arXiv subjects

Qiang Li

Publications and source records attributed to Qiang Li.

At least 469 records · Page 26Linked to original sources

arXiv2019

Tuning from failed superconductor to failed insulator with magnetic field

Do charge modulations compete with electron pairing in high-temperature copper-oxide superconductors? We investigated this question by suppressing superconductivity in a stripe-ordered cuprate compound at low temperature with high magnetic fields. With increasing field, loss of three-dimensional superconducting order is followed by reentrant two-dimensional superconductivity and then an ultra-quantum metal phase. Circumstantial evidence suggests that the latter state is bosonic and associated with the charge stripes. These results provide experimental support to the theoretical perspective that local segregation of doped holes and antiferromagnetic spin correlations underlies the electron-pairing mechanism in cuprates.

cond-mat.supr-con↗

arXiv2019

All-optical nanoscale heating and thermometry with resonant dielectric nanoparticles for photoinduced tumor treatment

All-dielectric nanophotonics becomes a versatile tool for various optical applications, including nanothermometry and optical heating. Its general concept includes excitation of Mie resonances in nonplasmonic nanoparticles. However, the potential of resonant dielectric nanoparticles in drug delivery applications still have not been fully realized. Here, optically resonant dielectric iron oxide nanoparticles ($α$-Fe$_2$O$_3$ NPs) are employed for remote rupture of microcontainers used as drug delivery platform. It is theoretically and experimentally demonstrated, that $α$-Fe$_2$O$_3$ NPs has several advantages in light-to-heat energy conversion comparing to previously used materials, such as noble metals and silicon, due to the broader spectral range of efficient optical heating, and in enhancement of thermally sensitive Raman signal. The $α$-Fe$_2$O$_3$ NPs embedded into the wall of universal drug carriers, polymer capsules, are used to experimentally determine the local temperature of the capsule rupture upon laser irradiation (170$^o$C). As a proof of principle, we successfully show the delivery and remote release of anticancer drug vincristine upon lowered laser irradiation (4.0$\times$10$^4$~W/cm$^2$) using polymer capsules modified with the $α$-Fe$_2$O$_3$ NPs. The biological tests were performed on two primary cell types: (i) carcinoma cells, as an example of malignant tumor, and (ii) human stem cells, as a model of healthy cells. The developed delivery system consisting of polymer capsules modified with the dielectric nanoparticles provides multifunctional platform for remote drug release and temperature detection.

physics.med-ph↗

arXiv2019

Galactic rotation curves in Einstein's conformal gravity

We show quantitatively that an exact solution of Einstein's conformal gravity can explain very well the galactic rotation curves for a sample of 104 galaxies without need for dark matter or other exotic modification of gravity. The metric is an overall rescaling of the Schwarzschild-de Sitter spacetime as required by Weyl conformal invariance, which has to be spontaneously broken, and the velocity of the stars depends only on two universal parameters determined on the base of the observational data.

gr-qc↗

arXiv2019

Molecular environs and triggered star formation around the large Galactic infrared bubble N 24

A multi-wavelength analysis of the large Galactic infrared bubble N 24 is has been presented in this paper in order to investigate the molecular and star formation environment around expanding HII regions. Using archival data from Herschel and ATLASGAL, the distribution and physical properties of the dust over the entire bubble are studied. Twenty three dense clumps are identified using the Clumpfind2d algorithm with sizes and masses in the range 0.65-1.73 pc and 600-16300 Msun, respectively. To analyse the molecular environment in N 24, observations of NH3 (1,1) and (2,2) were carried out using the Nanshan 26m radio telescope. Analysis of the kinetic temperature and gravitational stability of these clumps suggests gravitational collapse in several of them. The mass-size distributions of the clumps and the presence of massive young protostars indicate that the shell of N 24 is a region of ongoing massive star formation. The compatibility of the dynamical and fragmentation time-scales and the overabundance of YSOs and clumps on the rim suggest that the collect and collapse mechanism is in play at the boundary of the bubble, but the existence of the IRDC at the edge of bubble indicates that radiation-driven implosion mechanism may also have played a role there.

astro-ph.GA↗

arXiv2019

Joint Long-Term Cache Allocation and Short-Term Content Delivery in Green Cloud Small Cell Networks

