arXiv subjects

Hui Wang

Publications and source records attributed to Hui Wang.

At least 469 records · Page 26Linked to original sources

arXiv2018

Approximation by filter functions

In this exploratory article, we draw attention to the common formal ground among various estimators such as the belief functions of evidence theory and their relatives, approximation quality of rough set theory, and contextual probability. The unifying concept will be a general filter function composed of a basic probability and a weighting which varies according to the problem at hand. To compare the various filter functions we conclude with a simulation study with an example from the area of item response theory.

cs.AI↗

arXiv2018

Two-dimensional optomechanics formed by the graphene sheet and photonic crystal cavity

We theoretically study photon transmission and mechanical ground state cooling in a two-dimensional optomechanical system that is formed of a suspended graphene sheet on an one-dimensional optomechanical crystal. When the frequencies of graphene resonator and nanobeam resonator(phononic mode of optomechanical crystal) are approximately the same, the $Λ$-type degenerate four-level system of two-dimensional optomechanics shows two-color optomechanically-induced transparency , and the transparency window could be switched among probe signal's absorption, transparency, and amplification. According to our calculations, the graphene resonator could also effectively assist the ground state cooling of large damping nanobeam resonator in two-dimensional optomechanics.

quant-ph↗

arXiv2018

Monte Carlo Q-learning for General Game Playing

After the recent groundbreaking results of AlphaGo, we have seen a strong interest in reinforcement learning in game playing. General Game Playing (GGP) provides a good testbed for reinforcement learning. In GGP, a specification of games rules is given. GGP problems can be solved by reinforcement learning. Q-learning is one of the canonical reinforcement learning methods, and has been used by (Banerjee & Stone, IJCAI 2007) in GGP. In this paper we implement Q-learning in GGP for three small-board games (Tic-Tac-Toe, Connect Four, Hex), to allow comparison to Banerjee et al. As expected, Q-learning converges, although much slower than MCTS. Borrowing an idea from MCTS, we enhance Q-learning with Monte Carlo Search, to give QM-learning. This enhancement improves the performance of pure Q-learning. We believe that QM-learning can also be used to improve performance of reinforcement learning further for larger games, something which we will test in future work.

cs.AI↗

arXiv2018

Hydrogen as a Source of Flux Noise in SQUIDs

Superconducting qubits are hampered by flux noise produced by surface spins from a variety of microscopic sources. Recent experiments indicated that hydrogen (H) atoms may be one of those sources. Using density functional theory calculations, we report that H atoms either embedded in, or adsorbed on, an a-Al2O3(0001) surface have sizeable spin moments ranging from 0.81 to 0.87 uB with energy barriers for spin reorientation as low as ~10 mK. Furthermore, H adatoms on the surface attract gas molecules such as O2, producing new spin sources. We propose coating the surface with graphene to eliminate H-induced surface spins and to protect the surface from other adsorbates.

cond-mat.mtrl-sci↗

arXiv2018

Likelihood for transcriptions in a genetic regulatory system under asymmetric stable Lévy noise

This work is devoted to investigating the evolution of concentration in a genetic regulation system, when the synthesis reaction rate is under additive and multiplicative asymmetric stable Lévy fluctuations. By focusing on the impact of skewness (i.e., non-symmetry) in the probability distributions of noise, we find that via examining the mean first exit time (MFET) and the first escape probability (FEP), the asymmetric fluctuations, interacting with nonlinearity in the system, lead to peculiar likelihood for transcription. This includes, in the additive noise case, realizing higher likelihood of transcription for larger positive skewness (i.e., asymmetry) index $β$, causing a stochastic bifurcation at the non-Gaussianity index value $α=1$ (i.e., it is a separating point or line for the likelihood for transcription), and achieving a turning point at the threshold value $β\approx -0.5$ (i.e., beyond which the likelihood for transcription suddenly reversed for $α$ values). The stochastic bifurcation and turning point phenomena do not occur in the symmetric noise case ($β=0$). While in the multiplicative noise case, non-Gaussianity index value $α=1$ is a separating point or line for both the mean first exit time (MFET) and the first escape probability (FEP). We also investigate the noise enhanced stability phenomenon. Additionally, we are able to specify the regions in the whole parameter space for the asymmetric noise, in which we attain desired likelihood for transcription. We have conducted a series of numerical experiments in `regulating' the likelihood of gene transcription by tuning asymmetric stable Lévy noise indexes. This work offers insights for possible ways of achieving gene regulation in experimental research.

