arXiv subjects

Chen Wang

Publications and source records attributed to Chen Wang.

At least 793 records · Page 44Linked to original sources

arXiv2017

Steady state current fluctuations and dynamical control in a nonequilibrium single-site Bose-Hubbard system

We investigate nonequilibrium energy transfer in a single-site Bose-Hubbard model coupled to two thermal baths. By including a quantum kinetic equation combined with full counting statistics, we investigate the steady state energy flux and noise power. The influence of the nonlinear Bose-Hubbard interaction on the transfer behaviors is analyzed, and the nonmonotonic features are clearly exhibited. Particularly, in the strong on-site repulsion limit, the results become identical with the nonequilibrium spin-boson model. We also extend the quantum kinetic equation to study the geometric-phase-induced energy pump. An interesting reversal behavior is unraveled by enhancing the Bose-Hubbard repulsion strength.

cond-mat.mes-hall↗

arXiv2017

Negative differential thermal conductance and heat amplification in a nonequilibrium triangle-coupled spin-boson system at strong coupling

We investigate the nonequilibrium quantum heat transfer in a triangle-coupled spin-boson system within a three-terminal setup. By including the nonequilibrium noninteracting blip approximation approach combined with the full counting statistics, we analytically obtain the steady state populations and heat currents. The negative differential thermal conductance and giant heat amplification factor are clearly observed at strong qubit-bath coupling. %and the heat amplification is dramatically suppressed in the moderate coupling regime. Moreover, the strong interaction between the gating qubit and gating thermal bath is unraveled to be compulsory to exhibit these far-from equilibrium features.

cond-mat.mes-hall↗

arXiv2017

Zeno effect of the open quantum system in the presence of 1/f noise

We study the quantum Zeno effect (QZE) and quantum anti-Zeno effect (QAZE) in a two-level system(TLS) interacting with an environment owning 1/f noise. Using a numerically exact method based on the thermo field dynamics(TFD) theory and the matrix product states(MPS), we obtain exact evolutions of the TLS and bath(environment) under repetitive measurements at both zero and finite temperatures. At zero temperature, we observe a novel transition from a pure QZE in the short time scale to a QZE-QAZE crossover in the long time scale, by considering the measurement induced non-Markvoian effect. At finite temperature, we exploit that the thermal fluctuation suppresses the decay of the survival probability in the short time scale, whereas it enhances the decay in the long time scale.

quant-ph↗

arXiv2017

Ultra-Wideband Aided Fast Localization and Mapping System

This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces challenges with accumulated errors in the long run or under unfavourable environments, the UWB ranging measurements are fused to remove the visual drift and improve the robustness. A general framework is developed which consists of three parallel threads, two of which carry out the visual-inertial odometry (VIO) and UWB localization respectively. The other mapping thread integrates visual tracking constraints into a pose graph with the proposed smooth and virtual range constraints, such that an optimization is performed to provide robust trajectory estimation. Experiments show that the proposed system is able to create dense drift-free maps in real-time even running on an ultra-low power processor in featureless environments.

cs.RO↗

arXiv2017

p-Divisibility of the number of linear representations of an Abelian p-group

We establish lower bounds for the $p$-divisibility of the quantity $\#\operatorname{Hom}(G,GL_n(\mathbb{F}_q))$, the number of homomorphisms from $G$ to a general linear group, where $G$ is an Abelian $p$-group. This is in analogy to the result of Krattenthaler and Müller \cite{MR3383810} on homomorphisms to symmetric groups.

math.CO↗

arXiv2017

Interpreting Shared Deep Learning Models via Explicable Boundary Trees

Despite outperforming the human in many tasks, deep neural network models are also criticized for the lack of transparency and interpretability in decision making. The opaqueness results in uncertainty and low confidence when deploying such a model in model sharing scenarios, when the model is developed by a third party. For a supervised machine learning model, sharing training process including training data provides an effective way to gain trust and to better understand model predictions. However, it is not always possible to share all training data due to privacy and policy constraints. In this paper, we propose a method to disclose a small set of training data that is just sufficient for users to get the insight of a complicated model. The method constructs a boundary tree using selected training data and the tree is able to approximate the complicated model with high fidelity. We show that traversing data points in the tree gives users significantly better understanding of the model and paves the way for trustworthy model sharing.

