arXiv subjects

Peng Yuan

Publications and source records attributed to Peng Yuan.

At least 37 records · Page 2Linked to original sources

arXiv2024

MDS-GNN: A Mutual Dual-Stream Graph Neural Network on Graphs with Incomplete Features and Structure

Graph Neural Networks (GNNs) have emerged as powerful tools for analyzing and learning representations from graph-structured data. A crucial prerequisite for the outstanding performance of GNNs is the availability of complete graph information, i.e., node features and graph structure, which is frequently unmet in real-world scenarios since graphs are often incomplete due to various uncontrollable factors. Existing approaches only focus on dealing with either incomplete features or incomplete structure, which leads to performance loss inevitably. To address this issue, this study proposes a mutual dual-stream graph neural network (MDS-GNN), which implements a mutual benefit learning between features and structure. Its main ideas are as follows: a) reconstructing the missing node features based on the initial incomplete graph structure; b) generating an augmented global graph based on the reconstructed node features, and propagating the incomplete node features on this global graph; and c) utilizing contrastive learning to make the dual-stream process mutually benefit from each other. Extensive experiments on six real-world datasets demonstrate the effectiveness of our proposed MDS-GNN on incomplete graphs.

cs.LG↗

arXiv2024

Amplify Graph Learning for Recommendation via Sparsity Completion

Graph learning models have been widely deployed in collaborative filtering (CF) based recommendation systems. Due to the issue of data sparsity, the graph structure of the original input lacks potential positive preference edges, which significantly reduces the performance of recommendations. In this paper, we study how to enhance the graph structure for CF more effectively, thereby optimizing the representation of graph nodes. Previous works introduced matrix completion techniques into CF, proposing the use of either stochastic completion methods or superficial structure completion to address this issue. However, most of these approaches employ random numerical filling that lack control over noise perturbations and limit the in-depth exploration of higher-order interaction features of nodes, resulting in biased graph representations. In this paper, we propose an Amplify Graph Learning framework based on Sparsity Completion (called AGL-SC). First, we utilize graph neural network to mine direct interaction features between user and item nodes, which are used as the inputs of the encoder. Second, we design a factorization-based method to mine higher-order interaction features. These features serve as perturbation factors in the latent space of the hidden layer to facilitate generative enhancement. Finally, by employing the variational inference, the above multi-order features are integrated to implement the completion and enhancement of missing graph structures. We conducted benchmark and strategy experiments on four real-world datasets related to recommendation tasks. The experimental results demonstrate that AGL-SC significantly outperforms the state-of-the-art methods.

cs.IR↗

arXiv2023

Non-Hermitian Optical Parametric Systems with Anti-parity-time Symmetry

The continuous advancements in ultrafast lasers, characterized by high pulse energy, great average power, and ultrashort pulse duration, have opened up new frontiers and applications in various fields such as high-energy-density science. In this study, we investigated the implementation of non-Hermitian nonlinear parametric amplification by introducing anti-parity-time (anti-PT) symmetry to three-wave interaction processes. By exploring the parameter space defined by the coupling coefficient, phase mismatch, and absorption, we categorized the behavior of the non-Hermitian optical parametric system into four distinct quadrants, representing unbroken/broken anti-PT symmetry and amplification/attenuation, and amplification-attenuation boundaries and exceptional lines can be observed in such parametric space. Through simulations of the dynamical behavior of the interacting waves, we demonstrated the rich evolutions of the signal and idler waves in systems belonging to the respective quadrants and near exceptional points, revealed by the unique performance of eigenmodes. Our findings provide insights into the evaluation of energy flow direction in optical parametric amplification engineering by the directly linked parameter space, which contribute to a deeper understanding of photonics and laser science, potentially leading to new applications in these fields.

physics.optics↗

arXiv2023

Laboratory observation of ion acceleration via reflection off laser-produced magnetized collisionless shocks