physics.bio-ph↗

arXiv2018

Toward Scalable Boson Sampling with Photon Loss

Boson sampling is a well-defined task that is strongly believed to be intractable for classical computers, but can be efficiently solved by a specific quantum simulator. However, an outstanding problem for large-scale experimental boson sampling is the scalability. Here we report an experiment on boson sampling with photon loss, and demonstrate that boson sampling with a few photons lost can increase the sampling rate. Our experiment uses a quantum-dot-micropillar single-photon source demultiplexed into up to seven input ports of a 16*16 mode ultra-low-loss photonic circuit, and we detect three-, four- and five-fold coincidence counts. We implement and validate lossy boson sampling with one and two photons lost, and obtain sampling rates of 187 kHz, 13.6 kHz, and 0.78 kHz for five-, six- and seven-photon boson sampling with two photons lost, which is 9.4, 13.9, and 18.0 times faster than the standard boson sampling, respectively. Our experiment shows an approach to significantly enhance the sampling rate of multiphoton boson sampling.

quant-ph↗

arXiv2018

A Stochastic Pitchfork Bifurcation in Most Probable Phase Portraits

We study stochastic bifurcation for a system under multiplicative stable Levy noise (an important class of non-Gaussian noise), by examining the qualitative changes of equilibrium states in its most probable phase portraits. We have found some peculiar bifurcation phenomena in contrast to the deterministic counterpart: (i) When the non-Gaussianity parameter in Levy noise varies, there is either one, two or none backward pitchfork type bifurcations; (ii) When a parameter in the vector field varies, there are two or three forward pitchfork bifurcations; (iii) The non-Gaussian Levy noise clearly leads to fundamentally more complex bifurcation scenarios, since in the special case of Gaussian noise, there is only one pitchfork bifurcation which is reminiscent of the deterministic situation.

math.DS↗

arXiv2017

Experimental investigation of multi-observable uncertainty relations

The uncertainty relation is a distinguishing feature of quantum theory, characterizing the incompatibility of noncommuting observables in the preparation of quantum states. Recently, many uncertainty relations were proposed with improved lower bounds and were deemed capable of incorporating multiple observables. Here we report an experimental verification of seven uncertainty relations of this type with single-photon measurements. The results, while confirming these uncertainty relations, show as well the relative stringency of various uncertainty lower bounds.

quant-ph↗

arXiv2017

Investigation on the reported superconductivity in intercalated black phosphorus

Superconductivity intrinsic to the intercalated black phosphorus (BP) with a transition temperature Tc of 3.8 K, independent of the intercalant, whether an alkali or an alkaline earth element, has been reported recently by R. Zhang et al. (2017). However, the reported Tc and the field effect on the superconducting (SC) transition both bear great similarities to those for the pure Sn, which is commonly used for BP synthesis under the vapor transport method. We have therefore decided to determine whether a minute amount of Sn is present in the starting high purity BP crystals and whether it is the culprit for the small SC signal detected. Energy-dispersive X-ray spectroscopy results confirmed the existence of Sn in the starting high purity BP crystals purchased from the same company as in R. Zhang et al. (2017). We have reproduced the SC transition at 3.8 K in Li- and Na-intercalated BP crystals that contain minute amounts of Sn when prepared by the vapor transport method but not in BP crystals that are free of Sn when prepared by the high-pressure method. We have therefore concluded that the SC transition reported by R. Zhang et al. (2017) is associated with the Sn but not intrinsic to the intercalated BP crystals.

cond-mat.supr-con↗

arXiv2017

Quantum Dynamics of a Josephson Junction-Driven Cavity Mode System in the Presence of Voltage Bias Noise

We give a semiclassical analysis of the average photon number as well as photon number variance (Fano factor $F$) for a Josephson-junction (JJ) embedded microwave cavity system, where the JJ is subject to a fluctuating (i.e. noisy) bias voltage with finite dc average. Through the ac Josephson effect, the dc voltage bias drives the effectively nonlinear microwave cavity mode into an amplitude squeezed state ($F<1$), as has been established previously [A. D. Armour, et al., Phys. Rev. Lett. 111, 247001 (2013)], but bias noise acts to degrade this squeezing. We find that the sensitivity of the Fano factor to bias voltage noise depends qualitatively on which stable fixed point regime the system is in for the corresponding classical nonlinear steady state dynamics. Furthermore, we show that the impact of voltage bias noise is most significant when the cavity is excited to states with large average photon number.

cond-mat.mes-hall↗

arXiv2017

Multi-antenna Enabled Cluster-based Cooperation in Wireless Powered Communication Networks