cs.LG↗

arXiv2017

Predicting the Popularity of Topics based on User Sentiment in Microblogging Websites

Behavioral economics show us that emotions play an important role in individual behavior and decision-making. Does this also affect collective decision making in a community? Here we investigate whether the community sentiment energy of a topic is related to the spreading popularity of the topic. To compute the community sentiment energy of a topic, we first analyze the sentiment of a user on the key phrases of the topic based on the recent tweets of the user. Then we compute the total sentiment energy of all users in the community on the topic based on the Markov Random Field (MRF) model and graph entropy model. Experiments on two communities find the linear correlation between the community sentiment energy and the real spreading popularity of topics. Based on the finding, we proposed two models to predict the popularity of topics. Experimental results show the effectiveness of the two models and the helpful of sentiment in predicting the popularity of topics. Experiments also show that community sentiment affects collective decision making of spreading a topic or not in the community.

cs.SI↗

arXiv2017

A discriminative view of MRF pre-processing algorithms

While Markov Random Fields (MRFs) are widely used in computer vision, they present a quite challenging inference problem. MRF inference can be accelerated by pre-processing techniques like Dead End Elimination (DEE) or QPBO-based approaches which compute the optimal labeling of a subset of variables. These techniques are guaranteed to never wrongly label a variable but they often leave a large number of variables unlabeled. We address this shortcoming by interpreting pre-processing as a classification problem, which allows us to trade off false positives (i.e., giving a variable an incorrect label) versus false negatives (i.e., failing to label a variable). We describe an efficient discriminative rule that finds optimal solutions for a subset of variables. Our technique provides both per-instance and worst-case guarantees concerning the quality of the solution. Empirical studies were conducted over several benchmark datasets. We obtain a speedup factor of 2 to 12 over expansion moves without preprocessing, and on difficult non-submodular energy functions produce slightly lower energy.

cs.CV↗

arXiv2017

Non-Iterative SLAM

The goal of this paper is to create a new framework for dense SLAM that is light enough for micro-robot systems based on depth camera and inertial sensor. Feature-based and direct methods are two mainstreams in visual SLAM. Both methods minimize photometric or reprojection error by iterative solutions, which are computationally expensive. To overcome this problem, we propose a non-iterative framework to reduce computational requirement. First, the attitude and heading reference system (AHRS) and axonometric projection are utilized to decouple the 6 Degree-of-Freedom (DoF) data, so that point clouds can be matched in independent spaces respectively. Second, based on single key-frame training, the matching process is carried out in frequency domain by Fourier transformation, which provides a closed-form non-iterative solution. In this manner, the time complexity is reduced to $\mathcal{O}(n \log{n})$, where $n$ is the number of matched points in each frame. To the best of our knowledge, this method is the first non-iterative and online trainable approach for data association in visual SLAM. Compared with the state-of-the-arts, it runs at a faster speed and obtains 3-D maps with higher resolution yet still with comparable accuracy.

cs.RO↗

arXiv2017

Molecular gas toward the Gemini OB1 Giant Molecular Cloud Complex I: Observation data

We present a large-scale mapping toward the GEM OB1 association in the galactic anti-center direction. The 9^deg * 6.5^deg area was mapped in 12CO, 13CO, and C18O with 50" angular resolution at 30" sampling. The region was divided into four main components based on spatial distribution and velocity: the Gemini OB1 Giant Molecular Cloud (GGMC) Complex, the Lynds Dark Clouds and the West Front Clouds, the Swallow and Horn, and the Remote Clouds. The GGMC Complex is located in the Perseus arm, while the Lynds Dark Clouds and the West Front Clouds are located in the Local arm. Swallow and Horn are revealed for the first time in this paper. The two clouds have a similar velocity interval ([11, 21] km s^-1) and have similar sizes (0.6 and 0.8 deg^2). We analyzed the structure of these clouds in detail and calculated their parameters (mass, temperature, etc.). Two elongated structures were discovered in a longitude-velocity map in the velocity interval [11, 30] km s^-1. We also found an interesting filament that shows a 0.8 km s^-1 pc^-1 gradient perpendicular to the direction of the long axis.

