arXiv subjects

Wei Zhong

Publications and source records attributed to Wei Zhong.

At least 109 records · Page 6Linked to original sources

arXiv2020

Measurement-device-independent quantum key distribution of multiple degrees of freedom of a single photon

Measurement-device-independent quantum key distribution (MDI-QKD) provides us a powerful approach to resist all attacks at detection side. Besides the unconditional security, people also seek for high key generation rate, but MDI-QKD has relatively low key generation rate. In this paper, we provide an efficient approach to increase the key generation rate of MDI-QKD by adopting multiple degrees of freedom (DOFs) of single photons to generate keys. Compared with other high-dimension MDI-QKD protocols encoding in one DOF, our protocol is more flexible, for our protocol generating keys in independent subsystems and the detection failure or error in a DOF not affecting the information encoding in other DOFs. Based on above features, our MDI-QKD protocol may have potential application in future quantum communication field.

quant-ph↗

arXiv2020

Super slowing down in the bond-diluted Ising model

In models in statistical physics, the dynamics often slows down tremendously near the critical point. Usually, the correlation time $τ$ at the critical point increases with system size $L$ in power-law fashion: $τ\sim L^z$, which defines the critical dynamical exponent $z$. We show that this also holds for the 2D bond-diluted Ising model in the regime $p>p_c$, where $p$ is the parameter denoting the bond concentration, but with a dynamical critical exponent $z(p)$ which shows a strong $p$-dependence. Moreover, we show numerically that $z(p)$, as obtained from the autocorrelation of the total magnetisation, diverges when the percolation threshold $p_c=1/2$ is approached: $z(p)-z(1) \sim (p-p_c)^{-2}$. We refer to this observed extremely fast increase of the correlation time with size as {\it super slowing down}. Independent measurement data from the mean-square deviation of the total magnetisation, which exhibits anomalous diffusion at the critical point, supports this result.

cond-mat.stat-mech↗

arXiv2020

Ancilla-assisted frequency estimation under phase covariant noises with Greenberger-Horne-Zeilinger states

It has been demonstrated that the optimal sensitivity achievable with Greenberger-Horne-Zeilinger states is the same as that with uncorrelated probes in the frequency estimation in the presence of uncorrelated Markovian dephasing [S. F. Huelga, et al., Phys. Rev. Lett. 79, 3865 (1997)]. Here, we extend this issue by examining the optimal frequency sensitivities achievable by the use of ancilla-assisted strategy, which has been proposed recently for robust phase estimation. We present the ultimate frequency sensitivities bounded by the quantum Fisher information for a general case in the presence of Markovian covariant phase noises, and the optimal measurement observables that can saturate the theoretical sensitivity bounds. We also demonstrate the effectiveness of the ancilla-assisted strategy for preserving frequency sensitivities suffering from specific physically ground noises.

quant-ph↗

arXiv2020

Estimation and Inference for Multi-Kink Quantile Regression

The Multi-Kink Quantile Regression (MKQR) model is an important tool for analyzing data with heterogeneous conditional distributions, especially when quantiles of response variable are of interest, due to its robustness to outliers and heavy-tailed errors in the response. It assumes different linear quantile regression forms in different regions of the domain of the threshold covariate but are still continuous at kink points. In this paper, we investigate parameter estimation, kink point detection and statistical inference in MKQR models. We propose an iterative segmented quantile regression algorithm for estimating both the regression coefficients and the locations of kink points. The proposed algorithm is much more computationally efficient than the grid search algorithm and not sensitive to the selection of initial values. Asymptotic properties, such as selection consistency of the number of kink points, asymptotic normality of the estimators of both regression coefficients and kink effects, are established to justify the proposed method theoretically. A score test, based on partial subgradients, is developed to verify whether the kink effects exist or not. Test-inversion confidence intervals for kink location parameters are also constructed. Intensive simulation studies conducted show the proposed methods work very well when sample size is finite. Finally, we apply the MKQR models together with the proposed methods to the dataset about secondary industrial structure of China and the dataset about triceps skinfold thickness of Gambian females, which leads to some very interesting findings. A new R package MultiKink is developed to implement the proposed methods.