In this paper, we consider a wireless powered communication network (WPCN) consisting of a multi-antenna hybrid access point (HAP) that transfers wireless energy to and receives sensing data from a cluster of low-power wireless devices (WDs). To enhance the throughput performance of some far-away WDs, we allow one of the WDs to act as the cluster head (CH) that helps forward the messages of the other cluster members (CMs). However, the performance of the proposed cluster-based cooperation is fundamentally limited by the high energy consumption of the CH, who needs to transmit all the WDs' messages including its own. To tackle this issue, we exploit the capability of multi-antenna energy beamforming (EB) at the HAP, which can focus more transferred power to the CH to balance its energy consumption in assisting the other WDs. Specifically, we first derive the throughput performance of each individual WD under the proposed scheme. Then, we jointly optimize the EB design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of the CH to maximize the minimum data rate achievable among all the WDs (the max-min throughput) for improved throughput fairness among the WDs. An efficient optimal algorithm is proposed to solve the joint optimization problem. Moreover, we simulate under practical network setups and show that the proposed multi-antenna enabled cluster-based cooperation can effectively improve the throughput fairness of WPCN.

cs.NI↗

arXiv2017

Prediction of Sea Surface Temperature using Long Short-Term Memory

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

cs.CV↗

arXiv2017

Multi-photon boson-sampling machines beating early classical computers

Boson sampling is considered as a strong candidate to demonstrate the quantum computational supremacy over classical computers. However, previous proof-of-principle experiments suffered from small photon number and low sampling rates owing to the inefficiencies of the single-photon sources and multi-port optical interferometers. Here, we develop two central components for high-performance boson sampling: robust multi-photon interferometers with 0.99 transmission rate, and actively demultiplexed single-photon sources from a quantum-dot-micropillar with simultaneously high efficiency, purity and indistinguishability. We implement and validate 3-, 4-, and 5-photon boson sampling, and achieve sampling rates of 4.96 kHz, 151 Hz, and 4 Hz, respectively, which are over 24,000 times faster than the previous experiments, and over 220 times faster than obtaining one sample through calculating the matrices permanent using the first electronic computer (ENIAC) and transistorized computer (TRADIC) in the human history. Our architecture is feasible to be scaled up to larger number of photons and with higher rate to race against classical computers, and might provide experimental evidence against the Extended Church-Turing Thesis.

quant-ph↗

arXiv2017

Off resonance coupling between a cavity mode and an ensemble of driven spins

We study the interaction between a superconducting cavity and a spin ensemble. The response of a cavity mode is monitored while simultaneously the spins are driven at a frequency close to their Larmor frequency, which is tuned to a value much higher than the cavity resonance. We experimentally find that the effective damping rate of the cavity mode is shifted by the driven spins. The measured shift in the damping rate is attributed to the retarded response of the cavity mode to the driven spins. The experimental results are compared with theoretical predictions and fair agreement is found.

quant-ph↗

arXiv2017

Beam test of CSES silicon strip detector module

The silicon-strip tracker of the China Seismo-Electromagnetic Satellite (CSES) consists of two double-sided silicon strip detectors (DSSDs) which provide incident particle tracking information. The low-noise analog ASIC VA140 was used in this study for DSSD signal readout. A beam test on the DSSD module was performed at the Beijing Test Beam Facility of the Beijing Electron Positron Collider (BEPC) using a 400~800 MeV/c proton beam. The pedestal analysis results, RMSE noise, gain correction, and particle incident position reconstruction of the DSSD module are presented.

physics.ins-det↗

arXiv2017

Construction of crystal structure prototype database: methods and applications

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the Crystal Structure Prototype Database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program Structure Prototype Analysis Package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

cond-mat.mtrl-sci↗

arXiv2017

Searching for Large-gap Quantum Spin Hall Insulators: Boron-Nitride/(Pb, Sn)/α-Al2O3 Sandwich Structures

Topological insulators hold great potential for efficient information processing and storage. Using density functional theory calculations, we predict that a honeycomb lead monolayer can be stabilized on the Al2O3 (0001) substrate and becomes topologically non-trivial with a sizeable band gap (~0.27 eV). Furthermore, we propose to use hexagonal boron-nitride (h-BN) monolayer as a protection for the topological states of Pb/Al2O3 and Sn/Al2O3. Our findings suggest new possibilities for designing and protecting two-dimensional TIs for practical applications.

cond-mat.mtrl-sci↗

arXiv2017

Possibility of Realizing Quantum Spin Hall Effect at Room Temperature in Stanene/Al2O3(0001)

Two-dimensional quantum spin Hall (QSH) insulators with reasonably wide band gaps are imperative for the development of various innovative technologies. Through systematic density functional calculations and tight-binding simulations, we found that stanene on α-alumina surface may possess a sizeable topologically nontrivial band gap (~0.25 eV) at the Γ point. Furthermore, stanene is atomically bonded to but electronically decoupled from the substrate, providing high structural stability and isolated QSH states to a large extent. The underlying physical mechanism is rather general, and this finding may lead to the opening of a new vista for the exploration of QSH insulators for room temperature device applications.

cond-mat.mtrl-sci↗