Fermi acceleration by collisionless shocks is believed to be the primary mechanism to produce high energy charged particles in the Universe,where charged particles gain energy successively from multiple reflections off the shock front.Here,we present the first direct experimental evidence of ion energization from reflection off a supercritical quasi perpendicular collisionless shock,an essential component of Fermi acceleration in a laser produced magnetized plasma. We observed a quasi monoenergetic ion beam with 2,4 times the shock velocity in the upstream flow using time of flight method. Our related kinetic simulations reproduced the energy gain and showed that these ions were first reflected and then accelerated mainly by the motional electric field associated with the shock. This mechanism can also explain the quasi monoenergetic fast ion component observed in the Earth's bow shock.

physics.plasm-ph↗

arXiv2023

Optimal stopping: Bermudan strategies meet non-linear evaluations

We address an optimal stopping problem over the set of Bermudan-type strategies $Θ$ (which we understand in a more general sense than the stopping strategies for Bermudan options in finance) and with non-linear operators (non-linear evaluations) assessing the rewards, under general assumptions on the non-linear operators $ρ$. We provide a characterization of the value family V in terms of what we call the ($ρ$,$Θ$) -Snell envelope of the pay-off family. We establish a Dynamic Programming Principle. We provide an optimality criterion in terms of a ($ρ$,$Θ$) -martingale property of V on a stochastic interval. We investigate the ($ρ$,$Θ$)-martingale structure and we show that the ''first time'' when the value family coincides with the pay-off family is optimal. The reasoning simplifies in the case where there is a finite number n of pre-described stopping times, where n does not depend on the scenario $ω$. We provide examples of non-linear operators entering our framework.

math.OC↗

arXiv2022

An AFDM-Based Integrated Sensing and Communications

This paper considers an affine frequency division multiplexing (AFDM)-based integrated sensing and communications (ISAC) system, where the AFDM waveform is used to simultaneously carry communications information and sense targets. To realize AFDM-based sensing functionality, two parameter estimation methods are designed to process echoes in the time domain and the discrete affine Fourier transform (DAFT) domain, respectively. It allows us to decouple delay and Doppler shift in the fast time axis and can maintain good sensing performance even in large Doppler shift scenarios. Numerical results verify the effectiveness of our proposed AFDM-based system in high mobility scenarios.

eess.SP↗

arXiv2022

Direct ultrafast parametric amplification pumped by a picosecond thin-disk laser

Optical quadratic nonlinearity is ultrafast in nature, while parametric interaction usually manifests only the broadband characteristic. Enormous progress has been made toward broadband phase-matching for parametric amplification and wide applications. In existing devices of broadband parametric amplification, the power efficiency of conversion is restricted to approximately the energy efficiency, and the desire for the signal power enhancement necessitates additional pulse compression after amplification. Here, we demonstrate ultrafast parametric amplification having an extraordinary power efficiency of 1155%; this allows the generation of intense femtosecond pulses without the need for a pulse stretcher and compressor. Direct femtosecond signal amplification by picosecond pumping is enabled by an ultrafast parametric environment in which the pre-delayed signal of faster speed gradually overtakes and effectively depletes the pump of slower speed as they propagate in a nonlinear crystal. The demonstrated technique should lead to breakthroughs in ultrafast lasers as well as applications.

physics.optics↗

arXiv2021

Self-repairing high entropy oxides

All biological organisms, from plants to living creatures, can heal minor wounds and damage. The realization of a similar self-healing capacity in inorganic materials has been a design target for many decades. This would represent a breakthrough in materials engineering, enabling many novel technological applications, since such materials would be able to resist damage caused by electromagnetic irradiation and/or mechanical impact. Here we demonstrate that a high-entropy oxide is intrinsically capable of undergoing an autonomous self-repairing process. Transmission electron microscopy revealed that the spinel structure of (AlCoCrCu0.5FeNi)3O4 can regrow and repair itself at the atomic level when damaged. Density functional theory calculations reveal that the extra enthalpy stored in the high entropy material during fabrication can be released to effectively heal macroscopic defects by regrowing into a partially ordered state. This extraordinary self-repairing phenomenon makes this new material highly desirable as a coating, enabling structures used in harsh environments to better withstand damage, such as cosmic irradiation in space, nuclear irradiation in nuclear power facilities, or tribological damage. Most importantly, our results set the general design principles for the synthesis of self-repairing materials.

