arXiv subjects

Wei Fang

Publications and source records attributed to Wei Fang.

At least 73 records · Page 4Linked to original sources

arXiv2022

Quantum tunnelling driven H$_2$ formation on graphene

It is commonly believed that it is unfavourable for adsorbed H atoms on carbonaceous surfaces to form H$_2$ without the help of incident H atoms. Using ring-polymer instanton theory to describe multidimensional tunnelling effects, combined with ab initio electronic structure calculations, we find that these quantum-mechanical simulations reveal a qualitatively different picture. Recombination of adsorbed H atoms, which was believed to be irrelevant at low temperature due to high barriers, is enabled by deep tunnelling, with reaction rates enhanced by tens of orders of magnitude. Furthermore, we identify a new path for H recombination that proceeds via multidimensional tunnelling, but would have been predicted to be unfeasible by a simple one-dimensional description of the reaction. The results suggest that hydrogen molecule formation at low temperatures are rather fast processes that should not be ignored in experimental settings and natural environments with graphene, graphite and other planar carbon segments.

physics.chem-ph↗

arXiv2022

Jitter-calibrated second-order correlation measurement of low-repetition-rate pulsed excitation

We report a new technique for the realization of second-order correlation ($g^2(τ)$) measurement under low-repetition-rate pulsed excitation (1 kHz), with timing jitter calibrated to restore lateral $g^2(τ)$ curves and determine $g^2(0)$. We use CdSe nanowire (NW) laser to demonstrate the jitter-calibrated $g^2(τ)$ measurement, where $g^2(0)$ evolution shows the laser emission transition process. The exciting pulses are split into reference and excitation channels, which enables the jitter calibration when the exciting pulses have significant timing jitter and low repetition rate. After using the reference signals to calibrate and rearrange the single-photon signals, lateral $g^2(τ)$ curves can be entirely restored, and $g^2(0)$ evolution is demonstrated from our method.

physics.optics↗

arXiv2022

Deep Residual Learning in Spiking Neural Networks

Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-based approaches due to discrete binary activation and complex spatial-temporal dynamics. Considering the huge success of ResNet in deep learning, it would be natural to train deep SNNs with residual learning. Previous Spiking ResNet mimics the standard residual block in ANNs and simply replaces ReLU activation layers with spiking neurons, which suffers the degradation problem and can hardly implement residual learning. In this paper, we propose the spike-element-wise (SEW) ResNet to realize residual learning in deep SNNs. We prove that the SEW ResNet can easily implement identity mapping and overcome the vanishing/exploding gradient problems of Spiking ResNet. We evaluate our SEW ResNet on ImageNet, DVS Gesture, and CIFAR10-DVS datasets, and show that SEW ResNet outperforms the state-of-the-art directly trained SNNs in both accuracy and time-steps. Moreover, SEW ResNet can achieve higher performance by simply adding more layers, providing a simple method to train deep SNNs. To our best knowledge, this is the first time that directly training deep SNNs with more than 100 layers becomes possible. Our codes are available at https://github.com/fangwei123456/Spike-Element-Wise-ResNet.

cs.NE↗

arXiv2022

Dynamical Stability of the Power Law K-essence Dark Energy Model with a New Interaction

We investigate the cosmological evolution of the power law K-essence dark energy (DE) model $F(X)= -\sqrt{X} + X$ with a new interaction $Q = αρ_mρ_{ϕ}H^{-1}$ in FRWL spacetime. The evolution behavior of dark energy under this interaction is analyzed by using dynamical systems method, and ten critical points are obtained. Among those critical points, a new stable point, which we called Scaling-like dark energy(DE) solution, is very important and interesting. The cosmological meaning of this attractor is different from the Scaling solution and dark energy dominated solution. For some value of model parameters, the universe will evolve to the attractor solution with the dark energy density parameter $Ω_ϕ=0.682946$ and the the equation of state $w_ϕ=-0.99$, which can be in good agreement with the observed data, and alleviate the Coincidence Problem.

gr-qc↗

arXiv2021

Rapid water diffusion at cryogenic temperatures through an inchworm-like mechanism

