the original aSLIP with Linear Inverted Pendulum (LIP) dynamics in horizontal states and spring dynamics in the vertical state. The motion planning can be formulated as a discrete-time Model Predictive Control (MPC) and solved at a frequency of 1k~HZ. The output of the motion planner using a reduced-order model is fed into an inverse-dynamics based whole body controller for execution on the robot. A key result of this controller is that the foot of the robot is compliant, which further extends the robot's ability to be robust to unobserved terrain changes. We evaluate our method in simulation with the bipedal robot SLIDER. Results show the robot can blindly walk over various uneven terrains including slopes, wave fields and stairs. It can also resist pushes while walking on uneven terrain.

cs.RO↗
arXiv2021

Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting and Regularization

Deep neural networks generalize well despite being exceedingly overparameterized and being trained without explicit regularization. This curious phenomenon has inspired extensive research activity in establishing its statistical principles: Under what conditions is it observed? How do these depend on the data and on the training algorithm? When does regularization benefit generalization? While such questions remain wide open for deep neural nets, recent works have attempted gaining insights by studying simpler, often linear, models. Our paper contributes to this growing line of work by examining binary linear classification under a generative Gaussian mixture model. Motivated by recent results on the implicit bias of gradient descent, we study both max-margin SVM classifiers (corresponding to logistic loss) and min-norm interpolating classifiers (corresponding to least-squares loss). First, we leverage an idea introduced in [V. Muthukumar et al., arXiv:2005.08054, (2020)] to relate the SVM solution to the min-norm interpolating solution. Second, we derive novel non-asymptotic bounds on the classification error of the latter. Combining the two, we present novel sufficient conditions on the covariance spectrum and on the signal-to-noise ratio (SNR) under which interpolating estimators achieve asymptotically optimal performance as overparameterization increases. Interestingly, our results extend to a noisy model with constant probability noise flips. Contrary to previously studied discriminative data models, our results emphasize the crucial role of the SNR and its interplay with the data covariance. Finally, via a combination of analytical arguments and numerical demonstrations we identify conditions under which the interpolating estimator performs better than corresponding regularized estimates.

stat.ML↗
arXiv2021

Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation

Quality Estimation (QE) plays an essential role in applications of Machine Translation (MT). Traditionally, a QE system accepts the original source text and translation from a black-box MT system as input. Recently, a few studies indicate that as a by-product of translation, QE benefits from the model and training data's information of the MT system where the translations come from, and it is called the "glass-box QE". In this paper, we extend the definition of "glass-box QE" generally to uncertainty quantification with both "black-box" and "glass-box" approaches and design several features deduced from them to blaze a new trial in improving QE's performance. We propose a framework to fuse the feature engineering of uncertainty quantification into a pre-trained cross-lingual language model to predict the translation quality. Experiment results show that our method achieves state-of-the-art performances on the datasets of WMT 2020 QE shared task.

cs.CL↗
arXiv2021

Observation of a symmetry-protected topological time crystal with superconducting qubits

We report the observation of a symmetry-protected topological time crystal, which is implemented with an array of programmable superconducting qubits. Unlike the time crystals reported in previous experiments, where spontaneous breaking of the discrete time translational symmetry occurs for local observables throughout the whole system, the topological time crystal observed in our experiment breaks the time translational symmetry only at the boundaries and has trivial dynamics in the bulk. More concretely, we observe robust long-lived temporal correlations and sub-harmonic temporal response for the edge spins up to 40 driving cycles. We demonstrate that the sub-harmonic response is independent of whether the initial states are random product states or symmetry-protected topological states, and experimentally map out the phase boundary between the time crystalline and thermal phases. Our work paves the way to exploring peculiar non-equilibrium phases of matter emerged from the interplay between topology and localization as well as periodic driving, with current noisy intermediate-scale quantum processors.