stat.ME↗

arXiv2020

Quantum-enhanced interferometry with asymmetric beam splitters

In this paper, we investigate the phase sensitivities in two-path optical interferometry with asymmetric beam splitters. Here, we present the optimal conditions for the transmission ratio and the phase of the beam splitter to gain the highest sensitivities for a general class of non-classical states with parity symmetry. Additionally, we address the controversial question of whether the scheme with a combination of coherent state and photon-added or photon-subtracted squeezed vacuum state is better or worse than the most celebrated one using a combination of coherent state and squeezed vacuum state.

quant-ph↗

arXiv2019

VLSI Mask Optimization: From Shallow To Deep Learning

VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation. Recent researches have shown prominent advantages of machine learning techniques dealing with complicated and big data problems, which bring potential of dedicated machine learning solution for DFM problems and facilitate the VLSI design cycle. In this paper, we focus on a heterogeneous OPC framework that assists mask layout optimization. Preliminary results show the efficiency and effectiveness of proposed frameworks that have the potential to be alternatives to existing EDA solutions.

cs.LG↗

arXiv2019

Query Auto Completion for Math Formula Search

Query Auto Completion (QAC) is among the most appealing features of a web search engine. It helps users formulate queries quickly with less effort. Although there has been much effort in this area for text, to the best of our knowledge there is few work on mathematical formula auto completion. In this paper, we implement 5 existing QAC methods on mathematical formula and evaluate them on the NTCIR-12 MathIR task dataset. We report the efficiency of retrieved results using Mean Reciprocal Rank (MRR) and Mean Average Precision(MAP). Our study indicates that the Finite State Transducer outperforms other QAC models with a MRR score of $0.642$.

cs.IR↗

arXiv2019

Through-the-Wall Imaging Exploiting 2.4GHz Commodity Wi-Fi

In this letter, we experimentally investigate a low-cost through-the-wall imaging exploiting Wi-Fi signals in an indoor environment from the perspective of holographic imaging. In our experiments, a pair of antennas in a synthetic aperture mode is used to acquire signals produced by commodity Wi-Fi devices and reflected from the scene in a synthetic aperture mode. The classical filtered back propagation (FBP) algorithm is then employed to form the image based on these signals. We use an IEEE 802.11n wireless router working at 2.4GHz with bandwidth of 20MHz. Selected experimental results are provided to demonstrate the performance of the proposed Wi-Fi based imaging scheme.

eess.SP↗

arXiv2018

Critical Dynamical Exponent of the Two-Dimensional Scalar $ϕ^4$ Model with Local Moves

We study the scalar one-component two-dimensional (2D) $ϕ^4$ model by computer simulations, with local Metropolis moves. The equilibrium exponents of this model are well-established, e.g. for the 2D $ϕ^4$ model $γ= 1.75$ and $ν= 1$. The model has also been conjectured to belong to the Ising universality class. However, the value of the critical dynamical exponent $z_c$ is not settled. In this paper, we obtain $z_c$ for the 2D $ϕ^4$ model using two independent methods: (a) by calculating the relative terminal exponential decay time $τ$ for the correlation function $\langle ϕ(t)ϕ(0)\rangle$, and thereafter fitting the data as $τ\sim L^{z_c}$, where $L$ is the system size, and (b) by measuring the anomalous diffusion exponent for the order parameter, viz., the mean-square displacement (MSD) $\langle Δϕ^2(t)\rangle\sim t^c$ as $c=γ/(νz_c)$, and from the numerically obtained value $c\approx 0.80$, we calculate $z_c$. For different values of the coupling constant $λ$, we report that $z_c=2.17\pm0.03$ and $z_c=2.19\pm0.03$ for the two methods respectively. Our results indicate that $z_c$ is independent of $λ$, and is likely identical to that for the 2D Ising model. Additionally, we demonstrate that the Generalised Langevin Equation (GLE) formulation with a memory kernel, identical to those applicable for the Ising model and polymeric systems, consistently capture the observed anomalous diffusion behavior.