Water diffusion across the surfaces of materials is of importance to disparate processes such as water purification, ice formation, and more. Despite reports of rapid water diffusion on surfaces the molecular-level details of such processes remain unclear. Here, with scanning tunneling microscopy, we observe structural rearrangements and diffusion of water trimers at unexpectedly low temperatures (< 10 K) on a copper surface; temperatures at which water monomers or other clusters do not diffuse. Density functional theory calculations reveal a facile trimer diffusion process involving transformations between elongated and almost cyclic conformers in an inchworm-like manner. These subtle intermolecular reorientations maintain an optimal balance of hydrogen-bonding and water-surface interactions throughout the process. This work shows that the diffusion of hydrogen-bonded clusters can occur at exceedingly low temperatures without the need for hydrogen bond breakage or exchange; findings that will influence Ostwald ripening of ice nanoclusters and hydrogen bonded clusters in general.

physics.chem-ph↗

arXiv2021

Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks

Spiking Neural Networks (SNNs) have attracted enormous research interest due to temporal information processing capability, low power consumption, and high biological plausibility. However, the formulation of efficient and high-performance learning algorithms for SNNs is still challenging. Most existing learning methods learn weights only, and require manual tuning of the membrane-related parameters that determine the dynamics of a single spiking neuron. These parameters are typically chosen to be the same for all neurons, which limits the diversity of neurons and thus the expressiveness of the resulting SNNs. In this paper, we take inspiration from the observation that membrane-related parameters are different across brain regions, and propose a training algorithm that is capable of learning not only the synaptic weights but also the membrane time constants of SNNs. We show that incorporating learnable membrane time constants can make the network less sensitive to initial values and can speed up learning. In addition, we reevaluate the pooling methods in SNNs and find that max-pooling will not lead to significant information loss and have the advantage of low computation cost and binary compatibility. We evaluate the proposed method for image classification tasks on both traditional static MNIST, Fashion-MNIST, CIFAR-10 datasets, and neuromorphic N-MNIST, CIFAR10-DVS, DVS128 Gesture datasets. The experiment results show that the proposed method outperforms the state-of-the-art accuracy on nearly all datasets, using fewer time-steps. Our codes are available at https://github.com/fangwei123456/Parametric-Leaky-Integrate-and-Fire-Spiking-Neuron.

cs.NE↗

arXiv2021

Coherent mode-combined ultra-narrow-linewidth single-mode micro-disk laser

Integrated single-mode microlasers with ultra-narrow linewidths play a game-changing role in a broad spectrum of applications ranging from coherent communication and LIDAR to metrology and sensing. Generation of such light sources in a controllable and cost-effective manner remains an outstanding challenge due to the difficulties in the realization of ultra-high Q active micro-resonators with suppressed mode numbers. Here, we report a microlaser generated in an ultra-high Q Erbium doped lithium niobate (LN) micro-disk. Through the formation of coherently combined polygon modes at both pump and laser wavelengths, the microlaser exhibits single mode operation with an ultra-narrow-linewidth of 98 Hz. In combination with the superior electro-optic and nonlinear optical properties of LN crystal, the mass-producible on-chip single-mode microlaser will provide an essential building block for the photonic integrated circuits demanding high precision frequency control and reconfigurability.

physics.optics↗

arXiv2021

Lithium niobate microring with ultra-high Q factor above 10^8

We demonstrate ultra-high Q factor microring resonators close to the intrinsic material absorption limit on lithium niobate on insulator. The microrings are fabricated on pristine lithium niobate (LN) thin film wafer thinned from LN bulk via chemo-mechanical etching without ion slicing and ion etching. A record-high Q factor up to times ten to the power of 8th at the wavelength of 1550 nm is achieved because of the ultra-smooth interface of the microrings and the absence of ion induced lattice damage, indicating an ultra-low waveguide propagation loss of about 0.28 dB per meter. The ultra-high Q microrings will pave the way for integrated quantum light source, frequency comb generation, and nonlinear optical processes.

physics.optics↗

arXiv2021

Pruning of Deep Spiking Neural Networks through Gradient Rewiring

Spiking Neural Networks (SNNs) have been attached great importance due to their biological plausibility and high energy-efficiency on neuromorphic chips. As these chips are usually resource-constrained, the compression of SNNs is thus crucial along the road of practical use of SNNs. Most existing methods directly apply pruning approaches in artificial neural networks (ANNs) to SNNs, which ignore the difference between ANNs and SNNs, thus limiting the performance of the pruned SNNs. Besides, these methods are only suitable for shallow SNNs. In this paper, inspired by synaptogenesis and synapse elimination in the neural system, we propose gradient rewiring (Grad R), a joint learning algorithm of connectivity and weight for SNNs, that enables us to seamlessly optimize network structure without retraining. Our key innovation is to redefine the gradient to a new synaptic parameter, allowing better exploration of network structures by taking full advantage of the competition between pruning and regrowth of connections. The experimental results show that the proposed method achieves minimal loss of SNNs' performance on MNIST and CIFAR-10 dataset so far. Moreover, it reaches a $\sim$3.5% accuracy loss under unprecedented 0.73% connectivity, which reveals remarkable structure refining capability in SNNs. Our work suggests that there exists extremely high redundancy in deep SNNs. Our codes are available at https://github.com/Yanqi-Chen/Gradient-Rewiring.