quant-ph↗
arXiv2021

A Unified Model with Inertia Shaping for Highly Dynamic Jumps of Legged Robots

To achieve highly dynamic jumps of legged robots, it is essential to control the rotational dynamics of the robot. In this paper, we aim to improve the jumping performance by proposing a unified model for planning highly dynamic jumps that can approximately model the centroidal inertia. This model abstracts the robot as a single rigid body for the base and point masses for the legs. The model is called the Lump Leg Single Rigid Body Model (LL-SRBM) and can be used to plan motions for both bipedal and quadrupedal robots. By taking the effects of leg dynamics into account, LL-SRBM provides a computationally efficient way for the motion planner to change the centroidal inertia of the robot with various leg configurations. Concurrently, we propose a novel contact detection method by using the norm of the average spatial velocity. After the contact is detected, the controller is switched to force control to achieve a soft landing. Twisting jump and forward jump experiments on the bipedal robot SLIDER and quadrupedal robot ANYmal demonstrate the improved jump performance by actively changing the centroidal inertia. These experiments also show the generalization and the robustness of the integrated planning and control framework.

cs.RO↗
arXiv2021

Multi-step stochastic mechanism of polarization reversal in orthorhombic ferroelectrics

A stochastic model of electric field-driven polarization reversal in orthorhombic ferroelectrics is advanced, providing a description of their temporal electromechanical response. The theory accounts for all possible parallel and sequential switching events. Application of the model to the simultaneous measurements of polarization and strain kinetics in a lead-free orthorhombic (K,Na)NbO3-based ferroelectric ceramic over a wide timescale of 7 orders of magnitude allowed identification of preferable polarization switching paths, fractions of individual switching processes, and their activation fields. Particularly, the analysis revealed substantial contributions of coherent non-180° switching events, which do not cause macroscopic strain and thus mimic 180° switching processes.

cond-mat.mtrl-sci↗
arXiv2021

High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss

Purpose: To improve reconstruction fidelity of fine structures and textures in deep learning (DL) based reconstructions. Methods: A novel patch-based Unsupervised Feature Loss (UFLoss) is proposed and incorporated into the training of DL-based reconstruction frameworks in order to preserve perceptual similarity and high-order statistics. The UFLoss provides instance-level discrimination by mapping similar instances to similar low-dimensional feature vectors and is trained without any human annotation. By adding an additional loss function on the low-dimensional feature space during training, the reconstruction frameworks from under-sampled or corrupted data can reproduce more realistic images that are closer to the original with finer textures, sharper edges, and improved overall image quality. The performance of the proposed UFLoss is demonstrated on unrolled networks for accelerated 2D and 3D knee MRI reconstruction with retrospective under-sampling. Quantitative metrics including NRMSE, SSIM, and our proposed UFLoss were used to evaluate the performance of the proposed method and compare it with others. Results: In-vivo experiments indicate that adding the UFLoss encourages sharper edges and more faithful contrasts compared to traditional and learning-based methods with pure l2 loss. More detailed textures can be seen in both 2D and 3D knee MR images. Quantitative results indicate that reconstruction with UFLoss can provide comparable NRMSE and a higher SSIM while achieving a much lower UFLoss value. Conclusion: We present UFLoss, a patch-based unsupervised learned feature loss, which allows the training of DL-based reconstruction to obtain more detailed texture, finer features, and sharper edges with higher overall image quality under DL-based reconstruction frameworks.

eess.IV↗
arXiv2021

Constraints on Multicomponent Dark Energy from Cosmological Observations

Dark energy (DE) plays an important role in the expansion history of our universe. But we only got limited knowledge about its nature and properties after decades of study.In most numerical researches, DE is usually considered as a dynamical whole. Actually, multicomponent DE models can also explain the accelerating expansion of our universe, which is accepted theoretically but lack of numerical researches. We try to study the multicomponent DE models from observation by constructing $w_n$CDM models. The total energy density of DE is separated into $n$ ($n=2,3,5$) parts equally and every part has a constant EOS $w_i$ ($i=1,2...n$). We modify the Friedmann equation and the parameterized post-Friedmann description of DE, then put constraints on $w_i$s from Planck 2018 TT,TE,EE$+$lowE$+$lensing, BAO data and PANTHEON samples. The multicomponent DE models are favoured if any $w_n$CDM model is preferred by observational data and there is no overlap between the highest and lowest values of $w_i$s. We find the data combination supports the $w_n$CDM model when $n$ is small and the $w_2$CDM model is slightly preferred by $Δχ^2_{\text{min}} = Δ\text{AIC} =Δ\text{BIC} = -2.48$ over the CPL model, but the largest value of $w_i$ overlaps the smallest one. With larger $n$, the maximum and minimum of $w_i$s do not overlap with each other, but $χ^2_{\text{min}}$ and AIC also increase. In brief, we find no obvious evidence that DE is composed of different components.

