arXiv subjects

Peng Peng

Publications and source records attributed to Peng Peng.

At least 55 records · Page 3Linked to original sources

arXiv2022

Evolutionary Game-Theoretical Analysis for General Multiplayer Asymmetric Games

Evolutionary game theory has been a successful tool to combine classical game theory with learning-dynamical descriptions in multiagent systems. Provided some symmetric structures of interacting players, many studies have been focused on using a simplified heuristic payoff table as input to analyse the dynamics of interactions. Nevertheless, even for the state-of-the-art method, there are two limits. First, there is inaccuracy when analysing the simplified payoff table. Second, no existing work is able to deal with 2-population multiplayer asymmetric games. In this paper, we fill the gap between heuristic payoff table and dynamic analysis without any inaccuracy. In addition, we propose a general framework for $m$ versus $n$ 2-population multiplayer asymmetric games. Then, we compare our method with the state-of-the-art in some classic games. Finally, to illustrate our method, we perform empirical game-theoretical analysis on Wolfpack as well as StarCraft II, both of which involve complex multiagent interactions.

cs.AI↗

arXiv2022

Obstacle Avoidance of Resilient UAV Swarm Formation with Active Sensing System in the Dense Environment

This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First, the point cloud received by each UAV is fit by the gaussian mixture model (GMM) and transmitted in the swarm. Resampling from the received GMM contributes to a global map, which is used as the foundation for consensus. Second, to improve flight safety, an active sensing system is designed to plan the observation angle of each UAV considering the unknown field, overlap of the field of view (FOV), velocity direction and smoothness of yaw rotation, and this planning problem is solved by the distributed particle swarm optimization (DPSO) algorithm. Last, for the formation motion planning, to ensure obstacle avoidance, the formation structure is allowed for affine transformation and is treated as the soft constraint on the control points of the B-spline. Besides, the STGO is introduced to avoid local minima. The combination of GMM communication and STGO guarantees a safe and strict consensus between UAVs. Tests on different formations in the simulation show that our algorithm can contribute to a strict consensus and has a success rate of at least 80% for obstacle avoidance in a dense environment. Besides, the active sensing system can increase the success rate of obstacle avoidance from 50% to 100% in some scenarios.

cs.RO↗

arXiv2022

Risk-aware Trajectory Sampling for Quadrotor Obstacle Avoidance in Dynamic Environments

Obstacle avoidance of quadrotors in dynamic environments is still a very open problem. Current works commonly leverage traditional static maps to represent static obstacles and the detection and tracking of moving objects (DATMO) method to model dynamic obstacles separately. The detection module requires pre-training, and the dynamic obstacles can only be modeled with certain shapes, such as cylinders or ellipsoids. This work utilizes the dual-structure particle-based (DSP) dynamic occupancy map to represent the arbitrary-shaped static obstacles and dynamic obstacles simultaneously, and proposes an efficient risk-aware sampling-based local trajectory planner to realize safe flights in this map. The trajectory is planned by sampling motion primitives generated in the state space. Each motion primitive is divided into two phases: a short-term phase with a strict risk limitation and a relatively long-term phase designed to avoid high-risk regions. The risk is evaluated with the predicted particle-form future occupancy status, considering the time dimension. With an approach to split from and merge to an arbitrary global trajectory, the planner can also be used in the tasks with preplanned global trajectories. Comparison experiments show that the obstacle avoidance system composed of the DSP map and our planner performs the best in dynamic environments. In real-world tests, our quadrotor reaches a speed of 6 m/s with the motion capture system and 2.5 m/s with everything running on a low-price single-board computer.

cs.RO↗

arXiv2021

The dominant scattering channel induced by two-body collision of D-band atoms in triangular optical lattice