cond-mat.mtrl-sci↗

arXiv2021

K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce

Existing pre-trained language models (PLMs) have demonstrated the effectiveness of self-supervised learning for a broad range of natural language processing (NLP) tasks. However, most of them are not explicitly aware of domain-specific knowledge, which is essential for downstream tasks in many domains, such as tasks in e-commerce scenarios. In this paper, we propose K-PLUG, a knowledge-injected pre-trained language model based on the encoder-decoder transformer that can be transferred to both natural language understanding and generation tasks. We verify our method in a diverse range of e-commerce scenarios that require domain-specific knowledge. Specifically, we propose five knowledge-aware self-supervised pre-training objectives to formulate the learning of domain-specific knowledge, including e-commerce domain-specific knowledge-bases, aspects of product entities, categories of product entities, and unique selling propositions of product entities. K-PLUG achieves new state-of-the-art results on a suite of domain-specific NLP tasks, including product knowledge base completion, abstractive product summarization, and multi-turn dialogue, significantly outperforms baselines across the board, which demonstrates that the proposed method effectively learns a diverse set of domain-specific knowledge for both language understanding and generation tasks.

cs.CL↗

arXiv2021

Resolving ultrahigh-contrast ultrashort pulses with single-shot cross-correlator at the photon noise limit

In strong-field physics experiments with intense lasers, it is of paramount importance to single-shot diagnose the temporal contrast between laser pulse peak and its noise pedestal. This allows fast optimization of pulse contrast and meaningful comparison with theory for each pulse shot, and it can help new outcomes from clean laser-plasma interactions. Thus far, high contrast ratios up to ~10^10, required by present petawatt (PW) class lasers, have been accessible in both generation and single-shot characterization. However, ultrahigh contrast ~10^13, required by the planned 200-PW lasers, challenges intense laser technology and remains an open question. This paper reports on the first demonstration of such an ultrahigh-contrast measurement by adapting single-shot cross-correlator (SSCC). We introduce an ultrafast method that enables to determine the SSCC detection limit. Our strategy mimics the test laser having known ultrahigh contrast in the measurement frame of time-to-space mapping. The ultimate contrast-measurement limit of 10^13 is achieved, which corresponds to the highest pulse intensity set by SSCC damage threshold and the lowest noise pedestal set by single-photon detection. As a consequence, photon noise in the detection is observed and increases as the noise pedestal reduces. The demonstrated measurement ability at the photon noise limit is applied to a high-contrast laser system based on second-harmonic generation and optical parametric chirped-pulse amplification, suggesting accessible of ultrahigh contrast pulses.

physics.optics↗

arXiv2020

A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data

Unsupervised domain adaptation (UDA) assumes that source and target domain data are freely available and usually trained together to reduce the domain gap. However, considering the data privacy and the inefficiency of data transmission, it is impractical in real scenarios. Hence, it draws our eyes to optimize the network in the target domain without accessing labeled source data. To explore this direction in object detection, for the first time, we propose a source data-free domain adaptive object detection (SFOD) framework via modeling it into a problem of learning with noisy labels. Generally, a straightforward method is to leverage the pre-trained network from the source domain to generate the pseudo labels for target domain optimization. However, it is difficult to evaluate the quality of pseudo labels since no labels are available in target domain. In this paper, self-entropy descent (SED) is a metric proposed to search an appropriate confidence threshold for reliable pseudo label generation without using any handcrafted labels. Nonetheless, completely clean labels are still unattainable. After a thorough experimental analysis, false negatives are found to dominate in the generated noisy labels. Undoubtedly, false negatives mining is helpful for performance improvement, and we ease it to false negatives simulation through data augmentation like Mosaic. Extensive experiments conducted in four representative adaptation tasks have demonstrated that the proposed framework can easily achieve state-of-the-art performance. From another view, it also reminds the UDA community that the labeled source data are not fully exploited in the existing methods.