astro-ph.CO↗
arXiv2021

Planck Galactic Cold Clumps at High Galactic Latitude-A Study with CO Lines

Gas at high Galactic latitude is a relatively little-noticed component of the interstellar medium. In an effort to address this, forty-one Planck Galactic Cold Clumps at high Galactic latitude (HGal; $|b|>25^{\circ}$) were observed in $^{12}$CO, $^{13}$CO and C$^{18}$O J=1-0 lines, using the Purple Mountain Observatory 13.7-m telescope. $^{12}$CO (1-0) and $^{13}$CO (1-0) emission was detected in all clumps while C$^{18}$O (1-0) emission was only seen in sixteen clumps. The highest and average latitudes are $71.4^{\circ}$ and $37.8^{\circ}$, respectively. Fifty-one velocity components were obtained and then each was identified as a single clump. Thirty-three clumps were further mapped at 1$^\prime$ resolution and 54 dense cores were extracted. Among dense cores, the average excitation temperature $T_{\mathrm{ex}}$ of $^{12}$CO is 10.3 K. The average line widths of thermal and non-thermal velocity dispersions are $0.19$ km s$^{-1}$ and $0.46$ km s$^{-1}$ respectively, suggesting that these cores are dominated by turbulence. Distances of the HGal clumps given by Gaia dust reddening are about $120-360$ pc. The ratio of $X_{13}$/$X_{18}$ is significantly higher than that in the solar neighbourhood, implying that HGal gas has a different star formation history compared to the gas in the Galactic disk. HGal cores with sizes from $0.01-0.1$ pc show no notable Larson's relation and the turbulence remains supersonic down to a scale of slightly below $0.1$ pc. None of the HGal cores which bear masses from 0.01-1 $M_{\odot}$ are gravitationally bound and all appear to be confined by outer pressure.

astro-ph.GA↗
arXiv2021

Combating fake news by empowering fact-checked news spread via topology-based interventions

Rapid information diffusion and large-scaled information cascades can enable the undesired spread of false information. A small-scaled false information outbreak may potentially lead to an infodemic. We propose a novel information diffusion and intervention technique to combat the spread of false news. As false information is often spreading faster in a social network, the proposed diffusion methodology inhibits the spread of false news by proactively diffusing the fact-checked information. Our methodology mainly relies on defining the potential super-spreaders in a social network based on their centrality metrics. We run an extensive set of experiments on different networks to investigate the impact of centrality metrics on the performance of the proposed diffusion and intervention models. The obtained results demonstrate that empowering the diffusion of fact-checked news combats the spread of false news further and deeper in social networks.

cs.SI↗
arXiv2021

Efficient Byzantine Fault Tolerance using Trusted Execution Environment: Preventing Equivocation is only the Beginning

With the rapid development of blockchain, Byzantine fault-tolerant protocols have attracted revived interest recently. To overcome the theoretical bounds of Byzantine fault tolerance, many protocols attempt to use Trusted Execution Environment (TEE) to prevent equivocation and improve performance and scalability. However, due to the broken quorum intersection assumption caused by the reduction of the replica number, the improvement is mostly at the cost of increased communication complexity which prevents existing TEE-based protocols to be applied to large-scale blockchain systems. In this paper, we propose TBFT, an efficient Byzantine fault-tolerant protocol in the partial synchrony setting, which has O(n) message complexity in both normal-case and view-change. Compared to previous protocols, TBFT uses TEE-assisted primitives to limit more types of malicious behaviors of replicas rather than preventing equivocation only, thereby reducing the latency and communication complexity of clients and replicas. Besides, we also introduce lightweight cryptographic primitives including a novel leader election mechanism and an efficient voting message aggregation mechanism for better security and performance. We evaluate TBFT via systematic analysis and experiments, and the results show that TBFT has better performance and scalability compared to other protocols.

cs.DC↗
arXiv2021

An ALMA study of outflow parameters of protoclusters: outflow feedback to maintain the turbulence

