arXiv subjects

Hang Liu

Publications and source records attributed to Hang Liu.

At least 163 records · Page 9Linked to original sources

arXiv2020

Quantum key distribution with dissipative Kerr soliton generated by on-chip microresonators

Quantum key distribution (QKD) can distribute symmetric key bits between remote legitimate users with the guarantee of quantum mechanics principles. For practical applications, the compact and robust photonic components for QKD are essential, and there are increasing attention to integrate the source, detector and modulators on a photonic chip. However, the massive and parallel QKD based on wavelength multiplexing are still challenge, due to the limited coherent light sources on the chip. Here, we introduce the Kerr dissipative soliton in a microresonator, which provides the locked coherent frequency comb with 49GHz frequency spacing, for QKD. We demonstrate the parallel QKD by demulplexing the coherent comb lines form the soliton, and showing the potential of Gbps secret key rate if the hundreds of channels covering C and L bands are fully exploited. The demonstrated soliton based QKD architecture are compatible with the efforts of quantum photonic integrated circuits, which are compact, robust and low-cost, and provides a competitive platform of practical QKD chip.

quant-ph↗

arXiv2020

Statistical Beamforming for FDD Downlink Massive MIMO via Spatial Information Extraction and Beam Selection

In this paper, we study the beamforming design problem in frequency-division duplexing (FDD) downlink massive MIMO systems, where instantaneous channel state information (CSI) is assumed to be unavailable at the base station (BS). We propose to extract the information of the angle-of-departures (AoDs) and the corresponding large-scale fading coefficients (a.k.a. spatial information) of the downlink channel from the uplink channel estimation procedure, based on which a novel downlink beamforming design is presented. By separating the subpaths for different users based on the spatial information and the hidden sparsity of the physical channel, we construct near-orthogonal virtual channels in the beamforming design. Furthermore, we derive a sum-rate expression and its approximations for the proposed system. Based on these closed-form rate expressions, we develop two low-complexity beam selection schemes and carry out asymptotic analysis to provide valuable insights on the system design. Numerical results demonstrate a significant performance improvement of our proposed algorithm over the state-of-the-art beamforming approach.

cs.IT↗

arXiv2019

Double-Sparsity Learning Based Channel-and-Signal Estimation in Massive MIMO with Generalized Spatial Modulation

In this paper, we study joint antenna activity detection, channel estimation, and multiuser detection for massive multiple-input multiple-output (MIMO) systems with general spatial modulation (GSM). We first establish a double-sparsity massive MIMO model by considering the channel sparsity of the massive MIMO channel and the signal sparsity of GSM. Based on the double-sparsity model, we formulate a blind detection problem. To solve the blind detection problem, we develop message-passing based blind channel-and-signal estimation (BCSE) algorithm. The BCSE algorithm basically follows the affine sparse matrix factorization technique, but with critical modifications to handle the double-sparsity property of the model. We show that the BCSE algorithm significantly outperforms the existing blind and training-based algorithms, and is able to closely approach the genie bounds (with either known channel or known signal). In the BCSE algorithm, short pilots are employed to remove the phase and permutation ambiguities after sparse matrix factorization. To utilize the short pilots more efficiently, we further develop the semi-blind channel-and-signal estimation (SBCSE) algorithm to incorporate the estimation of the phase and permutation ambiguities into the iterative message-passing process. We show that the SBCSE algorithm substantially outperforms the counterpart algorithms including the BCSE algorithm in the short-pilot regime.

cs.IT↗

arXiv2019

Mahler measure of polynomials defining genus 2 and 3 curves

In this article, we study the Mahler measures of more than 500 families of reciprocal polynomials defining genus 2 and genus 3 curves. We numerically find relations between the Mahler measures of these polynomials with special values of $L$-functions. We also numerically discover more than 100 identities between Mahler measures involving different families of polynomials defining genus 2 and genus 3 curves. Furthermore, we study the Mahler measures of several families of nonreciprocal polynomials defining genus 2 curves and numerically find relations between the Mahler measures of these families and special values of $L$-functions of elliptic curves. We also find identities between the Mahler measures of these nonreciprocal families and tempered polynomials defining genus 1 curves. We will explain these relations by considering the pushforward and pullback of certain elements in $K_2$ of curves defined by these polynomials and applying Beilinson's conjecture on $K_2$ of curves. We show that there are two and three explicit linearly independent elements in $K_2$ of certain families of genus 2 and genus 3 curves.

