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Zhan Li

Publications and source records attributed to Zhan Li.

At least 73 records · Page 4Linked to original sources
arXiv2022

Robust fractional-order fast terminal sliding mode control of aerial manipulator derived from a mutable inertia parameters model

The coupling disturbance between the manipulator and the unmanned aerial vehicle (UAV) deteriorates the control performance of system. To get high performance of the aerial manipulator, a robust fractional order fast terminal sliding mode control (FOFTSMC) strategy based on mutable inertia parameters is proposed in this paper. First, the dynamics of aerial manipulator with consideration of the coupling disturbance is derived by utilizing mutable inertia parameters. Then, based on the dynamic model, a robust FOFTSMC algorithm is designed to make the system fly steadily under coupling disturbance. Furthermore, stability analysis is conducted to prove the convergence of tracking errors. Finally, comparative simulation results are given to show the validity and superiority of the proposed scheme.

cs.RO↗
arXiv2022

Top quark mass measurements at the $t\bar{t}$ threshold with CEPC

We present a study of top quark mass measurements at the $t\bar{t}$ threshold based on CEPC. A centre-of-mass energy scan near two times of the top mass is performed and the measurement precision of top quark mass, width and $α_S$ are evaluated using the $t\bar{t}$ production rates. Realistic scan strategies at the threshold are discussed to maximise the sensitivity to the measurement of the top quark properties individually and simultaneously in the CEPC scenarios assuming a limited total luminosity of 100 fb$^{-1}$. With the optimal scan for individual property measurements, the top quark mass precision is expected to be 9 MeV, the top quark width precision is expected to be 26 MeV, and $α_S$ can be measured at a precision of 0.00039. Taking into account the uncertainties from theory, background subtraction, beam energy and luminosity spectrum, the top quark mass can be measured at a precision of 14 MeV optimistically and 34 MeV conservatively at CEPC.

hep-ex↗
arXiv2022

Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

In this paper, a novel adaptive smooth disturbance observer-based fast finite-time adaptive backstepping control scheme is presented for the attitude tracking of the 3-DOF helicopter system subject to compound disturbances. First, an adaptive smooth disturbance observer (ASDO) is proposed to estimate the composite disturbance, which owns the characteristics of smooth output, fast finite-time convergence, and adaptability to the disturbance of unknown derivative boundary. Then, a finite-time backstepping control protocol is construct to drive the elevation and pitch angles to track reference trajectories. To tackle the "explosion of complexity" and "singularity" problems in the conventional backstepping design framework, a fast finite-time command filter (FFTCF) is utilized to estimate the virtual control signal and its derivative. Moreover, a fractional power-based auxiliary dynamic system is introduced to compensate the error caused by the FFTCF estimation. Furthermore, an improved fractional power-based adaptive law with the $σ$-modification term is designed to attenuate the observer approximation error, such that the tracking performance is further enhanced. In terms of the fast finite-time stability theory, the signals of the closed-loop system are all fast finite-time bounded while the attitude tracking errors can fast converge to a sufficiently small region of the origin in finite time. Finally, a contrastive numerical simulation is carried out to validate the effectiveness and superiority of the designed control scheme.

eess.SY↗
arXiv2021

Fast Monte Carlo Rendering via Multi-Resolution Sampling

Monte Carlo rendering algorithms are widely used to produce photorealistic computer graphics images. However, these algorithms need to sample a substantial amount of rays per pixel to enable proper global illumination and thus require an immense amount of computation. In this paper, we present a hybrid rendering method to speed up Monte Carlo rendering algorithms. Our method first generates two versions of a rendering: one at a low resolution with a high sample rate (LRHS) and the other at a high resolution with a low sample rate (HRLS). We then develop a deep convolutional neural network to fuse these two renderings into a high-quality image as if it were rendered at a high resolution with a high sample rate. Specifically, we formulate this fusion task as a super resolution problem that generates a high resolution rendering from a low resolution input (LRHS), assisted with the HRLS rendering. The HRLS rendering provides critical high frequency details which are difficult to recover from the LRHS for any super resolution methods. Our experiments show that our hybrid rendering algorithm is significantly faster than the state-of-the-art Monte Carlo denoising methods while rendering high-quality images when tested on both our own BCR dataset and the Gharbi dataset. \url{https://github.com/hqqxyy/msspl}

cs.CV↗
arXiv2021

Photon Conversion and Interaction on Chip

The conversion and interaction between quantum signals at a single-photon level are essential for scalable quantum photonic information technology. Using a fully-optimized, periodically-poled lithium niobate microring, we demonstrate ultra-efficient sum-frequency generation on chip. The external quantum efficiency reaches $(65\pm3)\%$ with only $(104\pm4)$ $μ$W pump power, improving the state-of-the-art by over one order of magnitude. At the peak conversion, $3\times10^{-5}$ noise photon is created during the cavity lifetime, which meets the requirement of quantum applications using single-photon pulses. Using pump and signal in single-photon coherent states, we directly measure the conversion probability produced by a single pump photon to be $10^{-5}$ -- breaking the record by 100 times -- and the photon-photon coupling strength to be 9.1 MHz. Our results mark a new milestone toward quantum nonlinear optics at the ultimate single photon limit, creating new background in highly integrated photonics and quantum optical computing.