With the aim of understanding the role of outflows in star formation, we performed a statistical study of the physical parameters of outflows in eleven massive protoclusters associated with ultra-compact HII regions. A total of 106 outflow lobes are identified in these protoclusters using the ALMA CO (3-2), HCN (4-3) and HCO+ (4-3) line observations. Although the position angles of outflow lobes do not differ in these three tracers, HCN and HCO+ tend to detect lower terminal velocity of the identified outflows compared to CO. The majority of the outflows in our targets are young with typical dynamical time-scales of 10^2-10^4 years, and are mostly composed of low-mass outflows along with at least one high-mass outflow in each target. An anti-correlation of outflow rate with dynamical time-scale indicates that the outflow rate possibly decreases with time. Also, a rising trend of dynamical time-scale with the mass of the associated core hints that the massive cores might have longer accretion histories than the low mass cores. Estimation of different energies in these protoclusters shows that outflows studied here cannot account for the generation of the observed turbulence, but can sustain the turbulence at the current epoch as the energy injection rate from the outflows is similar to the estimated dissipation rate.

astro-ph.GA↗
arXiv2021

Even-Odd Layer-Dependent Anomalous Hall Effect in Topological Magnet MnBi2Te4 Thin Films

A central theme in condensed matter physics is to create and understand the exotic states of matter by incorporating magnetism into topological materials. One prime example is the quantum anomalous Hall (QAH) state. Recently, MnBi2Te4 has been demonstrated to be an intrinsic magnetic topological insulator and the QAH effect was observed in exfoliated MnBi2Te4 flakes. Here, we used molecular beam epitaxy (MBE) to grow MnBi2Te4 films with thickness down to 1 septuple layer (SL) and performed thickness-dependent transport measurements. We observed a non-square hysteresis loop in the antiferromagnetic state for films with thickness greater than 2 SL. The hysteresis loop can be separated into two AH components. Through careful analysis, we demonstrated that one AH component with the larger coercive field is from the dominant MnBi2Te4 phase, while the other AH component with the smaller coercive field is from the minor Mn-doped Bi2Te3 phase in the samples. The extracted AH component of the MnBi2Te4 phase shows a clear even-odd layer-dependent behavior, a signature of antiferromagnetic thin films. Our studies reveal insights on how to optimize the MBE growth conditions to improve the quality of MnBi2Te4 films, in which the QAH and other exotic states are predicted.

cond-mat.mtrl-sci↗
arXiv2021

On a Class of Nonlocal SIR Models

We revisit the classic Susceptible-Infected-Recovered (SIR) epidemic model and one of its nonlocal variations recently developed in \cite{Guan}. We introduce several new approaches to derive exact analytical solutions in the classical situation and analyze the corresponding effective approximations in the nonlocal setting. An interesting new feature of the nonlocal models, compared with the classic SIR model, is the appearance of multiple peak solutions for the infected population. We provide several rigorous results on the existence and non-existence of peak solutions with sharp asymptotics.

math.AP↗
arXiv2021

Gate-tunable Veselago Interference in a Bipolar Graphene Microcavity

The relativistic charge carriers in monolayer graphene can be manipulated in manners akin to conventional optics (electron-optics): angle-dependent Klein tunneling collimates an electron beam (analogous to a laser), while a Veselago refraction process focuses it (analogous to an optical lens). Both processes have been previously investigated, but the collimation and focusing efficiency have been reported to be relatively low even in state-of-the-art ballistic pn-junction devices. These limitations prevented the realization of more advanced quantum devices based on electron-optical interference, while understanding of the underlying physics remains elusive. Here, we present a novel device architecture of a graphene microcavity defined by carefully-engineered local strain and electrostatic fields. We create a controlled electron-optic interference process at zero magnetic field as a consequence of consecutive Veselago refractions in the microcavity and provide direct experimental evidence through low-temperature electrical transport measurements. The experimentally observed first-, second-, and third-order interference peaks agree quantitatively with the Veselago physics in a microcavity. In addition, we demonstrate decoherence of the interference by an external magnetic field, as the cyclotron radius becomes comparable to the interference length scale. For its application in electron-optics, we utilize Veselago interference to localize uncollimated electrons and characterize its contribution in further improving collimation efficiency. Our work sheds new light on relativistic single-particle physics and provides important technical improvements toward next-generation quantum devices based on the coherent manipulation of electron momentum and trajectory.

cond-mat.mes-hall↗