math.NT↗

arXiv2019

Excited quantum Hall effect: enantiomorphic flat bands in a Yin-Yang Kagome lattice

Quantum Hall effect (QHE) is one of the most fruitful research topics in condensed-matter physics. Ordinarily, the QHE manifests in a ground state with time-reversal symmetry broken by magnetization to carry a quantized chiral edge conductivity around a two-dimensional insulating bulk. We propose a theoretical concept and model of non-equilibrium excited-state QHE (EQHE) without intrinsic magnetization. It arises from circularly polarized photoexcitation between two enantiomorphic flat bands of opposite chirality, each supporting originally a helical topological insulating state hosted in a Yin-Yang Kagome lattice. The chirality of its edge state can be reversed by the handedness of light, instead of the direction of magnetization as in the conventional quantum (anomalous) Hall effect, offering a simple switching mechanism for quantum devices. Implications and realization of EQHE in real materials are discussed.

cond-mat.mtrl-sci↗

arXiv2019

Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with One-Dimensional Antenna Array

In this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in massive MIMO systems. The state-of-the-art approach utilizes the structured channel sparsity by sampling the angular-domain channel representation with a uniform angle-sampling grid, a.k.a. virtual channel representation. However, this approach is only applicable to uniform linear arrays and may cause a substantial performance loss due to the mismatch between the virtual representation and the true angle information. To tackle these challenges, we propose a sparse channel representation with a super-resolution sampling grid and a hidden Markovian support. Based on this, we develop a novel approximate inference based blind estimation algorithm to estimate the channel and the user signals simultaneously, with emphasis on the adoption of the expectation-maximization method to learn the angle information. Furthermore, we demonstrate the low-complexity implementation of our algorithm, making use of factor graph and message passing principles to compute the marginal posteriors. Numerical results show that our proposed method significantly reduces the estimation error compared to the state-of-the-art approach under various settings, which verifies the efficiency and robustness of our method.

cs.IT↗

arXiv2019

Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach

With the cellular networks becoming increasingly agile, a major challenge lies in how to support diverse services for mobile users (MUs) over a common physical network infrastructure. Network slicing is a promising solution to tailor the network to match such service requests. This paper considers a system with radio access network (RAN)-only slicing, where the physical infrastructure is split into slices providing computation and communication functionalities. A limited number of channels are auctioned across scheduling slots to MUs of multiple service providers (SPs) (i.e., the tenants). Each SP behaves selfishly to maximize the expected long-term payoff from the competition with other SPs for the orchestration of channels, which provides its MUs with the opportunities to access the computation and communication slices. This problem is modelled as a stochastic game, in which the decision makings of a SP depend on the global network dynamics as well as the joint control policy of all SPs. To approximate the Nash equilibrium solutions, we first construct an abstract stochastic game with the local conjectures of channel auction among the SPs. We then linearly decompose the per-SP Markov decision process to simplify the decision makings at a SP and derive an online scheme based on deep reinforcement learning to approach the optimal abstract control policies. Numerical experiments show significant performance gains from our scheme.

cs.NI↗

arXiv2019

Strong Cosmic Censorship in Charged de Sitter spacetime with Scalar Field Non-minimally Coupled to Curvature

We examine the stability and the strong cosmic censorship in the Reissner-Nordstrom-de Sitter (RN-dS) black hole by investigating the evolution of a scalar field non-minimally coupled to the curvature. We find that when the coupling parameter is negative, the RN-dS black hole experiences instability. The instability disappears when the coupling parameter becomes non-negative. With the increase of the coupling parameter, the violation of the strong cosmic censorship occurs at a larger critical charge ratio. But such an increase of the critical charge is suppressed by the increase of the cosmological constant. Different from the minimal coupling situation, it is possible to accommodate $β\ge1$ in the near extremal black hole when the scalar field is non-minimally coupled to curvature. The increase of the cosmological constant can allow $β\ge1$ to be satisfied for even smaller value of the coupling parameter. The existence of $β\ge1$ implies that the resulting curvature can continuously cross the Cauchy horizon.