The mechanism of atomic collisions in excited bands plays an important role in the study of the orbital physics in optical lattices and simulation of condensed matter physics. Atoms distributing in one excited bands of an optical lattice would collide and decay to other bands through different scattering channels. In excited bands of one dimensional lattice, due to lack of geometry, there is no significant difference between cross section of scattering channels. Here, we investigate the collisional scattering channels for atoms in the excited bands of a triangular optical lattice and demonstrate a dominant scattering channel in the experiment. A shortcut method is utilized to load Bose-Einstein condensates of $^{87} {\rm Rb}$ atoms into the first D band with zero quasi-momentum. After some time for evolution, the number of atoms scattering to S band due to two-body collisions is around four times more than that to the second most band. We reveal that the scattering channel to $ss$ band is dominant by theoretical calculation, which agrees with experimental measurements. The appearance of dominant scattering channels in triangular optical lattice is owing to geometric dimension coupling. This work is helpful for the study of many-body systems and directional enhancement in optical lattices.

cond-mat.quant-gas↗

arXiv2021

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

AlphaStar, the AI that reaches GrandMaster level in StarCraft II, is a remarkable milestone demonstrating what deep reinforcement learning can achieve in complex Real-Time Strategy (RTS) games. However, the complexities of the game, algorithms and systems, and especially the tremendous amount of computation needed are big obstacles for the community to conduct further research in this direction. We propose a deep reinforcement learning agent, StarCraft Commander (SCC). With order of magnitude less computation, it demonstrates top human performance defeating GrandMaster players in test matches and top professional players in a live event. Moreover, it shows strong robustness to various human strategies and discovers novel strategies unseen from human plays. In this paper, we will share the key insights and optimizations on efficient imitation learning and reinforcement learning for StarCraft II full game.

cs.LG↗

arXiv2021

Thermal Infrared Image Colorization for Nighttime Driving Scenes with Top-Down Guided Attention

Benefitting from insensitivity to light and high penetration of foggy environments, infrared cameras are widely used for sensing in nighttime traffic scenes. However, the low contrast and lack of chromaticity of thermal infrared (TIR) images hinder the human interpretation and portability of high-level computer vision algorithms. Colorization to translate a nighttime TIR image into a daytime color (NTIR2DC) image may be a promising way to facilitate nighttime scene perception. Despite recent impressive advances in image translation, semantic encoding entanglement and geometric distortion in the NTIR2DC task remain under-addressed. Hence, we propose a toP-down attEntion And gRadient aLignment based GAN, referred to as PearlGAN. A top-down guided attention module and an elaborate attentional loss are first designed to reduce the semantic encoding ambiguity during translation. Then, a structured gradient alignment loss is introduced to encourage edge consistency between the translated and input images. In addition, pixel-level annotation is carried out on a subset of FLIR and KAIST datasets to evaluate the semantic preservation performance of multiple translation methods. Furthermore, a new metric is devised to evaluate the geometric consistency in the translation process. Extensive experiments demonstrate the superiority of the proposed PearlGAN over other image translation methods for the NTIR2DC task. The source code and labeled segmentation masks will be available at \url{https://github.com/FuyaLuo/PearlGAN/}.

cs.CV↗

arXiv2021

The last migration trap of compact objects in AGN accretion disc

Many black holes (BHs) detected by the Laser Interferometer Gravitational-wave Observatory (LIGO) and the Virgo detectors are multiple times more massive than those in X-ray binaries. One possibility is that some BBHs merge within a few Schwarzschild radii of a supermassive black hole (SMBH), such that the gravitational waves (GWs) are highly redshifted, causing the mass inferred from GW signals to appear higher than the real mass. The difficulty of this scenario lies in the delivery of BBH to such a small distance to a SMBH. Here we revisit the theoretical models for the migration of compact objects (COs) in the accretion discs of active galactic nuclei (AGNs). We find that when the accretion rate is high so that the disc is best described by the slim disc model, the COs in the disc could migrate to a radius close to the innermost stable circular orbit (ISCO) and be trapped there for the remaining lifetime of the AGN. The exact trapping radius coincides with the transition region between the sub- and super-Keplerian rotation of the slim disc. We call this region "the last migration trap" because inside it COs can no longer be trapped for a long time. We pinpoint the parameter space which could induce such a trap and we estimate that the last migration trap contributes a few per cent of the LIGO/Virgo events. Our result implies that a couple of BBHs discovered by LIGO/Virgo could have smaller intrinsic masses.