cs.NE↗

arXiv2021

A Symbolic Regression Method for Dynamic Modeling and Control of Quadrotor UAVs

This paper presents a mathematic dynamic model of a quadrotor unmanned aerial vehicle (QUAV) by using the symbolic regression approach and then proposes a hierarchical control scheme for trajectory tracking. The symbolic regression approach is capable of constructing analytical quadrotor dynamic equations only through the collected data, which relieves the burden of first principle modeling. To facilitate position tracking control of a QUAV, the design of controller can be decomposed into two parts: a proportional-integral controller for the position subsystem is first designed to obtain the desired horizontal position and the backstepping method for the attitude subsystem is developed to ensure that the Euler angles and the altitude can fast converge to the reference values. The effectiveness is verified through experiments on a benchmark multicopter simulator.

eess.SY↗

arXiv2021

Broadband highly efficient nonlinear optical processes in on-chip integrated lithium niobate microdisk resonators of Q-factor above 10^8

We demonstrated broadband highly efficient optical nonlinear processes in on-chip integrated lithium niobate (LN) microdisk resonators. The Q factors of the micro-resonators fabricated by femtosecond laser writing and chemo-mechanical polishing are reliably above 10^8, approaching the intrinsic material absorption limit of LN. Broadband nonlinear processes, including optical parametric oscillation (OPO), second harmonic generation (SHG), third harmonic generation, and fourth harmonic generation, were observed with ultrahigh efficiencies in the same LN microdisk without introducing domain inversion, thanks to the natural quasi phase-matching and the dense spectral modes of the X-cut LN microdisk with millimeter diameter. The threshold of OPO and the absolute conversion efficiency of SHG are 19.6 microwatt and 66%, both surpass the state-of-the-art values among on-chip LN micro-resonators demonstrated so far. The broadband and highly efficient nonlinear frequency conversions achieved with the ultrahigh-Q LN microdisk resonators promise high-density integration of nonlinear photonic devices such as frequency convertors and entangled photon sources.

physics.optics↗

arXiv2021

Both qubits of the singlet state can be steered simultaneously by multiple independent observers via sequential measurement

Quantum correlation is a fundamental property which distinguishes quantum systems from classical ones, and it is also a fragile resource under projective measurement. Recently, it has been shown that a subsystem in entangled pairs can share nonlocality with multiple observers in sequence. Here we present a new steering scenario where both subsystems are accessible by multiple observers. And it is found that the two qubits in singlet state can be simultaneously steered by two sequential observers, respectively.

quant-ph↗

arXiv2020

The color center singlet state of oxygen vacancies in TiO$_2$

Oxygen vacancies are ubiquitous in TiO$_2$ and play key roles in catalysis and magnetism applications.Despite being extensively investigated, the electronic structure of oxygen vacancies in TiO$_2$ remains controversial both experimentally and theoretically.Here we report a study of a neutral oxygen vacancy in TiO$_2$ using state-of-the-art quantum chemical electronic structure methods.We find that the ground state is a color center singlet state in both the rutile and the anatase phase of TiO$_2$. Specifically, embedded CCSD(T) calculations find, for an oxygen vacancy in rutile, that the lowest triplet state energy is 0.6 eV above the singlet state, and in anatase the triplet state energy is higher by 1.4 eV. Our study provides fresh insights on the electronic structure of the oxygen vacancy in TiO$_2$, clarifying earlier controversies and potentially inspiring future studies of defects with correlated wave function theories.

