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Xiao Liu

Publications and source records attributed to Xiao Liu.

At least 541 records · Page 30Linked to original sources
arXiv2016

A Polyhedral Study of the Static Probabilistic Lot-Sizing Problem

We study the polyhedral structure of the static probabilistic lot-sizing problem and propose valid inequalities that integrate information from the chance constraint and the binary setup variables. We prove that the proposed inequalities subsume existing inequalities for this problem, and they are facet-defining under certain conditions. In addition, we show that they give the convex hull description of a related stochastic lot-sizing problem. We propose a new formulation that exploits the simple recourse structure, which significantly reduces the number of variables and constraints of the deterministic equivalent program. This reformulation can be applied to general chance-constrained programs with simple recourse. The computational results show that the proposed inequalities and the new formulation are effective for the the static probabilistic lot-sizing problems.

math.OC↗
arXiv2016

Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks

Existing deep convolutional neural networks (CNNs) have shown their great success on image classification. CNNs mainly consist of convolutional and pooling layers, both of which are performed on local image areas without considering the dependencies among different image regions. However, such dependencies are very important for generating explicit image representation. In contrast, recurrent neural networks (RNNs) are well known for their ability of encoding contextual information among sequential data, and they only require a limited number of network parameters. General RNNs can hardly be directly applied on non-sequential data. Thus, we proposed the hierarchical RNNs (HRNNs). In HRNNs, each RNN layer focuses on modeling spatial dependencies among image regions from the same scale but different locations. While the cross RNN scale connections target on modeling scale dependencies among regions from the same location but different scales. Specifically, we propose two recurrent neural network models: 1) hierarchical simple recurrent network (HSRN), which is fast and has low computational cost; and 2) hierarchical long-short term memory recurrent network (HLSTM), which performs better than HSRN with the price of more computational cost. In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs). C-HRNNs not only make use of the representation power of CNNs, but also efficiently encodes spatial and scale dependencies among different image regions. On four of the most challenging object/scene image classification benchmarks, our C-HRNNs achieve state-of-the-art results on Places 205, SUN 397, MIT indoor, and competitive results on ILSVRC 2012.

cs.CV↗
arXiv2016

A Cost-Effective Strategy for Storing Scientific Datasets with Multiple Service Providers in the Cloud

Cloud computing provides scientists a platform that can deploy computation and data intensive applications without infrastructure investment. With excessive cloud resources and a decision support system, large generated data sets can be flexibly 1 stored locally in the current cloud, 2 deleted and regenerated whenever reused or 3 transferred to cheaper cloud service for storage. However, due to the pay for use model, the total application cost largely depends on the usage of computation, storage and bandwidth resources, hence cutting the cost of cloud based data storage becomes a big concern for deploying scientific applications in the cloud. In this paper, we propose a novel strategy that can cost effectively store large generated data sets with multiple cloud service providers. The strategy is based on a novel algorithm that finds the trade off among computation, storage and bandwidth costs in the cloud, which are three key factors for the cost of data storage. Both general (random) simulations conducted with popular cloud service providers pricing models and three specific case studies on real world scientific applications show that the proposed storage strategy is highly cost effective and practical for run time utilization in the cloud.

cs.DC↗
arXiv2015

On Differentially Private Online Collaborative Recommendation Systems

In collaborative recommendation systems, privacy may be compromised, as users' opinions are used to generate recommendations for others. In this paper, we consider an online collaborative recommendation system, and we measure users' privacy in terms of the standard differential privacy. We give the first quantitative analysis of the trade-offs between recommendation quality and users' privacy in such a system by showing a lower bound on the best achievable privacy for any non-trivial algorithm, and proposing a near-optimal algorithm. From our results, we find that there is actually little trade-off between recommendation quality and privacy for any non-trivial algorithm. Our results also identify the key parameters that determine the best achievable privacy.

cs.CR↗
arXiv2015

Storage of multiple single-photon pulses emitted from a quantum dot in a solid-state quantum memory

Quantum repeaters are critical components for distributing entanglement over long distances in presence of unavoidable optical losses during transmission. Stimulated by Duan-Lukin-Cirac-Zoller protocol, many improved quantum-repeater protocols based on quantum memories have been proposed, which commonly focus on the entanglement-distribution rate. Among these protocols, the elimination of multi-photons (multi-photon-pairs) and the use of multimode quantum memory are demonstrated to have the ability to greatly improve the entanglement-distribution rate. Here, we demonstrate the storage of deterministic single photons emitted from a quantum dot in a polarization-maintaining solid-state quantum memory; in addition, multi-temporal-mode memory with $1$, $20$ and $100$ narrow single-photon pulses is also demonstrated. Multi-photons are eliminated, and only one photon at most is contained in each pulse. Moreover, the solid-state properties of both sub-systems make this configuration more stable and easier to be scalable. Our work will be helpful in the construction of efficient quantum repeaters based on all-solid-state devices

