arXiv subjects

Feng Liu

Publications and source records attributed to Feng Liu.

At least 685 records · Page 38Linked to original sources

arXiv2017

Tunable Bi-frustrated Electron Spin and Charge States in a Cu-Hexaaminobenzene Framework

A geometrically frustrated lattice may host frustrated electron spin or charge states that spawn exotic quantum phases. We show that a newly synthesized metal-organic framework of Cu-Hexaaminobenzene [Cu$_3$(HAB)$_2$] exhibits a multi spectra of unusual quantum phases long sought after in condensed matter physics. On one hand, the Cu$^{2+}$ ions form an ideal $S$-1/2 antiferromagnetic kagome lattice. On the other hand, the conjugated-electrons from the organic ligands give rise to completely dispersionless energy bands around the Fermi level, reproducing a frustrated $π_x$-$π_y$ hopping model on a honeycomb lattice. We propose to characterize the coexistence of frustrated local spins and conjugated electrons through scanning tunneling microscopy simulations. Most remarkably, their close energy proximity enables one to tune the system between the two frustrated states by doping up to one hole per HAB unit. Thus, Cu$_3$(HAB)$_2$ provides a unique exciting platform to investigate the interplay of frustrated spins and electrons in one single lattice, e.g. by gating experiments, which will undoubtedly raise interesting theoretical questions leading to possible new condensed-matter phases.

cond-mat.str-el↗

arXiv2017

Mitigating Blackout Risk via Maintenance : Inference from Simulation Data

Whereas maintenance has been recognized as an important and effective means for risk management in power systems, it turns out to be intractable if cascading blackout risk is considered due to the extremely high computational complexity. In this paper, based on the inference from the blackout simulation data, we propose a methodology to efficiently identify the most influential component(s) for mitigating cascading blackout risk in a large power system. To this end, we first establish an analytic relationship between maintenance strategies and blackout risk estimation by inferring from the data of cascading outage simulations. Then we formulate the component maintenance decision-making problem as a nonlinear 0-1 programming. Afterwards, we quantify the credibility of blackout risk estimation, leading to an adaptive method to determine the least required number of simulations, which servers as a crucial parameter of the optimization model. Finally, we devise two heuristic algorithms to find approximate optimal solutions to the model with very high efficiency. Numerical experiments well manifest the efficacy and high efficiency of our methodology.

math.OC↗

arXiv2017

Novel Topological Phase with Zero Berry Curvature

We present a two-dimensional (2D) lattice model that exhibits a nontrivial topological phase in the absence of the Berry curvature. Instead, the Berry connection provides the topological nontrivial phase in the model, whose integration over the momentum space, the so-called 2D Zak phase, yields a fractional wave polarization in each direction. These fractional wave polarizations manifest themselves as degenerated edge states with opposite parities in the model.

cond-mat.mes-hall↗

arXiv2017

Black Hole Horizon in a Type-III Dirac Semimetal Zn$_2$In$_2$S$_5$

Recently, realizing new fermions, such as type-I and type-II Dirac/Weyl fermions in condensed matter systems, has attracted considerable attention. Here we show that the transition state from type-I to type-II Dirac fermions can be viewed as a type-III Dirac fermion, which exhibits unique characteristics, including a Dirac-line Fermi surface with nontrivial topological invariant and critical chiral anomaly effect, distinct from previously known Dirac semimetals. Most importantly, we discover Zn$_2$In$_2$S$_5$ is a type-III Dirac semimetal material, characterized with a pair of Dirac points in the bulk and Fermi arcs on the surface. We further propose a solid-state realization of the black-hole-horizon analogue in inhomogeneous Zn$_2$In$_2$S$_5$ to simulate black hole evaporation with high Hawking temperature. We envision that our findings will stimulate researchers to study novel physics of type-III Dirac fermions, as well as astronomical problems in a condensed matter analogue.

cond-mat.mes-hall↗

arXiv2017

Management of Cascading Outage Risk Based on Risk Gradient and Markovian Tree Search

Since cascading outages are major threats to power systems, it is important to reduce the risk of potential cascading outages. In this paper, a risk management method of cascading outages based on Markovian tree search is proposed. With the tree expansion on the cascading outage risk, risk gradient is computed efficiently by a forward-backward tree search scheme with good convergence, and it is then employed in an optimization model to minimize control cost while effectively reducing the cascading outage risk. To overcome the limitation with linearization in computing risk gradient, an iterative risk management (IRM) approach is further developed. Tests on the RTS-96 3-area system verify the accuracy of the computed risk gradient and its effectiveness for risk reduction. Time performance of the proposed IRM approach is tested on the RTS-96 system, a 410-bus US-Canada northeast system and a 1354-bus Mid-European system, and demonstrates its potentials for decision support on practical power systems online or on hourly basis.