physics.optics↗
arXiv2021

Efficient Frequency Doubling with Active Stabilization on Chip

Thin-film lithium niobate (TFLN) is superior for integrated nanophotonics due to its outstanding properties in nearly all aspects: strong second-order nonlinearity, fast and efficient electro-optic effects, wide transparency window, and little two photon absorption and free carrier scattering. Together, they permit highly integrated nanophotonic circuits capable of complex photonic processing by incorporating disparate elements on the same chip. Yet, there has to be a demonstration that synergizes those superior properties for system advantage. Here we demonstrate such a chip that capitalizes on TFLNs favorable ferroelectricity, high second-order nonlinearity, and strong electro-optic effects. It consists of a monolithic circuit integrating a Z-cut, quasi-phase matched microring with high quality factor and a phase modulator used in active feedback control. By Pound-Drever-Hall locking, it realizes stable frequency doubling at about 50% conversion with only milliwatt pump, marking the highest by far among all nanophotonic platforms with milliwatt pumping. Our demonstration addresses a long-outstanding challenge facing cavity-based optical processing, including frequency conversion, frequency comb generation, and all-optical switching, whose stable performance is hindered by photorefractive or thermal effects. Our results further establish TFLN as an excellent material capable of optical multitasking, as desirable to build multi-functional chip devices.

physics.optics↗
arXiv2021

Photon Conversion in Thin-film Lithium Niobate Nanowaveguides: A Noise Analysis

Wavelength transduction of single-photon signals is indispensable to networked quantum applications, particularly those incorporating quantum memories. Lithium niobate nanophotonic devices have demonstrated favorable linear, nonlinear, and electro-optical properties to deliver this crucial function while offering superiror efficiency, integrability, and scalability. Yet, their quantum noise level--an crucial metric for any single-photon based application--has yet to be understood. In this work, we report the first study with the focus on telecom to near-visible conversion driven by a telecom pump of small detuning, for practical considerations in distributed quantum processing over fiber networks. Our results find the noise level to be on the order of $10^{-4}$ photons per time-frequency mode for high conversion, allowing faithful pulsed operations. Through carefully analyzing the origins of such noise and each's dependence on the pump power and wavelength detuning, we have also identified a formula for noise suppression to $10^{-5}$ photons per mode. Our results assert a viable, low-cost, and modular approach to networked quantum processing and beyond using lithium niobate nanophotonics.

physics.optics↗
arXiv2020

On accumulation points of pseudo-effective thresholds

We characterize a $k$-th accumulation point of pseudo-effective thresholds of $n$-dimensional varieties as certain invariant associates to a numerically trivial pair of an $(n-k)$-dimensional variety. This characterization is applied towards Fujita's log spectrum conjecture for large $k$.

math.AG↗
arXiv2020

Ultra-bright Quantum Photon Sources on Chip

Quantum photon sources of high rate, brightness, and purity are increasingly desirable as quantum information systems are quickly scaled up and applied to many fields. Using a periodically poled lithium niobate microresonator on chip, we demonstrate photon-pair generation at high rates of 8.5 MHz and 36.3 MHz using only 3.4-$μ$W and 13.4-$μ$W pump power, respectively, marking orders of magnitude improvement over the state-of-the-art. The measured coincidence to accidental ratio is well above 100 at those high rates and reaches $14,682\pm 4427$ at a lower pump power. The same chip enables heralded single-photon generation at tens of megahertz rates, each with low auto-correlation $g^{(2)}_{H}(0)=0.008$ and $0.097$ for the microwatt pumps. Such distinct performance, facilitated by the chip device's noiseless and giant optical nonlinearity, will contribute to the forthcoming pervasive adoption of quantum optical information technologies.

physics.optics↗
arXiv2020

Adaptive Fast Smooth Second-Order Sliding Mode Control for Attitude Tracking of a 3-DOF Helicopter

This paper presents a novel adaptive fast smooth second-order sliding mode control for the attitude tracking of the three degree-of-freedom (3-DOF) helicopter system with lumped disturbances. Combining with a non-singular integral sliding mode surface, we propose a novel adaptive fast smooth second-order sliding mode control method to enable elevation and pitch angles to track given desired trajectories respectively with the features of non-singularity, adaptation to disturbances, chattering suppression and fast finite-time convergence. In addition, a novel adaptive-gain smooth second-order sliding mode observer is proposed to compensate time-varying lumped disturbances with the smoother output compared with the adaptive-gain second-order sliding mode observer. The fast finite-time convergence of the closed-loop system with constant disturbances and the fast finite-time uniformly ultimately boundedness of the closed-loop system with the time-varying lumped disturbances are proved with the finite-time Lyapunov stability theory. Finally, the effectiveness and superiority of the proposed control methods are verified by comparative simulation experiments.