quant-ph↗
arXiv2015

Two intervals Rényi entanglement entropy of compact free boson on torus

We compute the $N=2$ Rényi entanglement entropy of two intervals at equal time in a circle, for the theory of a 2d compact complex free scalar at finite temperature. This is carried out by performing functional integral on a genus 3 ramified cover of the torus, wherein the quantum part of the integral is captured by the four point function of twist fields on the worldsheet torus, and the classical piece is given by summing over winding modes of the genus 3 surface onto the target space torus. The final result is given in terms of a product of theta function and certain multi-dimensional theta function. We demonstrate the T-duality invariance of the result. We also study its low temperature limit. In the case in which the size of the intervals and of their separation are much smaller than the whole system, our result is in exact agreement with the known result for two intervals on an infinite system at zero temperature \cite{eeoftwo}. In the case in which the separation between the two intervals is much smaller than the interval length, the leading thermal corrections take the same universal form as proposed in \cite{Cardy:2014jwa,Chen:2015cna} for Rényi entanglement entropy of a single interval.

hep-th↗
arXiv2015

Quantum Storage of Three-Dimensional Orbital-Angular-Momentum Entanglement in a Crystal

Here we present the quantum storage of three-dimensional orbital-angular-momentum photonic entanglement in a rare-earth-ion-doped crystal. The properties of the entanglement and the storage process are confirmed by the violation of the Bell-type inequality generalized to three dimensions after storage ($S=2.152\pm0.033$). The fidelity of the memory process is $0.993\pm0.002$, as determined through complete quantum process tomography in three dimensions. An assessment of the visibility of the stored weak coherent pulses in higher-dimensional spaces, demonstrates that the memory is highly reliable for 51 spatial modes. These results pave the way towards the construction of high-dimensional and multiplexed quantum repeaters based on solid-state devices. The multimode capacity of rare-earth-based optical processor goes beyond the temporal and the spectral degree of freedom, which might provide a useful tool for photonic information processing.

quant-ph↗
arXiv2015

The Dirac Operator on Regular Metric Trees

A metric tree is a tree whose edges are viewed as line segments of positive length. The Dirac operator on such tree is the operator which operates on each edge, complemented by the matching conditions at the vertices which were given by Bolte and Harrison \cite{BolteHarrison2003}. The spectrum of Dirac operator can be quite different, reflecting geometry of the tree. We discuss a special case of trees, namely the so-called regular trees. They possess a rich group of symmetries. This allows one to construct an orthogonal decomposition of the space $L^2(Γ)$ which reduces the Dirac. Based upon this decomposition, a detailed spectral analysis of Dirac operator on the regular metric trees is possible.

math-ph↗
arXiv2015

Tunable temporal gap based on simultaneous fast and slow light in electro-optic photonic crystals

We demonstrated a tunable temporal gap based on simultaneous fast and slow light in electro-optic photonic crystals. The light experiences an anomalous dispersion near the transmission center and a normal dispersion away from the center, where it can be accelerated and slowed down, respectively. We also obtained the switch between fast and slow light by adjusting the external electric filed. The observed largest temporal gap is 541 ps, which is crucial in practical event operation inside the gap. The results offer a new solution for temporal cloak.

physics.optics↗
arXiv2014

An Empirical Study on Software Defect Prediction with a Simplified Metric Set

Software defect prediction plays a crucial role in estimating the most defect-prone components of software, and a large number of studies have pursued improving prediction accuracy within a project or across projects. However, the rules for making an appropriate decision between within- and cross-project defect prediction when available historical data are insufficient remain unclear. The objective of this work is to validate the feasibility of the predictor built with a simplified metric set for software defect prediction in different scenarios, and to investigate practical guidelines for the choice of training data, classifier and metric subset of a given project. First, based on six typical classifiers, we constructed three types of predictors using the size of software metric set in three scenarios. Then, we validated the acceptable performance of the predictor based on Top-k metrics in terms of statistical methods. Finally, we attempted to minimize the Top-k metric subset by removing redundant metrics, and we tested the stability of such a minimum metric subset with one-way ANOVA tests. The experimental results indicate that (1) the choice of training data should depend on the specific requirement of prediction accuracy; (2) the predictor built with a simplified metric set works well and is very useful in case limited resources are supplied; (3) simple classifiers (e.g., Naive Bayes) also tend to perform well when using a simplified metric set for defect prediction; and (4) in several cases, the minimum metric subset can be identified to facilitate the procedure of general defect prediction with acceptable loss of prediction precision in practice. The guideline for choosing a suitable simplified metric set in different scenarios is presented in Table 12.