cs.CV↗

arXiv2019

Van der Waals stacked multilayer in-plane graphene/hexagonal boron nitride heterostructure: its interfacial thermal transport properties

Combining both vertical and in-plane two-dimensional (2D) heterostructures opens up the possibility to create an unprecedented architecture using 2D atomic layer building blocks. The thermal transport properties of such mixed heterostructures, critical to various applications in nanoelectronics, however, have not been thoroughly explored. Herein, we construct two configurations of multilayer in-plane graphene/hexagonal boron nitride (Gr/h-BN) heterostructures (i.e. mixed heterostructures) via weak van der Waals (vdW) interactions and systematically investigate the dependence of their interfacial thermal conductance (ITC) on the number of layers using non-equilibrium molecular dynamics (NEMD) simulations. The computational results show that the ITC of two configurations of multilayer in-plane Gr/h-BN heterostructures (MIGHHs) decrease with increasing layer number n and both saturate at n = 3. And surprisingly, we find that the MIGHH is more advantageous to interfacial thermal transport than the monolayer in-plane Gr/h-BN heterostructure, which is in strong contrast to the commonly held notion that the multilayer structures of Gr and h-BN suppress the phonon transmission. The underlying physical mechanisms for these puzzling phenomena are probed through the analyses of heat flux, temperature jump, stress concentration factor, overlap of phonon vibrational spectra and phonon participation ratio. In particular, by changing the stacking angle of MIGHH, a higher ITC can be obtained due to the thermal rectification behavior. Furthermore, we find that the ITC in MIGHH can be well-regulated by controlling the coupling strength between layers. Our findings here are of significance for understanding the interfacial thermal transport behaviors of multilayer in-plane Gr/h-BN heterostructure, and are expected to attract extensive interest in exploring its new physics and applications.

cond-mat.mtrl-sci↗

arXiv2018

Black phosphorus Q-switched and mode-locked Er:ZBLAN fiber lasers at 3.5 um

With the proposal of dual-wavelength pumping (DWP) scheme, DWP Er:ZBLAN fiber lasers at 3.5 um have become a fascinating area of research. However, limited by the absence of suitable saturable absorber, passively Q-switched and mode-locked fiber lasers have not been realized in this spectral region. Based on the layer-dependent bandgap and excellent photoelectric characteristics of black phosphorus (BP), BP is a promising candidate for saturable absorber near 3.5 um. Here, we fabricated a 3.5-um saturable absorber mirror (SAM) by transferring liquid-phase exfoliated BP flakes onto a gold-coated mirror. With the as-prepared BP SAM, we realized stable Q-switching and continuous-wave mode-locking operations in the DWP Er:ZBLAN fiber lasers at 3.5 um. To the best of our knowledge, it is the first time to achieve passively Q-switched and mode-locked pulses in 3.5 um spectral region. The research results will not only promote the development of 3.5-um pulsed fiber lasers but also open the photonic application of two-dimensional materials in this spectral region

physics.optics↗

arXiv2017

Diode-pumped mode-locked femtosecond 2-um Tm:CaYAlO4 laser

Continuous-wave mode-locked femtosecond 2 um solid-state laser with a c-cut Tm:CaYAlO4 as gain medium was experimentally demonstrated. The mode locked laser generated stable pulses with average output power as high as 531 mW, pulse duration of 496 fs, and repetition rate of 97 MHz at 1975 nm. The research results show that Tm:CaYAlO4 is an excellent gain medium for femtosecond pulse generation at 2um wavelength.

physics.optics↗

arXiv2017

Efficient Privacy Preserving Viola-Jones Type Object Detection via Random Base Image Representation