cond-mat.stat-mech↗

arXiv2018

Generalised Langevin Equation Formulation for Anomalous Diffusion in the Ising Model at the Critical Temperature

We consider the two- (2D) and three-dimensional (3D) Ising model on a square lattice at the critical temperature $T_c$, under Monte-Carlo spin flip dynamics. The bulk magnetisation and the magnetisation of a tagged line in the 2D Ising model, and the bulk magnetisation and the magnetisation of a tagged plane in the 3D Ising model exhibit anomalous diffusion. Specifically, their mean-square displacement increases as power-laws in time, collectively denoted as $\sim t^c$, where $c$ is the anomalous exponent. We argue that the anomalous diffusion in all these quantities for the Ising model stems from time-dependent restoring forces, decaying as power-laws in time --- also with exponent $c$ --- in striking similarity to anomalous diffusion in polymeric systems. Prompted by our previous work that has established a memory-kernel based Generalised Langevin Equation (GLE) formulation for polymeric systems, we show that a closely analogous GLE formulation holds for the Ising model as well. We obtain the memory kernels from spin-spin correlation functions, and the formulation allows us to consistently explain anomalous diffusion as well as anomalous response of the Ising model to an externally applied magnetic field in a consistent manner.

cond-mat.stat-mech↗

arXiv2018

A Distribution-Free Test of Independence and Its Application to Variable Selection

Motivated by the importance of measuring the association between the response and predictors in high dimensional data, In this article, we propose a new mean variance test of independence between a categorical random variable and a continuous one based on mean variance index. The mean variance index is zero if and only if two variables are independent. Under the independence, we derive an explicit form of its asymptotic null distribution, which provides us with an efficient and fast way to compute the empirical p-value in practice. The number of classes of the categorical variable is allowed to diverge slowly to the infinity. It is essentially a rank test and thus distribution-free. No assumption on the distributions of two random variables is required and the test statistic is invariant under one-to-one transformations. It is resistent to heavy-tailed distributions and extreme values. We assess its performance by Monte Carlo simulations and demonstrate that the proposed test achieves a higher power in comparison with the existing tests. We apply the proposed MV test to a high dimensional colon cancer gene expression data to detect the significant genes associated with the tissue syndrome.

stat.ME↗

arXiv2016

Magnetic Trapping of Cold Methyl Radicals

We have demonstrated that a supersonic beam of methyl radicals (CH$_3$) in the ground rotational state of both $para$ and $ortho$ species has been slowed down to standstill with a magnetic molecular decelerator, and successfully captured spatially in an anti-Helmholtz magnetic trap for $>$ 1 s. The trapped CH$_3$ radicals have a mean translational temperature of about 200 mK with an estimated density of $>5.0\times10^7$ cm$^{-3}$. The methyl radical is an ideal system for the study of cold molecules not only because of its high reactivities at low temperatures, but also because further cooling below 1 mK is plausible via sympathetic cooling with ultracold atoms. The demonstrated trapping capability of methyl radicals opens up various possibilities for realizing ultracold ensembles of molecules towards Bose-Einstein condensation of polyatomic molecules and investigations of reactions governed by quantum statistics.

physics.chem-ph↗

arXiv2016

Optimal Conventional Measurements for Quantum-Enhanced Interferometry

A major obstacle to attain the fundamental precision limit of the phase estimation in an interferometry is the identification and implementation of the optimal measurement. Here we demonstrate that this can be accomplished by the use of three conventional measurements among interferometers with Bayesian estimation techniques. Conditions that hold for the precision limit to be attained with these measurements are obtained by explicitly calculating the Fisher information. Remarkably, these conditions are naturally satisfied in most interferometric experiments. We apply our results to an experiment of atomic spectroscopy and examine robustness of phase sensitivity for the two-axis counter-twisted state suffering from detection noise.

quant-ph↗

arXiv2015

A fast algorithm for detecting gene-gene interactions in genome-wide association studies