astro-ph.GA↗

arXiv2017

HPDedup: A Hybrid Prioritized Data Deduplication Mechanism for Primary Storage in the Cloud

Eliminating duplicate data in primary storage of clouds increases the cost-efficiency of cloud service providers as well as reduces the cost of users for using cloud services. Existing primary deduplication techniques either use inline caching to exploit locality in primary workloads or use post-processing deduplication running in system idle time to avoid the negative impact on I/O performance. However, neither of them works well in the cloud servers running multiple services or applications for the following two reasons: Firstly, the temporal locality of duplicate data writes may not exist in some primary storage workloads thus inline caching often fails to achieve good deduplication ratio. Secondly, the post-processing deduplication allows duplicate data to be written into disks, therefore does not provide the benefit of I/O deduplication and requires high peak storage capacity. This paper presents HPDedup, a Hybrid Prioritized data Deduplication mechanism to deal with the storage system shared by applications running in co-located virtual machines or containers by fusing an inline and a post-processing process for exact deduplication. In the inline deduplication phase, HPDedup gives a fingerprint caching mechanism that estimates the temporal locality of duplicates in data streams from different VMs or applications and prioritizes the cache allocation for these streams based on the estimation. HPDedup also allows different deduplication threshold for streams based on their spatial locality to reduce the disk fragmentation. The post-processing phase removes duplicates whose fingerprints are not able to be cached due to the weak temporal locality from disks. Our experimental results show that HPDedup clearly outperforms the state-of-the-art primary storage deduplication techniques in terms of inline cache efficiency and primary deduplication efficiency.

cs.DC↗

arXiv2017

Order Determination of Large Dimensional Dynamic Factor Model

Consider the following dynamic factor model: $\mathbf{R}_t=\sum_{i=0}^q \mathbfΛ_i \mathbf{f}_{t-i}+\mathbf{e}_t,t=1,...,T$, where $\mathbfΛ_i$ is an $n\times k$ loading matrix of full rank, $\{\mathbf{f}_t\}$ are i.i.d. $k\times1$-factors, and $\mathbf{e}_t$ are independent $n\times1$ white noises. Now, assuming that $n/T\to c>0$, we want to estimate the orders $k$ and $q$ respectively. Define a random matrix $$\mathbfΦ_n(τ)=\frac{1}{2T}\sum_{j=1}^T (\mathbf{R}_j \mathbf{R}_{j+τ}^* + \mathbf{R}_{j+τ} \mathbf{R}_j^*),$$ where $τ\ge 0$ is an integer. When there are no factors, the matrix $Φ_{n}(τ)$ reduces to $$\mathbf{M}_n(τ) = \frac{1}{2T} \sum_{j=1}^T (\mathbf{e}_j \mathbf{e}_{j+τ}^* + \mathbf{e}_{j+τ} \mathbf{e}_j^*).$$ When $τ=0$, $\mathbf{M}_n(τ)$ reduces to the usual sample covariance matrix whose ESD tends to the well known MP law and $\mathbfΦ_n(0)$ reduces to the standard spike model. Hence the number $k(q+1)$ can be estimated by the number of spiked eigenvalues of $\mathbfΦ_n(0)$. To obtain separate estimates of $k$ and $q$ , we have employed the spectral analysis of $\mathbf{M}_n(τ)$ and established the spiked model analysis for $\mathbfΦ_n(τ)$.

math.ST↗

arXiv2017

Spectral indices for radio emission of 228 pulsars

We determine spectral indices of 228 pulsars by using Parkes pulsar data observed at 1.4 GHz, among which 200 spectra are newly determined. The indices are distributed in the range from -4.84 to -0.46.Together with known pulsar spectra from literature, we tried to find clues to the pulsar emission process. The weak correlations between the spectral index, the spin-down energy loss rate $\dot{E}$ and the potential drop in the polar gap $ΔΨ$ hint that emission properties are related to the particle acceleration process in a pulsar's magnetosphere.

astro-ph.HE↗

arXiv2017

Unifying quantum heat transfer in a nonequilibrium spin-boson model with full counting statistics

