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Lin Zhang

Publications and source records attributed to Lin Zhang.

At least 343 records · Page 19Linked to original sources
arXiv2020

The influence of anti-chiral edge states on Andreev reflection in graphene-superconductor junction

Using the tight binding model and the non-equilibrium Green function method, we study Andreev reflection in graphene-superconductor junction, where graphene has two nonequal Dirac Cones split in energy and therefore time reversal symmetry is broken. Due to the anti-chiral edge states of the current graphene model, an incident electron travelling along the edges makes distinct contribution to Andreev reflections. In a two-terminal device, because Andreev retro-reflection is not allowed for just the anti-chiral edges, in this case the mutual scattering between edge and bulk states is necessary, which leads that the coefficient of Andreev retro-reflection is always symmetrical about the incident energy. In a four-terminal junction, however, the edges are parallel to the interface of superconductor and graphene, so at the interface an incident electron travelling along the edges can be retro-reflected as a hole into bulk modes, or specularly reflected as a hole into anti-chiral edge states again. It is noted that, the coefficient of specular Andreev reflection keeps symmetric as to the incident energy of electron which is consistent with the reported results before, however the coefficient of Andreev retro-reflection shows an unexpected asymmetrical behavior due to the presence of anti-chiral edge states. Our results present some new ideas to study the anti-chiral edge modes and Andreev reflection for a graphene model with the broken time reversal symmetry.

cond-mat.supr-con↗
arXiv2019

Incompatibility probability of random quantum measurements

Incompatibility of quantum measurements is of fundamental importance in quantum mechanics. It is closely related to many nonclassical phenomena such as Bell nonlocality, quantum uncertainty relations, and quantum steering. We study the necessary and sufficient conditions of quantum compatibility for a given collection of $n$ measurements in $d$-dimensional space. From the compatibility criterion for two-qubit measurements, we compute the incompatibility probability of a pair of independent random measurements. For a pair of unbiased random qubit measurements, we derive that the incompatibility probability is exactly $\frac35$. Detailed results are also presented in figures for pairs of general qubit measurements.

quant-ph↗
arXiv2019

Overcoming the Channel Estimation Barrier in Massive MIMO Communication Systems

A new wave of wireless services, including virtual reality, autonomous driving and internet of things, is driving the design of new generations of wireless systems to deliver ultra-high data rates, massive number of connected devices and ultra low latency. Massive multiple-input multiple-output (MIMO) is one of the critical underlying technologies that allow future wireless networks to meet these service needs. This article discusses the application of deep learning (DL) for massive MIMO channel estimation in wireless networks by integrating the underlying characteristics of channels in future high-speed cellular deployment. We develop important insights derived from the physical radio frequency (RF) channel properties and present a comprehensive overview on the application of DL for accurately estimating channel state information (CSI) with low overhead. We provide examples of successful DL application in CSI estimation for massive MIMO wireless systems and highlight several promising directions for future research.

cs.IT↗
arXiv2019

An Efficient Deep Learning Framework for Low Rate Massive MIMO CSI Reporting

Channel state information (CSI) reporting is important for multiple-input multiple-output (MIMO) transmitters to achieve high capacity and energy efficiency in frequency division duplex (FDD) mode. CSI reporting for massive MIMO systems could consume excessive bandwidth and degrade spectrum efficiency. Deep learning (DL)-based compression integrated with channel correlations have demonstrated success in improving CSI recovery. However, existing works focusing on CSI compression have shown little on the efficient encoding of CSI report. In this paper, we propose an efficient DL-based compression framework (called CQNet) to jointly tackle CSI compression, report encoding, and recovery under bandwidth constraint. CQNet can be directly integrated within other DL-based CSI feedback works for further enhancement. CQNet significantly outperforms solutions using uniform CSI quantization and $μ$-law non-uniform quantization. Compared with traditional CSI reporting, much fewer bits are required to achieve comparable CSI reconstruction accuracy.

cs.IT↗
arXiv2019

Information transfer in generalized probabilistic theories based on weak repeatability

Information transfer in generalized probabilistic theories (GPT) is an important problem. We have dealt with the problem based on repeatability postulate, which generalizes Zurek's result to the GPT framework [Phys. Lett. A \textbf{379} (2015) 2694]. A natural question arises: can we deduce the information transfer result under weaker assumptions? In this paper, we generalize Zurek's result to the framework of GPT using weak repeatability postulate. We show that if distinguishable information can be transferred from a physical system to a series of apparatuses under the weak repeatability postulate in GPT, then the initial states of the physical system must be completely distinguishable. Moreover, after each step of invertible transformation, the composite states of the composite system composed of the physical systems and the apparatuses must also be completely distinguishable.