With the recent advent of high-throughput genotyping techniques, genetic data for genome-wide association studies (GWAS) have become increasingly available, which entails the development of efficient and effective statistical approaches. Although many such approaches have been developed and used to identify single-nucleotide polymorphisms (SNPs) that are associated with complex traits or diseases, few are able to detect gene-gene interactions among different SNPs. Genetic interactions, also known as epistasis, have been recognized to play a pivotal role in contributing to the genetic variation of phenotypic traits. However, because of an extremely large number of SNP-SNP combinations in GWAS, the model dimensionality can quickly become so overwhelming that no prevailing variable selection methods are capable of handling this problem. In this paper, we present a statistical framework for characterizing main genetic effects and epistatic interactions in a GWAS study. Specifically, we first propose a two-stage sure independence screening (TS-SIS) procedure and generate a pool of candidate SNPs and interactions, which serve as predictors to explain and predict the phenotypes of a complex trait. We also propose a rates adjusted thresholding estimation (RATE) approach to determine the size of the reduced model selected by an independence screening. Regularization regression methods, such as LASSO or SCAD, are then applied to further identify important genetic effects. Simulation studies show that the TS-SIS procedure is computationally efficient and has an outstanding finite sample performance in selecting potential SNPs as well as gene-gene interactions. We apply the proposed framework to analyze an ultrahigh-dimensional GWAS data set from the Framingham Heart Study, and select 23 active SNPs and 24 active epistatic interactions for the body mass index variation. It shows the capability of our procedure to resolve the complexity of genetic control.

stat.AP↗

arXiv2014

Non-Markovian dynamics of mixed-state geometric phase of dissipative qubits

We investigate the geometric phase of a two-level atom (qubit) coupled to a bosonic reservoir with Lorentzian spectral density, and find that for the non-Markovian dynamics in which rotating-wave approximation (RWA) is performed, geometric phase has a $π$-phase jump at the nodal point. However, the exact result without RWA given by hierarchy equation of motion method shows that there is no such a phase jump or nodal structure in geometric phase. Thus our results demonstrate that the counter-rotating terms significantly contribute to the geometric phase in multi-mode Hamiltonian under certain circumstances.

quant-ph↗

arXiv2014

Optimal condition for measurement observable via error-propagation

Propagation of error is a widely used estimation tool in experiments, where the estimation precision of the parameter depends on the fluctuation of the physical observable. Thus which observable is chosen will greatly affect the estimation sensitivity. Here we study the optimal observable for the ultimate sensitivity bounded by the quantum Cramér-Rao theorem in parameter estimation. By invoking the Schrödinger-Robertson uncertainty relation, we derive the necessary and sufficient condition for the optimal observables saturating the ultimate sensitivity for single parameter estimate. By applying this condition to Greenberg-Horne-Zeilinger states, we obtain the general expression of the optimal observable for separable measurements to achieve the Heisenberg-limit precision and show that it is closely related to the parity measurement. However, Jose {\em et al} [Phys. Rev. A {\bf 87}, 022330 (2013)] have claimed that the Heisenberg limit may not be obtained via separable measurements. We show this claim is incorrect.

quant-ph↗

arXiv2014

Quantum Fisher information and spin squeezing in one-axis twisting model

We consider the quantum Fisher information and spin squeezing in one-axis twisting model with a coherent spin state $|θ_{0},ϕ_{0}\rangle$. We analytically discuss the dependence of the two parameters: spin squeezing parameter $ξ^2_{K}$ and the average parameter estimation precision $χ^2$ on the polar angle $θ_{0}$ and the azimuth angle $ϕ_0$. Moreover, we discuss the effects of the collisional dephasing on the dynamics of the two parameters. In this case, the analytical solution of $ξ^2_K$ is also obtained.

quant-ph↗

arXiv2013

Quantum Fisher information for density matrices with arbitrary ranks

We provide a new expression of the quantum Fisher information(QFI) for a general system. Utilizing this expression, the QFI for a non-full rank density matrix is only determined by its support. This expression can bring convenience for a infinite dimensional density matrix with a finite support. Besides, a matrix representation of the QFI is also given.

quant-ph↗