To study the full counting statistics of quantum heat transfer in a driven nonequilibrium spin-boson model, we develop a generalized nonequilibrium polaron-transformed Redfield equation with an auxiliary counting field. This enables us to study the impact of qubit-bath coupling ranging from weak to strong regimes. Without external modulations, we observe maximal values of both steady state heat flux and noise power at moderate coupling regimes, below which we find those two transport quantities are enhanced by the finite qubit energy bias. With external modulations, the geometric-phase-induced heat flux shows monotonic decrease as increasing the qubit-bath coupling at zero qubit energy bias (without bias). While under finite qubit energy bias (with bias), the geometric-phase-induced heat flux exhibits an interesting reversal behavior in strong coupling regime. Our results unify the seemingly contradictory results in weak and strong qubit-bath coupling regimes, and provide detailed dissections for the quantum fluctuation of nonequilibrium heat transfer.

cond-mat.mes-hall↗

arXiv2016

Influence of counter-rotating interaction on quantum phase transition in Dicke-Hubbard lattice: an extended coherent state approach

We investigate the ground state behavior of the Dicke-Hubbard model including counter-rotating-terms. By generalizing an extended coherent state approach within mean-field theory, we self-consistently obtain the ground state energy and delocalized order parameter. Localization-delocalization quantum phase transition of photons is clearly observed by breaking the parity symmetry. Particularly, Mott lobes are fully suppressed, and the delocalized order parameter shows monotonic enhancement by increasing qubit-cavity coupling strength, in sharp contrast to the Dicke-Hubbard model under rotating-wave approximation. Moreover, the corresponding phase boundaries are stabilized by decreasing photon hopping strength, compared to the Rabi-Hubbard model.

quant-ph↗

arXiv2016

Alternative asymptotics for cointegration tests in large VARs

Johansen's (1988, 1991) likelihood ratio test for cointegration rank of a Gaussian VAR depends only on the squared sample canonical correlations between current changes and past levels of a simple transformation of the data. We study the asymptotic behavior of the empirical distribution of those squared canonical correlations when the number of observations and the dimensionality of the VAR diverge to infinity simultaneously and proportionally. We find that the distribution almost surely weakly converges to the so-called Wachter distribution. This finding provides a theoretical explanation for the observed tendency of Johansen's test to find "spurious cointegration". It also sheds light on the workings and limitations of the Bartlett correction approach to the over-rejection problem. We propose a simple graphical device, similar to the scree plot, for a preliminary assessment of cointegration in high-dimensional VARs.

math.ST↗

arXiv2016

Axion-photon Propagation in Magnetized Universe

Oscillations between photons and axion-like particles (ALP) travelling in intergalactic magnetic fields have been invoked to explain a number of astrophysical phenomena, or used to constrain ALP properties using observations. One example is the anomalous transparency of the universe to TeV gamma-rays. The intergalactic magnetic field is usually modeled as patches of coherent domains, each with a uniform magnetic field, but the field orientation changes randomly from one domain to the next ("discrete-$φ$ model"). We show in this paper that in more realistic situations, when the magnetic field direction varies continuously along the propagation path, the photon-to-ALP conversion probability $P$ can be significantly different from the discrete-$φ$ model. In particular, $P$ has a distinct dependence on the photon energy and ALP mass, and can be as large as 100 percent. This result may affect previous constraints on ALP properties based on ALP-photon propagation in intergalactic magnetic fields.

astro-ph.HE↗

arXiv2016

A coaxial line architecture for integrating and scaling 3D cQED systems

Numerous loss mechanisms can limit coherence and scalability of planar and 3D-based circuit quantum electrodynamics (cQED) devices, particularly due to their packaging. The low loss and natural isolation of 3D enclosures make them good candidates for coherent scaling. We introduce a coaxial transmission line device architecture with coherence similar to traditional 3D cQED systems. Measurements demonstrate well-controlled external and on-chip couplings, a spectrum absent of cross-talk or spurious modes, and excellent resonator and qubit lifetimes. We integrate a resonator-qubit system in this architecture with a seamless 3D cavity, and separately pattern a qubit, readout resonator, Purcell filter and high-Q stripline resonator on a single chip. Device coherence and its ease of integration make this a promising tool for complex experiments.

quant-ph↗