quant-ph↗
arXiv2019

Phase Contrast Microscopy Cell PopulationSegmentation: A Survey

Phase contrast microscopy (PCM) has been widely used in biomedicine research, which allows users to observe objectives without staining or killing them. One important related research is to employ PCM to monitor live cells. How to segment cell populations in obtained PCM images gains more and more attention as its a critical step for downstream applications, such as cell tracking, cell classification and others. Many papers have been published to deal with this problem from different perspectives. In this paper we aim to present a comprehensive review on the development of PCM cell population segmentation.

cs.CV↗
arXiv2019

Multipartite Entanglement Measure and Complete Monogamy Relation

Although many different entanglement measures have been proposed so far, much less is known in the multipartite case, which leads to the previous monogamy relations in literatures are not complete. We establish here a strict framework for defining multipartite entanglement measure (MEM): apart from the postulates of bipartite measure, a genuine MEM should additionally satisfy the unification condition and the hierarchy condition. We then come up with a complete monogamy formula for the unified MEM and a tightly complete monogamy relation for the genuine MEM. Consequently, we propose MEMs which are multipartite extensions of entanglement of formation (EoF), concurrence, tangle, Tsallis $q$-entropy of entanglement, Rényi $α$-entropy of entanglement, the convex-roof extension of negativity and negativity, respectively. We show that (i) the extensions of EoF, concurrence, tangle, and Tsallis $q$-entropy of entanglement are genuine MEMs, (ii) multipartite extensions of Rényi $α$-entropy of entanglement, negativity and the convex-roof extension of negativity are unified MEMs but not genuine MEMs, and (iii) all these multipartite extensions are completely monogamous and the ones which are defined by the convex-roof structure (except for the Rényi $α$-entropy of entanglement and the convex-roof extension of negativity) are not only completely monogamous but also tightly completely monogamous. In addition, we find a class of tripartite states that one part can maximally entangled with other two parts simultaneously according to the definition of maximally entangled mixed state (MEMS) in [Quantum Inf. Comput. 12, 0063 (2012)]. Consequently, we improve the definition of maximally entangled state (MES) and prove that there is no MEMS and that the only MES is the pure MES.

quant-ph↗
arXiv2019

Duistermaat-Heckman measure and the mixture of quantum states

In this paper, we present a general framework to solve a fundamental problem in Random Matrix Theory (RMT), i.e., the problem of describing the joint distribution of eigenvalues of the sum $\bsA+\bsB$ of two independent random Hermitian matrices $\bsA$ and $\bsB$. Some considerations about the mixture of quantum states are basically subsumed into the above mathematical problem. Instead, we focus on deriving the spectral density of the mixture of adjoint orbits of quantum states in terms of Duistermaat-Heckman measure, originated from the theory of symplectic geometry. Based on this method, we can obtain the spectral density of the mixture of independent random states. In particular, we obtain explicit formulas for the mixture of random qubits. We also find that, in the two-level quantum system, the average entropy of the equiprobable mixture of $n$ random density matrices chosen from a random state ensemble (specified in the text) increases with the number $n$. Hence, as a physical application, our results quantitatively explain that the quantum coherence of the mixture monotonously decreases statistically as the number of components $n$ in the mixture. Besides, our method may be used to investigate some statistical properties of a special subclass of unital qubit channels.

quant-ph↗
arXiv2019

Chiral transition and meson melting with finite chemical potential in an improved soft-wall AdS/QCD Model

We give a further study on the improved soft-wall AdS/QCD model with two flavors. The chiral transition behaviors are studied in the case of finite chemical potential, with the chiral phase diagram obtained at zero quark mass. The thermal spectral functions of the vector and axial-vector mesons are calculated, and the in-medium melting properties of the mesons are investigated. We find that the chiral transition behaviors and the meson melting properties at finite chemical potential can be qualitatively described by the improved soft-wall AdS/QCD model, except in the region of large chemical potential. The reason for these inadequate descriptions may be that the background geometry adopted in the model is not a dynamical one which is able to produce the QCD equation of state. To give a quantitative description for these low-energy phenomenologies, we shall consider a more consistent AdS/QCD model which treats the background fields and the chiral fields on the same footing.

hep-ph↗
arXiv2019

A random covariance model for bi-level graphical modeling with application to resting-state fMRI data