gr-qc↗

arXiv2019

Fermionic analogue of black hole radiation with a super high Hawking temperature

Measurement of gravitational Hawking radiation of black hole (BH) is prohibitive because of an extremely low Hawking temperature (TH). Here we demonstrate a fermionic analog of BH with a super high TH ~ 3 K, which is several orders of magnitude higher than previous works. We propose that Floquet-Dirac states, formed in a periodically laser driven two-dimensional black phosphorous thin film, can be designed with a spatial gradient to mimic the "gravity" felt by fermionic quasiparticles as that for a Schwarzschild BH (SBH). Quantum tunneling of electrons from a type-II Dirac cone (inside BH) to a type-I Dirac cone (outside) emits a SBH-like Hawking radiation spectrum.

cond-mat.mes-hall↗

arXiv2019

Strong Cosmic Censorship in higher-dimensional Reissner-Nordström-de Sitter spacetime

It was recently shown that Strong Cosmic Censorship might be violated for near-extremally-charged black holes in 4-dimensional de Sitter space under scalar perturbations. Here, we extend the study of neutral massless scalar perturbations in higher dimensions and discuss the dimensional influence on the validity of Strong Cosmic Censorship hypothesis. By giving an elaborate description of neutral massless scalar perturbations of Reissner-Nordström-de Sitter black holes in $d=4,5$ and $6$ dimensions we conclude that Strong Cosmic Censorship is violated near extremality.

gr-qc↗

arXiv2019

Engineering Dirac states in graphene: Coexisting type-I and type-II Floquet-Dirac fermions

The coupling of monochromatic light fields and solids introduces nonequilibrium Floquet states, offering opportunities to create and explore new topological phenomena. Using combined first-principles and Floquet analysis we show that one can freely engineer Floquet-Dirac fermions (FDFs) in graphene by tuning the frequency and intensity of linearly polarized light. Not only type-II FDFs are created, but they also coexist with type-I FDFs near the Fermi level. Intriguingly, novel topologically nontrivial edge states connecting type-I and type-II Floquet-Dirac points emerge in photodriven graphene, providing an ideal channel to realize electron transport between the two types of Dirac states. Simulating time- and angle-resolved photoelectron spectroscopy suggests that the new coexisting state of type-I and type-II fermions is experimentally accessible. This work implies that a rich FDF phenomenon can be engineered in atomically thin graphene, hinting for developments of novel optoelectronic and quantum computing devices.

cond-mat.str-el↗

arXiv2019

Cooperative evolution of intraband and interband excitations for high harmonic generation in strained MoS2

Modulating electronic structure of two-dimensional (2D) materials represents an exciting avenue for tailoring their optoelectronic properties. Here, we identify a strain-induced, cooperative effect of intraband and interband excitations contributing to high harmonic generation (HHG) in prototype dichalcogenide MoS2 monolayer. We find that besides the dominant intraband contributions, interband current is also indispensable in modulating HHG. The HHG yields increase linearly with the compressive strain since flatter band dispersion and Berry curvature enhance both interband and intraband dynamics. Band structure can be retrieved with high reliability by monitoring the strain-induced evolution of HHG spectra, suggesting that strain not only provides an additional knob to control HHG in solids, but also marks a way towards a complete understanding of underlying microscopic mechanisms.