Recent years have witnessed an exponential growth of mobile data traffic, which may lead to a serious traffic burn on the wireless networks and considerable power consumption. Network densification and edge caching are effective approaches to addressing these challenges. In this study, we investigate joint long-term cache allocation and short-term content delivery in cloud small cell networks (C-SCNs), where multiple smallcell BSs (SBSs) are connected to the central processor via fronthaul and can store popular contents so as to reduce the duplicated transmissions in networks. Accordingly, a long-term power minimization problem is formulated by jointly optimizing multicast beamforming, BS clustering, and cache allocation under quality of service (QoS) and storage constraints. The resultant mixed timescale design problem is an anticausal problem because the optimal cache allocation depends on the future file requests. To handle it, a two-stage optimization scheme is proposed by utilizing historical knowledge of users' requests and channel state information. Specifically, the online content delivery design is tackled with a penalty-based approach, and the periodic cache updating is optimized with a distributed alternating method. Simulation results indicate that the proposed scheme significantly outperforms conventional schemes and performs extremely close to a genie-aided lower bound in the low caching region.

cs.IT↗

arXiv2019

Correlated Logistic Model With Elastic Net Regularization for Multilabel Image Classification

In this paper, we present correlated logistic (CorrLog) model for multilabel image classification. CorrLog extends conventional logistic regression model into multilabel cases, via explicitly modeling the pairwise correlation between labels. In addition, we propose to learn the model parameters of CorrLog with elastic net regularization, which helps exploit the sparsity in feature selection and label correlations and thus further boost the performance of multilabel classification. CorrLog can be efficiently learned, though approximately, by regularized maximum pseudo likelihood estimation, and it enjoys a satisfying generalization bound that is independent of the number of labels. CorrLog performs competitively for multilabel image classification on benchmark data sets MULAN scene, MIT outdoor scene, PASCAL VOC 2007, and PASCAL VOC 2012, compared with the state-of-the-art multilabel classification algorithms.

cs.CV↗

arXiv2019

PT-ISABB: A Hybrid Tree-based Complete Algorithm to Solve Asymmetric Distributed Constraint Optimization Problems

Asymmetric Distributed Constraint Optimization Problems (ADCOPs) have emerged as an important formalism in multi-agent community due to their ability to capture personal preferences. However, the existing search-based complete algorithms for ADCOPs can only use local knowledge to compute lower bounds, which leads to inefficient pruning and prohibits them from solving large scale problems. On the other hand, inference-based complete algorithms (e.g., DPOP) for Distributed Constraint Optimization Problems (DCOPs) require only a linear number of messages, but they cannot be directly applied into ADCOPs due to a privacy concern. Therefore, in the paper, we consider the possibility of combining inference and search to effectively solve ADCOPs at an acceptable loss of privacy. Specifically, we propose a hybrid complete algorithm called PT-ISABB which uses a tailored inference algorithm to provide tight lower bounds and a tree-based complete search algorithm to exhaust the search space. We prove the correctness of our algorithm and the experimental results demonstrate its superiority over other state-of-the-art complete algorithms.

cs.MA↗

arXiv2019

Adapting Stochastic Block Models to Power-Law Degree Distributions

Stochastic block models (SBMs) have been playing an important role in modeling clusters or community structures of network data. But, it is incapable of handling several complex features ubiquitously exhibited in real-world networks, one of which is the power-law degree characteristic. To this end, we propose a new variant of SBM, termed power-law degree SBM (PLD-SBM), by introducing degree decay variables to explicitly encode the varying degree distribution over all nodes. With an exponential prior, it is proved that PLD-SBM approximately preserves the scale-free feature in real networks. In addition, from the inference of variational E-Step, PLD-SBM is indeed to correct the bias inherited in SBM with the introduced degree decay factors. Furthermore, experiments conducted on both synthetic networks and two real-world datasets including Adolescent Health Data and the political blogs network verify the effectiveness of the proposed model in terms of cluster prediction accuracies.

cs.SI↗

arXiv2019

StyleRemix: An Interpretable Representation for Neural Image Style Transfer

Multi-Style Transfer (MST) intents to capture the high-level visual vocabulary of different styles and expresses these vocabularies in a joint model to transfer each specific style. Recently, Style Embedding Learning (SEL) based methods represent each style with an explicit set of parameters to perform MST task. However, most existing SEL methods either learn explicit style representation with numerous independent parameters or learn a relatively black-box style representation, which makes them difficult to control the stylized results. In this paper, we outline a novel MST model, StyleRemix, to compactly and explicitly integrate multiple styles into one network. By decomposing diverse styles into the same basis, StyleRemix represents a specific style in a continuous vector space with 1-dimensional coefficients. With the interpretable style representation, StyleRemix not only enables the style visualization task but also allows several ways of remixing styles in the smooth style embedding space.~Extensive experiments demonstrate the effectiveness of StyleRemix on various MST tasks compared to state-of-the-art SEL approaches.