astro-ph.HE↗

arXiv2021

Study to improve the performance of interferometer with ultra-cold atoms

Ultra-cold atoms provide ideal platforms for interferometry. The macroscopic matter-wave property of ultra-cold atoms leads to large coherent length and long coherent time, which enable high accuracy and sensitivity to measurement. Here, we review our efforts to improve the performance of the interferometer. We demonstrate a shortcut method for manipulating ultra-cold atoms in an optical lattice. Compared with traditional ones, this shortcut method can reduce manipulation time by up to three orders of magnitude. We construct a matter-wave Ramsey interferometer for trapped motional quantum states and significantly increase its coherence time by one order of magnitude with an echo technique based on this method. Efforts have also been made to enhance the resolution by multimode scheme. Application of a noise-resilient multi-component interferometer shows that increasing the number of paths could sharpen the peaks in the time-domain interference fringes, which leads to a resolution nearly twice compared with that of a conventional double-path two-mode interferometer. With the shortcut method mentioned above, improvement of the momentum resolution could also be fulfilled, which leads to atomic momentum patterns less than 0.6 $\hbar k_L$. To identify and remove systematic noises, we introduce the methods based on the principal component analysis (PCA) that reduce the noise in detection close to the $1/\sqrt{2}$ of the photon-shot noise and separate and identify or even eliminate noises. Furthermore, we give a proposal to measure precisely the local gravity acceleration within a few centimeters based on our study of ultracold atoms in precision measurements.

cond-mat.quant-gas↗

arXiv2020

How to fine-tune deep neural networks in few-shot learning?

Deep learning has been widely used in data-intensive applications. However, training a deep neural network often requires a large data set. When there is not enough data available for training, the performance of deep learning models is even worse than that of shallow networks. It has been proved that few-shot learning can generalize to new tasks with few training samples. Fine-tuning of a deep model is simple and effective few-shot learning method. However, how to fine-tune deep learning models (fine-tune convolution layer or BN layer?) still lack deep investigation. Hence, we study how to fine-tune deep models through experimental comparison in this paper. Furthermore, the weight of the models is analyzed to verify the feasibility of the fine-tuning method.

cs.LG↗

arXiv2020

A Unified Structure for Efficient RGB and RGB-D Salient Object Detection

Salient object detection (SOD) has been well studied in recent years, especially using deep neural networks. However, SOD with RGB and RGB-D images is usually treated as two different tasks with different network structures that need to be designed specifically. In this paper, we proposed a unified and efficient structure with a cross-attention context extraction (CRACE) module to address both tasks of SOD efficiently. The proposed CRACE module receives and appropriately fuses two (for RGB SOD) or three (for RGB-D SOD) inputs. The simple unified feature pyramid network (FPN)-like structure with CRACE modules conveys and refines the results under the multi-level supervisions of saliency and boundaries. The proposed structure is simple yet effective; the rich context information of RGB and depth can be appropriately extracted and fused by the proposed structure efficiently. Experimental results show that our method outperforms other state-of-the-art methods in both RGB and RGB-D SOD tasks on various datasets and in terms of most metrics.

cs.CV↗

arXiv2020

Degeneracy between mass and peculiar acceleration for the double white dwarfs in the LISA band

Mass and distance are fundamental quantities to measure in gravitational-wave (GW) astronomy. However, recent studies suggest that the measurement may be biased due to the acceleration of GW source. Here we develop an analytical method to quantify such a bias induced by a tertiary on a double white dwarf (DWD), since DWDs are the most common GW sources in the milli-Hertz band. We show that in a large parameter space the mass is degenerate with the peculiar acceleration, so that from the waveform we can only retrieve a mass of ${\cal M}(1+Γ)^{3/5}$, where ${\cal M}$ is the real chirp mass of the DWD and $Γ$ is a dimensionless factor proportional to the peculiar acceleration. Based on our analytical method, we conduct mock observation of DWDs by the Laser Interferometer Space Antenna (LISA). We find that in about $9\%$ of the cases the measured chirp mass is biased due to the presence of a tertiary by $(5-30)\%$. Even more extreme cases are found in about a dozen DWDs and they may be misclassified as double neutron stars, binary black holes, DWDs undergoing mass transfer, or even binaries containing lower-mass-gap objects and primordial black holes. The bias in mass also affects the measurement of distance, resulting in a seemingly over-density of DWDs within a heliocentric distance of $1$ kpc as well as beyond $100$ kpc. Our result highlights the necessity of modeling the astrophysical environments of GW sources to retrieve their correct physical parameters.