eess.SY↗

arXiv2017

Quantifying the Influence of Component Failure Probability on Cascading Blackout Risk

The risk of cascading blackouts greatly relies on failure probabilities of individual components in power grids. To quantify how component failure probabilities (CFP) influences blackout risk (BR), this paper proposes a sample-induced semi-analytic approach to characterize the relationship between CFP and BR. To this end, we first give a generic component failure probability function (CoFPF) to describe CFP with varying parameters or forms. Then the exact relationship between BR and CoFPFs is built on the abstract Markov-sequence model of cascading outages. Leveraging a set of samples generated by blackout simulations, we further establish a sample-induced semi-analytic mapping between the unbiased estimation of BR and CoFPFs. Finally, we derive an efficient algorithm that can directly calculate the unbiased estimation of BR when the CoFPFs change. Since no additional simulations are required, the algorithm is computationally scalable and efficient. Numerical experiments well confirm the theory and the algorithm.

math.OC↗

arXiv2017

Photoinduced topological phase transitions in strained black phosphorus

Photoinduced topological phase transitions (TPTs) in black phosphorous (BP) under compressive strain were investigated by combining Floquet theory and first-principles calculations. Intriguing photo-dressed electronic states including Floquet-Dirac semimetals and Floquet topological insulators have been identified, which can be feasibly engineered by changing the direction, intensity and frequency of incident laser. Remarkably, tunable TPT from type-I to type-II Floquet-Dirac fermions can be realized by irradiating circularly polarized laser (CPL), with an origin rooted in optical Stark effect. Furthermore, the photoinduced Floquet-Dirac phases is shown to host topological surface states that exhibit nonequilibrium electron transport in a direction locked by the helicity of CPL. This work provides useful guidance for experimental observation of Floquet TPTs, and extends optoelectrionic applications of BP to nonequilibrium regime.

cond-mat.mtrl-sci↗

arXiv2017

Intelligence Quotient and Intelligence Grade of Artificial Intelligence

Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI and human characteristics in terms of four aspects of knowledge, i.e., input, output, mastery, and creation. Using this model, we observe three challenges, namely, expanding of the von Neumann architecture; testing and ranking the intelligence quotient of naturally and artificially intelligent systems, including humans, Google, Bing, Baidu, and Siri; and finally, the dividing of artificially intelligent systems into seven grades from robots to Google Brain. Based on this, we conclude that AlphaGo belongs to the third grade.

cs.AI↗

arXiv2017

Impacts and Benefits of UPFC to Wind Power Integration in Unit Commitment

Unified Power Flow Controller (UPFC) is recognized as the most powerful flexible AC transmission systems (FACTS) device for power system operation. This paper addresses how UPFC explores the transmission flexibility and facilitates the integration of uncertain and volatile wind power generation. To this end, a comprehensive unit commitment (UC) model with UPFC and uncertain wind power generation is proposed. Then, some metrics are introduced to evaluate the impacts of UPFC on the reliability, security and economy of power system operation. Further, different dispatch strategies of UPFC are compared to provide helpful guidances on making full use of UPFC to hedge against uncertainties. In addition, facing the challenging mixed-integer non-linear non-convex problems, approximate models are proposed to provide a starting point to solve the problems efficiently. All these models are easy to adapt to other types of FACTS devices. Illustrative numerical results are provided.

math.OC↗

arXiv2017

Efficient Simulation of Temperature Evolution of Overhead Transmission Lines Based on Analytical Solution and NWP

Transmission lines are vital components in power systems. Tripping of transmission lines caused by over-temperature is a major threat to the security of system operations, so it is necessary to efficiently simulate line temperature under both normal operation conditions and foreseen fault conditions. Existing methods based on thermal-steady-state analyses cannot reflect transient temperature evolution, and thus cannot provide timing information needed for taking remedial actions. Moreover, conventional numerical method requires huge computational efforts and barricades system-wide analysis. In this regard, this paper derives an approximate analytical solution of transmission-line temperature evolution enabling efficient analysis on multiple operation states. Considering the uncertainties in environmental parameters, the region of over-temperature is constructed in the environmental parameter space to realize the over-temperature risk assessment in both the planning stage and real-time operations. A test on a typical conductor model verifies the accuracy of the approximate analytical solution. Based on the analytical solution and numerical weather prediction (NWP) data, an efficient simulation method for temperature evolution of transmission systems under multiple operation states is proposed. As demonstrated on an NPCC 140-bus system, it achieves over 1000 times of efficiency enhancement, verifying its potentials in online risk assessment and decision support.