cond-mat.mtrl-sci↗

arXiv2020

Microcanonical Tunneling Rates from Density-of-States Instanton Theory

Semiclassical instanton theory is a form of quantum transition-state theory which can be applied to computing thermal reaction rates for complex molecular systems including quantum tunneling effects. There have been a number of attempts to extend the theory to treat microcanonical rates. However, the previous formulations are either computationally unfeasible for large systems due to an explicit sum over states or they involve extra approximations which make them less reliable. We propose a robust and practical microcanonical formulation called density-of-states instanton theory, which avoids the sum over states altogether. In line with the semiclassical approximations inherent to the instanton approach, we employ the stationary-phase approximation to the inverse Laplace transform to obtain the densities of states. This can be evaluated using only post-processing of the data available from a small set of instanton calculations, such that our approach remains computationally efficient. We show that the new formulation predicts results that agree well with quantum scattering theory for an atom-diatom reaction and with experiments for a photoexcited unimolecular hydrogen transfer in a Criegee intermediate. When the thermal rate is evaluated from a Boltzmann average over our new microcanonical formalism, it can overcome some problems of conventional instanton theory. In particular, it predicts a smooth transition at the crossover temperature and is able to describe bimolecular reactions with pre-reactive complexes such as CH3OH + OH.

physics.chem-ph↗

arXiv2020

Observation of photon antibunching with a single conventional detector

The second-order photon correlation function is of great importance in quantum optics which is typically measured with the Hanbury Brown and Twiss interferometer which employs a pair of single-photon detectors and a dual-channel time acquisition module. Here we demonstrate a new method to measure and extract the second-order correlation function with a standard single-photon avalanche photodiode (dead-time = 22 ns) and a single-channel time acquisition module. This is realized by shifting the informative coincidence counts near the zero-time delay to a time window which is not obliterated by the dead-time and after-pulse of detection system. The new scheme is verified by measuring the second-order correlation from a single colloidal nanocrystal. Photon antibunching is unambiguously observed and agrees well with the result measured using the standard HBT setup. Our scheme simplifies the higher-order correlation technique and might be favored in cost-sensitive circumstances.

quant-ph↗

arXiv2020

Importance Sampling for Pathwise Sensitivity of Stochastic Chaotic Systems

This paper proposes a new pathwise sensitivity estimator for chaotic SDEs. By introducing a spring term between the original and perturbated SDEs, we derive a new estimator by importance sampling. The variance of the new estimator increases only linearly in time $T,$ compared with the exponential increase of the standard pathwise estimator. We compare our estimator with the Malliavin estimator and extend both of them to the Multilevel Monte Carlo method, which further improves the computational efficiency. Finally, we also consider using this estimator for the SDE with small volatility to approximate the sensitivities of the invariant measure of chaotic ODEs. Furthermore, Richardson-Romberg extrapolation on the volatility parameter gives a more accurate and efficient estimator. Numerical experiments support our analysis.

math.NA↗

arXiv2020

Deciphering exciton-generation processes in quantum-dot electroluminescence

Electroluminescence (EL) of colloidal nanocrystals promises a new generation of high-performance and solution-processable light-emitting diodes (LEDs). The operation of nanocrystal-based LEDs relies on the recombination of electrically-generated excitons. However, a fundamental question, i.e, how excitons are electrically generated in individual nanocrystals, remains unanswered. Here, we reveal a molecular mechanism of sequential electron-hole injection for the exciton generation in nanocrystal-based EL devices. To decipher the corresponding elementary processes, we develop electrically-pumped single-nanocrystal spectroscopy. While hole injection into neutral quantum dots (QDs) is generally-considered to be inefficient, we find that the intermediate negatively-charged state of QD triggers confinement-enhanced Coulomb interactions, which simultaneously accelerate hole injection and hinder excessive electron injection. In-situ/operando spectroscopy on state-of-the-art QD-LEDs demonstrate that exciton generation at the ensemble level is consistent with the charge-confinement-enabled sequential electron-hole injection mechanism revealed at the single-nanocrystal level. Our findings provide a universal mechanism for enhancing charge balance in nanocrystal-based EL devices.

physics.optics↗

arXiv2020

Efficient light coupling between an ultra-low loss lithium niobate waveguide and an adiabatically tapered single mode optical fiber

A lithium niobate on insulator ridge waveguide allows constructing high-density photonic integrated circuits thanks to its small bending radius offered by the high index contrast. Meanwhile, the significant mode-field mismatch between an optical fiber and the single-mode lithium niobate waveguide leads to low coupling efficiencies. Here, we demonstrate, both numerically and experimentally, that the problem can be solved with a tapered single mode fiber of an optimized mode field profile. Numerical simulation shows that the minimum coupling losses for the TE and TM mode are 0.32 dB and 0.86 dB, respectively. Experimentally, though without anti-reflection coating, the measured coupling losses for TE and TM mode are 1.32 dB and 1.88 dB, respectively. Our technique paves a way for a broad range of on-chip lithium niobate applications.

physics.optics↗