astro-ph.HE↗

arXiv2020

Segmentation overlapping wear particles with few labelled data and imbalance sample

Ferrograph image segmentation is of significance for obtaining features of wear particles. However, wear particles are usually overlapped in the form of debris chains, which makes challenges to segment wear debris. An overlapping wear particle segmentation network (OWPSNet) is proposed in this study to segment the overlapped debris chains. The proposed deep learning model includes three parts: a region segmentation network, an edge detection network and a feature refine module. The region segmentation network is an improved U shape network, and it is applied to separate the wear debris form background of ferrograph image. The edge detection network is used to detect the edges of wear particles. Then, the feature refine module combines low-level features and high-level semantic features to obtain the final results. In order to solve the problem of sample imbalance, we proposed a square dice loss function to optimize the model. Finally, extensive experiments have been carried out on a ferrograph image dataset. Results show that the proposed model is capable of separating overlapping wear particles. Moreover, the proposed square dice loss function can improve the segmentation results, especially for the segmentation results of wear particle edge.

cs.CV↗

arXiv2020

Ferrograph image classification

It has been challenging to identify ferrograph images with a small dataset and various scales of wear particle. A novel model is proposed in this study to cope with these challenging problems. For the problem of insufficient samples, we first proposed a data augmentation algorithm based on the permutation of image patches. Then, an auxiliary loss function of image patch permutation recognition was proposed to identify the image generated by the data augmentation algorithm. Moreover, we designed a feature extraction loss function to force the proposed model to extract more abundant features and to reduce redundant representations. As for the challenge of large change range of wear particle size, we proposed a multi-scale feature extraction block to obtain the multi-scale representations of wear particles. We carried out experiments on a ferrograph image dataset and a mini-CIFAR-10 dataset. Experimental results show that the proposed model can improve the accuracy of the two datasets by 9% and 20% respectively compared with the baseline.

cs.CV↗

arXiv2020

Control of $\text{N}_2^+$ Air Lasing

A near-infrared laser generates gain on transitions between the $\text{B}^{\text{2}} Σ_{\text{u}}^{\text{+}}$ and $\text{X}^{\text{2}} Σ_{\text{g}}^{\text{+}}$ states of the nitrogen molecular cation in part by coupling the $\text{X}^{\text{2}} Σ_{\text{g}}^{\text{+}}$ and $\text{A}^{\text{2}} Π_{\text{u}}$ states in the V-system. Traditional time resolved pump-probe measurements rely on post-ionization coupling by the pump pulse to initialize dynamics in the $\text{A}^{\text{2}} Π_{\text{u}}$ state. Here we show that a weak second excitation pulse reduces ambiguity because it acts only on the ion independent of ionization. The additional control pulse can increase gain by moving population to the $\text{A}^{\text{2}} Π_{\text{u}}$ state, which modifies the lasing emission in two distinct ways. The presence of fast decoherence on $\text{X}^{\text{2}} Σ_{\text{g}}^{\text{+}}$ to $\text{A}^{\text{2}} Π_{\text{u}}$ transitions may prevent the formation of a coherent rotational wave packet in the ground state in our experiment, but the control pulse can reverse impulsive alignment by the pump pulse to remove rotational wave packets in the $\text{B}^{\text{2}} Σ_{\text{u}}^{\text{+}}$ state.

physics.optics↗

arXiv2020

Experimental realization of spin-tensor momentum coupling in ultracold Fermi gases