cs.CV↗

arXiv2019

The Chiral Qubit: quantum computing with chiral anomaly

The quantum chiral anomaly enables a nearly dissipationless current in the presence of chirality imbalance and magnetic field -- this is the Chiral Magnetic Effect (CME), observed recently in Dirac and Weyl semimetals. Here we propose to utilize the CME for the design of qubits potentially capable of operating at THz frequency, room temperature, and the coherence time to gate time ratio of about $10^4$. The proposed "Chiral Qubit" is a micron-scale ring made of a Weyl or Dirac semimetal, with the $|0\rangle$ and $|1\rangle$ quantum states corresponding to the symmetric and antisymmetric superpositions of quantum states describing chiral fermions circulating along the ring clockwise and counter-clockwise. A fractional magnetic flux through the ring induces a quantum superposition of the $|0\rangle$ and $|1\rangle$ quantum states. The entanglement of qubits can be implemented through the near-field THz frequency electromagnetic fields.

quant-ph↗

arXiv2019

An ADMM-Based Approach to Robust Array Pattern Synthesis

In most existing robust array beam pattern synthesis studies, the bounded-sphere model is used to describe the steering vector (SV) uncertainties. In this letter, instead of bounding the norm of SV perturbations as a whole, we explore the amplitude and phase perturbations of each SV element separately, thereby obtaining a tighter SV uncertainty model. Based on this model, we formulate the robust array pattern synthesis problem from the perspective of the min-max optimization, which aims to minimize the maximum side lobe response, while preserving the main lobe response. However, this problem is difficult due to the infinitely many non-convex constraints. As a remedy, we employ the worst-case criterion and recast the problem as a convex second-order cone program (SOCP). To solve the SOCP, we further develop an alternating direction method of multipliers (ADMM)-based algorithm, which is computationally efficient with each step being computed in closed form. Numerical simulations demonstrate the efficacy and efficiency of the proposed algorithm.

cs.IT↗

arXiv2019

Precision Higgs Physics at CEPC

The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS and CMS Collaborations marked the beginning of a new era in high energy physics. The Higgs boson will be the subject of extensive studies of the ongoing LHC program. At the same time, lepton collider based Higgs factories have been proposed as a possible next step beyond the LHC, with its main goal to precisely measure the properties of the Higgs boson and probe potential new physics associated with the Higgs boson. The Circular Electron Positron Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an $e^+e^-$ circular collider proposed by and to be hosted in China. Located in a tunnel of approximately 100~km in circumference, it will operate at a center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we present the first estimates on the precision of the Higgs boson property measurements achievable at the CEPC and discuss implications of these measurements.

hep-ex↗

arXiv2019

Symbol-Based Multi-Layer Iterative Successive Interference Cancellation for Faster-Than-Nyquist Signaling

A symbol-based multi-layer iterative successive interference cancellation (MLISIC) algorithm is proposed to eliminate the inter-symbol interference (ISI) for faster-than-Nyquist (FTN) signaling. The computational complexity of the proposed MLISIC algorithm is much lower than most existing block-based estimation algorithms. By comparison with existing symbol-based algorithms, the proposed MLISIC algorithm has higher estimation accuracy. Furthermore, by means of utilizing more accurate symbols and elaborate length of successive interference cancellation, an improved MLISIC (IMLISIC) algorithm is presented to further promote the estimation accuracy. Simulation results show in mild ISI cases, the proposed MLISIC and IMLISIC algorithms can approximate the theoretical performance even using 256-amplitude phase shift keying (APSK) which is adopted in digital video broadcasting-satellite-second generation extension (DVB-S2X), i.e., bit error rate (BER) performance degradation is about 0.03 dB when the signal-to-noise ratio is high. In other words, using the proposed MLISIC and IMLISIC algorithms in mild ISI cases, the spectrum efficiency can be improved with negligible BER performance degradation. In moderate ISI cases, BER performance degradation of our proposed IMLISIC algorithm is no more than 0.13 dB when adopting 64/128/256-APSK, which is still satisfying. Besides, compared with existing symbol-based algorithms, the greater BER performance improvement can be achieved under severer ISI circumstances.