cs.CE↗

arXiv2017

Risk-limiting Load Restoration for Resilience Enhancement with Intermittent Energy Resources

Microgrids are resources that can be used to restore critical loads after a natural disaster, enhancing resilience of a distribution network. To deal with the stochastic nature of intermittent energy resources, such as wind turbines (WTs) and photovoltaics (PVs), many methods rely on forecast information. However, some microgrids may not be equipped with power forecasting tools. To fill this gap, a risk-limiting strategy based on measurements is proposed. Gaussian mixture model (GMM) is used to represent a prior joint probability density function (PDF) of power outputs of WTs and PVs over multiple periods. As time rolls forward, the distribution of WT/PV generation is updated based the latest measurement data in a recursive manner. The updated distribution is used as an input for the risk-limiting load restoration problem, enabling an equivalent transformation of the original chance constrained problem into a mixed integer linear programming (MILP). Simulation cases on a distribution system with three microgrids demonstrate the effectiveness of the proposed method. Results also indicate that networked microgrids have better uncertainty management capabilities than stand-alone microgrids.

eess.SY↗

arXiv2017

Demonstration of Laser-produced Neutron Diagnostic by Radiative Capture Gamma-rays

We report a new scenario of time-of-flight (TOF) technique in which fast neutrons and delayed gamma-ray signals were both recorded in a millisecond time window in harsh environments induced by high-intensity lasers. The delayed gamma signals, arriving far later than the original fast neutron and often being ignored previously, were identified to be the results of radiative captures of thermalized neutrons. The linear correlation between gamma photon number and the fast neutron yield shows that these delayed gamma events can be employed for neutron diagnosis. This method can reduce the detecting efficiency dropping problem caused by prompt high-flux gamma radiation, and provides a new way for neutron diagnosing in high-intensity laser-target interaction experiments.

physics.ins-det↗

arXiv2017

Prediction of Ideal Topological Semimetals with Triply Degenerate Points in NaCu$_3$Te$_2$ Family

Triply degenerate points (TDPs) in band structure of a crystal can generate novel TDP fermions without high-energy counterparts. Although identifying ideal TDP semimetals, which host clean TDP fermions around the Fermi level ($E_F$) without coexisting of other quasiparticles, is critical to explore the intrinsic properties of this new fermion, it is still a big challenge and has not been achieved up to now. Here, we disclose an effective approach to search for ideal TDP semimetals via selective band crossing between antibonding $s$ and bonding $p$ orbitals along a line in the momentum space with $C_{3v}$ symmetry. Applying this approach, we have successfully identified the NaCu$_3$Te$_2$ family of compounds to be ideal TDP semimetals, where two and only two pairs of TDPs are located around the $E_F$. Moreover, we reveal an interesting mechanism to modulate energy splitting between a pair of TDPs, and illustrate the intrinsic features of TDP Fermi arcs in these ideal TDP semimetals.

cond-mat.mtrl-sci↗

arXiv2017

Electronic and spin dynamics in the insulating iron pnictide NaFe$_{0.5}$Cu$_{0.5}$As

NaFe$_{0.5}$Cu$_{0.5}$As represents a rare exception in the metallic iron pnictide family, in which a small insulating gap is opened. Based on first-principles study, we provide a comprehensive theoretical characterization of this insulating compound. The Fe$^{3+} $spin degree of freedom is quantified as a quasi-1D $S=\frac{5}{2}$ Heisenberg model. The itinerant As hole state is downfolded to a $p_{xy}$-orbital hopping model on a square lattice. A unique orbital-dependent Hund's coupling between the spin and the hole is revealed. Several important material properties are analyzed, including (a) factors affecting the small $p-d$ charge-transfer gap; (b) role of the extra interchain Fe; and (c) the quasi-1D spin excitation in the Fe chains. The experimental manifestations of these properties are discussed.