cond-mat.mes-hall↗

arXiv2018

SIMD-X: Programming and Processing of Graph Algorithms on GPUs

With high computation power and memory bandwidth, graphics processing units (GPUs) lend themselves to accelerate data-intensive analytics, especially when such applications fit the single instruction multiple data (SIMD) model. However, graph algorithms such as breadth-first search and k-core, often fail to take full advantage of GPUs, due to irregularity in memory access and control flow. To address this challenge, we have developed SIMD-X, for programming and processing of single instruction multiple, complex, data on GPUs. Specifically, the new Active-Compute-Combine (ACC) model not only provides ease of programming to programmers, but more importantly creates opportunities for system-level optimizations. To this end, SIMD-X utilizes just-in-time task management which filters out inactive vertices at runtime and intelligently maps various tasks to different amount of GPU cores in pursuit of workload balancing. In addition, SIMD-X leverages push-pull based kernel fusion that, with the help of a new deadlock-free global barrier, reduces a large number of computation kernels to very few. Using SIMD-X, a user can program a graph algorithm in tens of lines of code, while achieving 3?, 6?, 24?, 3? speedup over Gunrock, Galois, CuSha, and Ligra, respectively.

cs.DC↗

arXiv2018

Screening magnetic two-dimensional atomic crystals with nontrivial electronic topology

To date only a few two-dimensional (2D) magnetic crystals were experimentally confirmed, such as CrI3 and CrGeTe3, all with very low Curie temperatures (TC). High-throughput first-principles screening over a large set of materials yields 89 magnetic monolayers including 56 ferromagnetic (FM) and 33 antiferromagnetic compounds. Among them, 24 FM monolayers are promising candidates possessing TC higher than that of CrI3. High TC monolayers with fascinating electronic phases are identified: (i) quantum anomalous and valley Hall effects coexist in a single material RuCl3 or VCl3, leading to a valley-polarized quantum anomalous Hall state; (ii) TiBr3, Co2NiO6 and V2H3O5 are revealed to be half-metals. More importantly, a new type of fermion dubbed type-II Weyl ring is discovered in ScCl. Our work provides a database of 2D magnetic materials, which could guide experimental realization of high-temperature magnetic monolayers with exotic electronic states for future spintronics and quantum computing applications.

cond-mat.mtrl-sci↗

arXiv2018

A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns

This letter presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view in a panoramic RGB-D camera system. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a 360$^\circ$ field of view using RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach, both superior to those of existing methods (800 ms vs. 5 seconds; rotation error of 0.56 degrees vs. 1.6 degrees; and translation error of 1.80 cm vs. 2.5 cm.

eess.IV↗

arXiv2018

Multipath Transmission Scheduling in Millimeter Wave Cloud Radio Access Networks

Millimeter wave (mmWave) communications provide great potential for next-generation cellular networks to meet the demands of fast-growing mobile data traffic with plentiful spectrum available. However, in a mmWave cellular system, the shadowing and blockage effects lead to the intermittent connectivity, and the handovers are more frequent. This paper investigates an ``all-mmWave'' cloud radio access network (cloud-RAN), in which both the fronthaul and the radio access links operate at mmWave. To address the intermittent transmissions, we allow the mobile users (MUs) to establish multiple connections to the central unit over the remote radio heads (RRHs). Specifically, we propose a multipath transmission framework by leveraging the ``all-mmWave'' cloud-RAN architecture, which makes decisions of the RRH association and the packet transmission scheduling according to the time-varying network statistics, such that a MU experiences the minimum queueing delay and packet drops. The joint RRH association and transmission scheduling problem is formulated as a Markov decision process (MDP). Due to the problem size, a low-complexity online learning scheme is put forward, which requires no a priori statistic information of network dynamics. Simulations show that our proposed scheme outperforms the state-of-art baselines, in terms of average queue length and average packet dropping rate.

cs.NI↗

arXiv2018

Construction of all-in-focus images assisted by depth sensing

Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a color camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.

cs.CV↗

arXiv2018

Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers

Shrinking transistors, which powered the advancement of computing in the past half century, has stalled due to power wall; now extreme heterogeneity is promised to be the next driving force to feed the needs of ever-increasingly diverse scientific domains. To unlock the potentials of such supercomputers, we identify eight potential challenges in three categories: First, one needs fast data movement since extreme heterogeneity will inevitably complicate the communication circuits -- thus hampering the data movement. Second, we need to intelligently schedule suitable hardware for corresponding applications/stages. Third, we have to lower the programming complexity in order to encourage the adoption of heterogeneous computing.

cs.DC↗