eess.SY↗
arXiv2020

On finiteness of log canonical models

Let $(X, Δ)/U$ be klt pairs and $Q$ be a convex set of divisors. Assuming that the relative Kodaira dimensions are non-negative, then there are only finitely many log canonical models when the boundary divisors varying in a relatively compact rational polytope in $Q$. As a consequence, we show the existence of the log canonical model for a klt pair $(X, Δ)/U$ with real coefficients.

math.AG↗
arXiv2020

Data-Driven Construction of Data Center Graph of Things for Anomaly Detection

Data center (DC) contains both IT devices and facility equipment, and the operation of a DC requires a high-quality monitoring (anomaly detection) system. There are lots of sensors in computer rooms for the DC monitoring system, and they are inherently related. This work proposes a data-driven pipeline (ts2graph) to build a DC graph of things (sensor graph) from the time series measurements of sensors. The sensor graph is an undirected weighted property graph, where sensors are the nodes, sensor features are the node properties, and sensor connections are the edges. The sensor node property is defined by features that characterize the sensor events (behaviors), instead of the original time series. The sensor connection (edge weight) is defined by the probability of concurrent events between two sensors. A graph of things prototype is constructed from the sensor time series of a real data center, and it successfully reveals meaningful relationships between the sensors. To demonstrate the use of the DC sensor graph for anomaly detection, we compare the performance of graph neural network (GNN) and existing standard methods on synthetic anomaly data. GNN outperforms existing algorithms by a factor of 2 to 3 (in terms of precision and F1 score), because it takes into account the topology relationship between DC sensors. We expect that the DC sensor graph can serve as the infrastructure for the DC monitoring system since it represents the sensor relationships.

cs.LG↗
arXiv2020

Ultra-efficient and highly-tunable second-harmonic generation in Z-cut periodically poled lithium niobate nanowaveguides

Thin-film lithium niobate on insulator (LNOI) has emerged as a superior integrated-photonics platform for linear, nonlinear, and electro-optics. Here we combine quasi-phase-matching, dispersion engineering, and tight mode confinement to realize nonlinear parametric processes with both high efficiency and wide wavelength tunability. On a millimeter-long, Z-cut LNOI waveguide, we demonstrate ultra-efficient ($1900\pm500 \% $W$^{-1}$cm$^{-2}$) and highly tunable (-1.71 nm/K) second-harmonic generation from 1530 to 1583 nm by type-0 quasi-phase-matching. Our technique is applicable to optical harmonic generation, quantum light sources, frequency conversion, and many other photonic information processing across visible to mid-IR spectral bands.

physics.optics↗
arXiv2020

Automatic removal of false image stars in disk-resolved images of the Cassini Imaging Science Subsystem

Taking a large amount of images, the Cassini Imaging Science Subsystem (ISS) has been routinely used in astrometry. In ISS images, disk-resolved objects often lead to false detection of stars that disturb the camera pointing correction. The aim of this study was to develop an automated processing method to remove the false image stars in disk-resolved objects in ISS images. The method included the following steps: extracting edges, segmenting boundary arcs, fitting circles and excluding false image stars. The proposed method was tested using 200 ISS images. Preliminary experimental results show that it can remove the false image stars in more than 95% of ISS images with disk-resolved objects in a fully automatic manner, i.e. outperforming the traditional circle detection based on Circular Hough Transform (CHT) by 17%. In addition, its speed is more than twice as fast as that of the CHT method. It is also more robust (no manual parameter tuning is needed) when compared with CHT. The proposed method was also applied to a set of ISS images of Rhea to eliminate the mismatch in pointing correction in automatic procedure. Experiment results showed that the precision of final astrometry results can be improve by roughly 2 times than that of automatic procedure without the method. It proved that the proposed method is helpful in the astrometry of ISS images in fully automatic manner.

astro-ph.IM↗
arXiv2019

Contour Detection in Cassini ISS images based on Hierarchical Extreme Learning Machine and Dense Conditional Random Field

In Cassini ISS (Imaging Science Subsystem) images, contour detection is often performed on disk-resolved object to accurately locate their center. Thus, the contour detection is a key problem. Traditional edge detection methods, such as Canny and Roberts, often extract the contour with too much interior details and noise. Although the deep convolutional neural network has been applied successfully in many image tasks, such as classification and object detection, it needs more time and computer resources. In the paper, a contour detection algorithm based on H-ELM (Hierarchical Extreme Learning Machine) and DenseCRF (Dense Conditional Random Field) is proposed for Cassini ISS images. The experimental results show that this algorithm's performance is better than both traditional machine learning methods such as SVM, ELM and even deep convolutional neural network. And the extracted contour is closer to the actual contour. Moreover, it can be trained and tested quickly on the general configuration of PC, so can be applied to contour detection for Cassini ISS images.

astro-ph.IM↗