We experimentally realize the spin-tensor momentum coupling (STMC) using the three ground Zeeman states coupled by three Raman laser beams in ultracold atomic system of $^{40}$K Fermi atoms. This new type of STMC consists of two bright-state bands as a regular spin-orbit coupled spin-1/2 system and one dark-state middle band. Using radio-frequency spin-injection spectroscopy, we investigate the energy band of STMC. It is demonstrated that the middle state is a dark state in the STMC system. The realized energy band of STMC may open the door for further exploring exotic quantum matters.

cond-mat.quant-gas↗

arXiv2020

Fake massive black holes in the milli-Hertz gravitational-wave band

In gravitational wave (GW) astronomy accurate measurement of the source parameters, such as mass, relies on accurate waveform templates. Currently, the templates are developed assuming that the source, such as a binary black hole (BBH), is residing in a vacuum. However, astrophysical models predict that BBHs could form in gaseous environments, such as common envelops, stellar cores, and accretion disks of active galactic nuclei. Here we revisit the impact of gas on the GW waveforms of stellar-mass BBHs with a focus on the early inspiral phase when the GW frequency is around milli-Hertz. We show that for these BBHs, gas friction could dominate the dynamical evolution and hence duplicate chirp signals. The relevant hydrodynamical timescale, $τ_{\rm gas}$, could be much shorter than the GW radiation timescale, $τ_{\rm gw}$, in the above astrophysical scenarios. As a result, the observable chirp mass is higher than the real one by a factor of $(1+τ_{\rm gw}/τ_{\rm gas})^{3/5}$ if the gas effect is ignored in the data analysis. Such an error also results in an overestimation of the source distance by a factor of $(1+τ_{\rm gw}/τ_{\rm gas})$. By performing matched-filtering analysis in the milli-Hertz band, we prove that the gas-dominated signals are practically indistinguishable from the chirp signals of those more massive BBHs residing in a vacuum environment. Such fake massive objects in the milli-Hertz band, if not appropriately accounted for in the future, may alter our understanding of the formation, evolution, and detection of BBHs.

astro-ph.HE↗

arXiv2019

Parallel multicomponent interferometer with a spinor Bose-Einstein condensate

Atom interferometry with high visibility is of high demand for precision measurements. Here, a parallel multicomponent interferometer is achieved by preparing a spin-$2$ Bose-Einstein condensate of $^{87}$Rb atoms confined in a hybrid magneto-optical trap. After the preparation of a spinor Bose-Einstein condensate with spin degrees of freedom entangled, we observe four spatial interference patterns in each run of measurements corresponding to four hyperfine states we mainly populate in the experiment. The atomic populations in different Zeeman sublevels are made controllably using magnetic-field-pulse induced Majorana transitions. The spatial separation of atom cloud in different hyperfine states is reached by Stern-Gerlach momentum splitting. The high visibility of the interference fringes is reached by designing a proper overlap of the interfering wave packets. Due to uncontrollable phase accumulation in Majorana transitions, the phase of each individual spin is found to be subjected to unreproducible shift in multiple experimental runs. However, the relative phase across different spins is stable, paving a way towards noise-resilient multicomponent parallel interferometers.

cond-mat.quant-gas↗

arXiv2019

Detecting the Beaming Effect of Gravitational Waves

The models currently used in the detection of gravitational waves (GWs) either do not consider a relative motion between the center-of-mass of the source and the observer, or usually only consider its effect on the frequencies of GWs. However, it is known for light waves that a relative motion not only changes the frequencies but also the brightness of the source, the latter of which is called the `beaming effect'. Here we investigate such an effect for GWs and find that the observed amplitude of a GW signal, unlike the behavior of light, is not a monotonic function of the relative velocity and responds differently to the two GW polarizations. We attribute the difference to a rotation of the wave-vector, as well as a reorientation of the GW polarizations. We find that even for velocities as small as $0.25\%$ of the speed of light, ignoring the aforementioned beaming effect could induce a systematic error that is larger than the designated calibration accuracy of LIGO. This error could lead to an incorrect estimation of the distance and orbital inclination of a GW source, or result in a spurious signal that appears to be incompatible with general relativity.

astro-ph.HE↗