eess.SP↗

arXiv2019

Polarization fraction measurement in same-sign WW scattering using deep learning

Studying the longitudinally polarized fraction of $W^\pm W^\pm$ scattering at the LHC is crucial to examine the unitarization mechanism of the vector boson scattering amplitude through Higgs and possible new physics. We apply here for the first time a Deep Neural Network classification to extract the longitudinal fraction. Based on fast simulation implemented with the Delphes framework, significant improvement from a deep neural network is found to be achievable and robust over all dijet mass region. A conservative estimation shows that a high significance of four standard deviations can be reached with the High-Luminosity LHC designed luminosity of 3000 $fb^{-1}$

hep-ph↗

arXiv2018

On-demand generation of shallow silicon vacancy in silicon carbide

Defects in silicon carbide have been explored as promising spin systems in quantum technologies. However, for practical quantum metrology and quantum communication, it is critical to achieve the on-demand shallow spin-defect generation. In this work, we present the generation and characterization of shallow silicon vacancies in silicon carbide by using different implanted ions and annealing conditions. The conversion efficiency of silicon vacancy of helium ions is shown to be higher than that by carbon and hydrogen ions in a wide implanted fluence range. Furthermore, after optimizing annealing conditions, the conversion efficiency can be increased more than 2 times. Due to the high density of the generated ensemble defects, the sensitivity to sense a static magnetic field can be research as high as , which is about 15 times higher than previous results. By carefully optimizing implanted conditions, we further show that a single silicon vacancy array can be generated with about 80 % conversion efficiency, which reaches the highest conversion yield in solid state systems. The results pave the way for using on-demand generated shallow silicon vacancy for quantum information processing and quantum photonics.

quant-ph↗

arXiv2018

Coherent control of defect spins in silicon carbide above 550 K

Great efforts have been made to the investigation of defects in silicon carbide for their attractive optical and spin properties. However, most of the researches are implemented at low and room temperature. Little is known about the spin coherent property at high temperature. Here, we experimentally demonstrate coherent control of divacancy defect spins in silicon carbide above 550 K. The spin properties of defects ranging from room temperature to 600 K are investigated, in which the zero-field-splitting is found to have a polynomial temperature dependence and the spin coherence time decreases as the temperature increases. Moreover, as an example of application, we demonstrate a thermal sensing using the Ramsey method at about 450 K. Our experimental results would be useful for the investigation of high temperature properties of defect spins and silicon carbide-based broad-temperature range quantum sensing.

cond-mat.mes-hall↗

arXiv2018

Charged lepton flavor violating Higgs decays at future $e^+e^-$ colliders

After the discovery of the Higgs boson, several future experiments have been proposed to study the Higgs boson properties, including two circular lepton colliders, the CEPC and the FCC-ee, and one linear lepton collider, the ILC. We evaluate the precision reach of these colliders in measuring the branching ratios of the charged lepton flavor violating Higgs decays $H\to e^\pmμ^\mp$, $e^\pmτ^\mp$ and $μ^\pmτ^\mp$. The expected upper bounds on the branching ratios given by the circular (linear) colliders are found to be $\mathcal{B}(H\to e^\pmμ^\mp) < 1.2\ (2.1) \times 10^{-5}$, $\mathcal{B}(H\to e^\pmτ^\mp) < 1.6\ (2.4) \times 10^{-4}$ and $\mathcal{B}(H\to μ^\pmτ^\mp) < 1.4\ (2.3) \times 10^{-4}$ at 95\% CL, which are improved by one to two orders compared to the current experimental bounds. We also discuss the constraints that these upper bounds set on certain theory parameters, including the charged lepton flavor violating Higgs couplings, the corresponding parameters in the type-III 2HDM, and the new physics cut-off scales in the SMEFT, in RS models and in models with heavy neutrinos.

hep-ph↗

arXiv2018

Multiuser One-Bit Massive MIMO Precoding Under MPSK Signaling

Most recently, there has been a flurry of research activities on studying how massive MIMO precoding should be designed when the digital-to-analog conversion at the transmitter side is operated by cheap one-bit digital-to-analog converters (DACs). Such research is motivated by the desire to substantially cut down the hardware cost and power consumption of the radio-frequency chain, which is unaffordable in massive MIMO if high-resolution DACs are still used. One-bit MIMO precoding design problems are much harder to solve than their high-resolution DAC counterparts. In our previous work, we developed a minimum symbol-error probability (SEP) design for one-bit precoding under the multiuser MISO downlink scenario and under quadrature amplitude modulation signaling. Leveraging on the previous work, this work shows how the minimum SEP design is applied to M-ary phase shift keying (MPSK) signaling. Simulation results show that our minimum SEP design delivers significantly better bit-error rate (BER) performance than the other designs for higher-order PSK such as 8-PSK and 16-PSK. As a minor, but useful, side contribution, we also tackle an MPSK SEP characterization problem which was only intuitively treated in the prior arts.

cs.IT↗