A cloud server spent a lot of time, energy and money to train a Viola-Jones type object detector with high accuracy. Clients can upload their photos to the cloud server to find objects. However, the client does not want the leakage of the content of his/her photos. In the meanwhile, the cloud server is also reluctant to leak any parameters of the trained object detectors. 10 years ago, Avidan & Butman introduced Blind Vision, which is a method for securely evaluating a Viola-Jones type object detector. Blind Vision uses standard cryptographic tools and is painfully slow to compute, taking a couple of hours to scan a single image. The purpose of this work is to explore an efficient method that can speed up the process. We propose the Random Base Image (RBI) Representation. The original image is divided into random base images. Only the base images are submitted randomly to the cloud server. Thus, the content of the image can not be leaked. In the meanwhile, a random vector and the secure Millionaire protocol are leveraged to protect the parameters of the trained object detector. The RBI makes the integral-image enable again for the great acceleration. The experimental results reveal that our method can retain the detection accuracy of that of the plain vision algorithm and is significantly faster than the traditional blind vision, with only a very low probability of the information leakage theoretically.

cs.CV↗

arXiv2017

High-Contrast Chirped-Pulse Amplification Enabled by In-Band Noise Filtering

Lasers that generate ultra-intense light pulses are under development for experiments in high-field and high-energy-density physics, as well as for applications such as particle acceleration. Extensions to even higher powers are being considered for future investigations that can only be imagined today, such as the quantum electrodynamics of plasmas and isolated attosecond-pulse generation with solid targets. For all of these areas, it is vital to produce high-contrast pulses, so that no pre-plasma is created in the target before the arrival of the main pulse. However, noise is unavoidable in high-gain amplification, and is manifested in the form of background light that accompanies pulses generated by chirped-pulse amplification (CPA). Here, we introduce a linear filtering technique based on spatio-spectral coupling, which allows in-band filtering of amplified pulses for the first time. Experiments demonstrate approximately 40 times contrast enhancement in optical parametric chirped-pulse amplification (OPCPA) and provide a foundation for scaling to much higher performance. The simplicity, efficiency, and direct compatibility with existing techniques for short-pulse generation will make spatio-spectral filtering attractive to a wide range of applications in ultrafast optics and time-resolved spectroscopy, and may open new directions in noise reduction.

physics.optics↗

arXiv2015

Black phosphorus mode-locked Er-doped ZBLAN fiber laser at 2.8 um wavelength

Mid-infrared saturable absorber mirror is successfully fabricated by transferring the mechanically exfoliated black phosphorus onto the gold-coated mirror. With the as-prepared black phosphorus saturable absorber mirror, a continuous-wave passively mode-locked Er:ZBLAN fiber laser is demonstrated at the wavelength of 2.8 um, which delivers a maximum average output power of 613 mW, a repetition rate of 24 MHz and a pulse duration of 42 ps. To the best of our knowledge, it is the first time to demonstrate black phosphorus mode-locked laser at 2.8 um wavelength. Our results demonstrate the feasibility of black phosphorus flake as a new two-dimensional material for application in mid-infrared ultrafast photonics.

physics.optics↗

arXiv2015

Multilayer black phosphorus as broadband saturable absorber for pulsed lasers from 1 to 2.7 μm wavelength

It attracts wide interest to seek universe saturable absorber covering wavelengths from near infrared to mid-infrared band. Multilayer black phosphorus, with variable direct bandgap (0.3-2 eV) depending on the layer number, becomes a good alternative as a universe saturable absorber for pulsed lasers. In this contribution, we first experimentally demonstrated broadband saturable absorption of multilayer black phosphorus from 1 μm to 2.7 μm wavelength. With the as-fabricated black phosphorus nanoflakes as saturable absorber, stable Q-switching operation of bulk lasers at 1.03 μm, 1.93 μm, 2.72 μm were realized, respectively. In contrast with large-bandgap semiconducting transition metal dichalcogenides, such as MoS2, MoSe2, multilayer black phosphorus shows particular advantage at the long wavelength regime thanks to its narrow direct bandgap. This work will open promising optoelectronic applications of black phosphorus in mid-infrared spectral region and further demonstrate that BP may fill the gap of between zero-bandgap graphene and large-bandgap TMDs.

physics.optics↗