This paper considers a novel problem, bi-level graphical modeling, in which multiple individual graphical models can be considered as variants of a common group-level graphical model and inference of both the group- and individual-level graphical models are of interest. Such problem arises from many applications including multi-subject neuroimaging and genomics data analysis. We propose a novel and efficient statistical method, the random covariance model, to learn the group- and individual-level graphical models simultaneously. The proposed method can be nicely interpreted as a random covariance model that mimics the random effects model for mean structures in linear regression. It accounts for similarity between individual graphical models, identifies group-level connections that are shared by individuals in the group, and at the same time infers multiple individual-level networks. Compared to existing multiple graphical modeling methods that only focus on individual-level networks, our model learns the group-level structure underlying the multiple individual networks and enjoys computational efficiency that is particularly attractive for practical use. We further define a measure of degrees-of-freedom for the complexity of the model that can be used for model selection. We demonstrate the asymptotic properties of the method and show its finite sample performance through simulation studies. Finally, we apply the proposed method to our motivating clinical data, a multi-subject resting-state functional magnetic resonance imaging (fMRI) dataset collected from schizophrenia patients.

stat.ME↗
arXiv2019

20 Years of Evolution from Cognitive to Intelligent Communications

It has been 20 years since the concept of cognitive radio (CR) was proposed, which is an efficient approach to provide more access opportunities to connect massive wireless devices. To improve the spectrum efficiency, CR enables unlicensed usage of licensed spectrum resources. It has been regarded as the key enabler for intelligent communications. In this article, we will provide an overview on the intelligent communication in the past two decades to illustrate the revolution of its capability from cognition to artificial intelligence (AI). Particularly, this article starts from a comprehensive review of typical spectrum sensing and sharing, followed by the recent achievements on the AI-enabled intelligent radio. Moreover, research challenges in the future intelligent communications will be discussed to show a path to the real deployment of intelligent radio. After witnessing the glorious developments of CR in the past 20 years, we try to provide readers a clear picture on how intelligent radio could be further developed to smartly utilize the limited spectrum resources as well as to optimally configure wireless devices in the future communication systems.

cs.NI↗
arXiv2019

An Efficient Approach to Informative Feature Extraction from Multimodal Data

One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the Hirschfeld-Gebelein-Rényi (HGR) maximal correlation becomes an appealing objective because of its operational meaning and desirable properties. However, the strict whitening constraints formalized in the HGR maximal correlation limit its application. To address this problem, this paper proposes Soft-HGR, a novel framework to extract informative features from multiple data modalities. Specifically, our framework prevents the "hard" whitening constraints, while simultaneously preserving the same feature geometry as in the HGR maximal correlation. The objective of Soft-HGR is straightforward, only involving two inner products, which guarantees the efficiency and stability in optimization. We further generalize the framework to handle more than two modalities and missing modalities. When labels are partially available, we enhance the discriminative power of the feature representations by making a semi-supervised adaptation. Empirical evaluation implies that our approach learns more informative feature mappings and is more efficient to optimize.

cs.LG↗
arXiv2019

A variant of Horn's problem and derivative principle

Identifying the spectrum of the sum of two given Hermitian matrices with fixed eigenvalues is the famous Horn's problem.In this note, we investigate a variant of Horn's problem, i.e., we identify the probability density function (abbr. pdf) of the diagonals of the sum of two random Hermitian matrices with given spectra. We then use it to re-derive the pdf of the eigenvalues of the sum of two random Hermitian matrices with given eigenvalues via \emph{derivative principle}, a powerful tool used to get the exact probability distribution by reducing to the corresponding distribution of diagonal entries.We can recover Jean-Bernard Zuber's recent results on the pdf of the eigenvalues of two random Hermitian matrices with given eigenvalues. Moreover, as an illustration, we derive the analytical expressions of eigenvalues of the sum of two random Hermitian matrices from $\rG\rU\rE(n)$ or Wishart ensemble by derivative principle, respectively.We also investigate the statistics of exponential of random matrices and connect them with Golden-Thompson inequality, and partly answer a question proposed by Forrester. Some potential applications in quantum information theory, such as uniform average quantum Jensen-Shannon divergence and average coherence of uniform mixture of two orbits,are discussed.

quant-ph↗
arXiv2019

Octet meson spectra and chiral phase diagram in the improved soft-wall AdS/QCD model