cond-mat.str-el↗

arXiv2017

Atomically Abrupt Topological p-n Junction

Topological insulators (TI's) are a new class of quantum matter with extraordinary surface electronic states, which bear great potential for spintronics and error-tolerant quantum computing. In order to put a TI into any practical use, these materials need to be fabricated into devices whose basic units are often p-n junctions. Unique electronic properties of a 'topological' p-n junction were proposed theoretically such as the junction electronic state and the spin rectification. However, the fabrication of a lateral topological p-n junction has been challenging because of materials, process, and fundamental reasons. Here, we demonstrate an innovative approach to realize a p-n junction of topological surface states (TSS's) of a three-dimensional (3D) topological insulator (TI) with an atomically abrupt interface. When a ultrathin Sb film is grown on a 3D TI of Bi2Se3 with a typical n-type TSS, the surface develops a strongly p-type TSS through the substantial hybridization between the 2D Sb film and the Bi2Se3 surface. Thus, the Bi2Se3 surface covered partially with Sb films bifurcates into areas of n- and p-type TSS's as separated by atomic step edges with a lateral electronic junction of as short as 2 nm. This approach opens a different avenue toward various electronic and spintronic devices based on well defined topological p-n junctions with the scalability down to atomic dimensions

cond-mat.mtrl-sci↗

arXiv2017

Optimal Power Flow in Stand-alone DC Microgrids

Direct-current microgrids (DC-MGs) can operate in either grid-connected or stand-alone mode. In particular, stand-alone DC-MG has many distinct applications. However, the optimal power flow problem of a stand-alone DC-MG is inherently non-convex. In this paper, the optimal power flow (OPF) problem of DC-MG is investigated considering convex relaxation based on second-order cone programming (SOCP). Mild assumptions are proposed to guarantee the exactness of relaxation, which only require uniform nodal voltage upper bounds and positive network loss. Furthermore, it is revealed that the exactness of SOCP relaxation of DC-MGs does not rely on either topology or operating mode of DC-MGs, and an optimal solution must be unique if it exists. If line constraints are considered, the exactness of SOCP relaxation may not hold. In this regard, two heuristic methods are proposed to give approximate solutions. Simulations are conducted to confirm the theoretic results.

math.OC↗

arXiv2017

Video Frame Interpolation via Adaptive Separable Convolution

Standard video frame interpolation methods first estimate optical flow between input frames and then synthesize an intermediate frame guided by motion. Recent approaches merge these two steps into a single convolution process by convolving input frames with spatially adaptive kernels that account for motion and re-sampling simultaneously. These methods require large kernels to handle large motion, which limits the number of pixels whose kernels can be estimated at once due to the large memory demand. To address this problem, this paper formulates frame interpolation as local separable convolution over input frames using pairs of 1D kernels. Compared to regular 2D kernels, the 1D kernels require significantly fewer parameters to be estimated. Our method develops a deep fully convolutional neural network that takes two input frames and estimates pairs of 1D kernels for all pixels simultaneously. Since our method is able to estimate kernels and synthesizes the whole video frame at once, it allows for the incorporation of perceptual loss to train the neural network to produce visually pleasing frames. This deep neural network is trained end-to-end using widely available video data without any human annotation. Both qualitative and quantitative experiments show that our method provides a practical solution to high-quality video frame interpolation.

cs.CV↗

arXiv2017

Cumulants of event-by-event net-strangeness distributions in Au+Au collisions at $\sqrt{s_\mathrm{NN}}$=7.7-200 GeV from UrQMD model

Fluctuations of conserved quantities, such as baryon, electric charge and strangeness number, are sensitive observables in heavy-ion collisions to search for the QCD phase transition and critical point. In this paper, we performed a systematical analysis on the various cumulants and cumulant ratios of event-by-event net-strangeness distributions in Au+Au collisions at $\sqrt{s_{NN}}$=7.7, 11.5, 19.6, 27, 39, 62.4 and 200 GeV from UrQMD model. We performed a systematical study on the contributions from various strange baryons and mesons to the net-strangeness fluctuations. The results demonstrate that the cumulants and cumulant ratios of net-strangeness distributions extracted from different strange particles show very different centrality and energy dependence behavior. By comparing with the net-kaon fluctuations, we found that the strange baryons play an important role in the fluctuations of net-strangeness. This study can provide useful baselines to study the QCD phase transition and search for the QCD critical point by using the fluctuations of net-strangeness in heavy-ion collisions experiment. It can help us to understand non-critical physics contributions to the fluctuations of net-strangeness.

nucl-ex↗