cs.SE↗
arXiv2014

A Robust Point Sets Matching Method

Point sets matching method is very important in computer vision, feature extraction, fingerprint matching, motion estimation and so on. This paper proposes a robust point sets matching method. We present an iterative algorithm that is robust to noise case. Firstly, we calculate all transformations between two points. Then similarity matrix are computed to measure the possibility that two transformation are both true. We iteratively update the matching score matrix by using the similarity matrix. By using matching algorithm on graph, we obtain the matching result. Experimental results obtained by our approach show robustness to outlier and jitter.

cs.CV↗
arXiv2013

A Survey on Gas Sensing Technology

Sensing technology has been widely investigated and utilized for gas detection. Due to the different applicability and inherent limitations of different gas sensing technologies, researchers have been working on different scenarios with enhanced gas sensor calibration. This paper reviews the descriptions, evaluation, comparison and recent developments in existing gas sensing technologies. A classification of sensing technologies is given, based on the variation of electrical and other properties. Detailed introduction to sensing methods based on electrical variation is discussed through further classification according to sensing materials, including metal oxide semiconductors, polymers, carbon nanotubes, and moisture absorbing materials. Methods based on other kinds of variations such as optical, calorimetric, acoustic and gas-chromatographic, are presented in a general way. Several suggestions related to future development are also discussed. Furthermore, this paper focuses on sensitivity and selectivity for performance indicators to compare different sensing technologies, analyzes the factors that influence these two indicators, and lists several corresponding improved approaches.

physics.ins-det↗
arXiv2013

Dynamical behaviors of FRW Universe containing a positive/negative potential scalar field in loop quantum cosmology

The dynamical behaviors of FRW Universe containing a posivive/negative potential scalar field in loop quantum cosmology scenario are discussed. The method of the phase-plane analysis is used to investigate the stability of the Universe. It is found that the stability properties in this situation are quite different from the classical cosmology case. For a positive potential scalar field coupled with a barotropic fluid, the cosmological autonomous system has five fixed points and one of them is stable if the adiabatic index $γ$ satisfies $0<γ<2$. This leads to the fact that the universe just have one bounce point instead of the singularity which lies in the quantum dominated area and it is caused by the quantum geometry effect. There are four fixed points if one considers a scalar field with a negative potential, but none of them is stable. Therefore, the universe has two kinds of bounce points, one is caused by the quantum geometry effect and the other is caused by the negative potential, the Universe may enter a classical re-collapse after the quantum bounce. This hints that the spatially flat FRW Universe containing a negative potential scalar field is cyclic.

gr-qc↗
arXiv2013

Path Integral of Bianchi I models in Loop Quantum Cosmology

A path integral formulation of the Bianchi I models containing a massless scalar field in loop quantum cosmology is constructed. Following the strategy used in the homogenous and isotropic case, the calculation is extended to the simplest non-isotropic models according to the $\barμ$ and $\barμ^{\prime}$ scheme. It is proved from the path integral angle that the quantum dynamic lacks the full invariance with respect to fiducial cell scaling in the $\barμ$ scheme, but it does not in the $\barμ^{\prime}$ scheme. The investigation affirms the equivalence of the canonical approach and the path integral approach in loop quantum cosmology.

gr-qc↗
arXiv2013

Focusing Singularity in a Derivative Nonlinear Schrödinger Equation

We present a numerical study of a derivative nonlinear Schrödinger equation with a general power nonlinearity, $|ψ|^{2σ}ψ_x$. In the $L^2$-supercritical regime, $σ>1$, our simulations indicate that there is a finite time singularity. We obtain a precise description of the local structure of the solution in terms of blowup rate and asymptotic profile, in a form similar to that of the nonlinear Schrödinger equation with supercritical power law nonlinearity.

math.AP↗
arXiv2011

The Leading Behaviour of The Ground-State Energy of Heavy Ions According to Brown and Ravenhall

In this article we prove the absence of relativistic effects in leading order for the ground-state energy according to Brown-Ravenhall operator. We obtain this asymptotic result for negative ions and for systems with the number of electrons proportional to the nuclear charge. In the case of neutral atoms the analogous result was obtained earlier by Cassanas and Siedentop [4].

math-ph↗
arXiv2010

Shocks and Universal Statistics in (1+1)-Dimensional Relativistic Turbulence

We propose that statistical averages in relativistic turbulence exhibit universal properties. We consider analytically the velocity and temperature differences structure functions in the (1+1)-dimensional relativistic turbulence in which shock waves provide the main contribution to the structure functions in the inertial range. We study shock scattering, demonstrate the stability of the shock waves, and calculate the anomalous exponents. We comment on the possibility of finite time blowup singularities.

hep-th↗