We give a further study on chiral phase diagram in the improved soft-wall AdS/QCD model with $2+1$ flavors. The equations of motion for the octet pseudoscalar, vector and axial-vector mesons are derived to compute the octet meson spectra and relevant decay constants, by which the model parameters are determined. The chemical potential effects on thermal transition of chiral condensate are investigated, which enables us to obtain the chiral phase diagram in the $μ-T$ plane. We find that the critical end point linking the crossover transition with the first-order phase transition still exists and locates at $(μ_B, T_c) \simeq (390 \MeV, 145 \MeV)$, which along with the crossover line are consistent with lattice result and experimental analysis from relativistic heavy ion collisions.

hep-ph↗
arXiv2019

Emergent topology and symmetry-breaking order in correlated quench dynamics

Quenching a quantum system involves three basic ingredients: the initial phase, the post-quench target phase, and the non-equilibrium dynamics which carries the information of the former two. Here we propose a dynamical theory to characterize both the topology and symmetry-breaking order in correlated quantum system, through quenching the Haldane-Hubbard model from an initial magnetic phase to topologically nontrivial regime. The equation of motion for the complex pseudospin dynamics is obtained with the flow equation method, with the pseudospin evolution shown to obey a microscopic Landau-Lifshitz-Gilbert-Bloch equation. We find that the correlated quench dynamics exhibit robust universal behaviors on the so-called band-inversion surfaces (BISs), from which the nontrivial topology and magnetic order can be extracted. In particular, the topology of the post-quench regime can be characterized by an emergent dynamical topological pattern of quench dynamics on BISs, which is robust against dephasing and heating induced by interactions; the pre-quench symmetry-breaking orders is read out from a universal scaling behavior of the quench dynamics emerging on the BIS, which is valid beyond the mean-field regime. This work opens a way to characterize both the topology and symmetry-breaking orders by correlated quench dynamics.

cond-mat.quant-gas↗
arXiv2019

Characterizing topological phases by quantum quenches: A general theory

We investigate a generic dynamical theory to characterize topological quantum phases by quantum quenches, and study the emergent topology of quantum dynamics when the quenches start from a deep or shallow trivial phase to topological regimes. Two dynamical schemes are examined: One is to characterize topological phases via quantum dynamics induced by a single quench along an arbitrary axis, and the other applies a sequence of quenches with respect to all (pseudo)spin axes. These two schemes are both built on the so-called dynamical bulk-surface correspondence, which shows that the $d$-dimensional ($d$D) topological phases with integer invariants can be characterized by the dynamical topological pattern emerging on $(d-1)$D band inversion surfaces (BISs). We show that the first dynamical scheme works for both deep and shallow quenches, the latter of which is initialized in an incompletely polarized trivial phase. For the second scheme, however, when the initial phase for the quench study varies from the deep trivial (fully polarized) to shallow trivial (incompletely polarized) regime, a new dynamical topological transition, associated with topological charges crossing BISs, is predicted in quench dynamics. A generic criterion of the dynamical topological transition is precisely obtained. Above the criterion, quantum dynamics on BISs well characterizes the topology of the post-quench Hamiltonian. Below the criterion, the quench dynamics may depict a new dynamical topology; the post-quench topology can be characterized by the emergent topological invariant plus the total charges moving outside the region enclosed by BISs. We illustrate our results by numerically calculating the 2D quantum anomalous Hall model. This work broadens the way to classify topological phases by non-equilibrium quantum dynamics, and has feasibility for experimental realization.

cond-mat.mes-hall↗
arXiv2019

Observing topological charges and dynamical bulk-surface correspondence with ultracold atoms

In quenching a topological phase across phase transition, the dynamical bulk-surface correspondence emerges that the bulk topology of $d$-dimensional ($d$D) phase relates to the nontrivial pattern of quench dynamics emerging on $(d-1)$D subspace, called band inversion surfaces (BISs) in momentum space. Here we report the first experimental observation of the dynamical bulk-surface correspondence through measuring the topological charges in a 2D quantum anomalous Hall model realized in an optical Raman lattice. The system can be quenched with respect to every spin axis by suddenly varying the two-photon detuning or phases of the Raman couplings, in which the topological charges and BISs are measured dynamically by the time-averaged spin textures. We observe that the total charges in the region enclosed by BISs define a dynamical topological invariant, which equals the Chern index of the post-quench band. The topological charges relate to an emergent dynamical field which exhibits nontrivial topology on BIS, rendering the dynamical bulk-surface correspondence. This study opens a new avenue to explore topological phases dynamically.

cond-mat.quant-gas↗