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Wenji Wu

Publications and source records attributed to Wenji Wu.

11 recordsLinked to original sources

The Cauchy problem for the improved Boussinesq equation with spatially quasi-periodic initial data

We study the Cauchy problem for the improved Boussinesq equation \[ u_{tt}-u_{xx}-u_{xxtt}-(u^2)_{xx}=0 \] on the real line with spatially quasi-periodic initial data. For a non-resonant frequency vector $\omega\in\mathbb R^\nu$, we prove local existence and uniqueness of classical spatially quasi-periodic solutions with the same frequency vector $\omega$ in two Fourier-side classes. First, for exponentially decaying initial Fourier coefficients, we obtain a spatially quasi-periodic solution whose Fourier coefficients remain exponentially decaying on an explicit time interval. Second, for initial Fourier coefficients $c(n)$ and $d(n)$ satisfying the polynomial decay $ |c(n)|+|d(n)|\lesssim (1+|n|)^{-r}, \; r>\nu+2, $ we prove that the corresponding spatially quasi-periodic solution preserves the same polynomial decay rate as the initial data. We also extend these results to the nonlinearity $u^p$ with integer $p \geq 3$.

math.AP

High-Resolution Underwater Camouflaged Object Detection: GBU-UCOD Dataset and Topology-Aware and Frequency-Decoupled Networks

Underwater Camouflaged Object Detection (UCOD) is a challenging task due to the extreme visual similarity between targets and backgrounds across varying marine depths. Existing methods often struggle with topological fragmentation of slender creatures in the deep sea and the subtle feature extraction of transparent organisms. In this paper, we propose DeepTopo-Net, a novel framework that integrates topology-aware modeling with frequency-decoupled perception. To address physical degradation, we design the Water-Conditioned Adaptive Perceptor (WCAP), which employs Riemannian metric tensors to dynamically deform convolutional sampling fields. Furthermore, the Abyssal-Topology Refinement Module (ATRM) is developed to maintain the structural connectivity of spindly targets through skeletal priors. Specifically, we first introduce GBU-UCOD, the first high-resolution (2K) benchmark tailored for marine vertical zonation, filling the data gap for hadal and abyssal zones. Extensive experiments on MAS3K, RMAS, and our proposed GBU-UCOD datasets demonstrate that DeepTopo-Net achieves state-of-the-art performance, particularly in preserving the morphological integrity of complex underwater patterns. The datasets and codes will be released at https://github.com/Wuwenji18/GBU-UCOD.

cs.CV

Theoretical Analysis and Simulations of Memory-based and All-photonic Quantum Repeaters and Networks

Developing and deploying advanced Quantum Repeater (QR) technologies will be necessary to scale quantum networks to longer distances. Depending on the error mitigation mechanisms adopted to suppress loss and errors, QRs are typically classified into memory-based or all-photonic QRs; and each type of QR may be best suited for a specific type of underlying quantum technology, a particular scale of quantum networks, or a specific regime of operational parameters. We perform theoretical analysis and simulations of quantum repeaters and networks to investigate the relative performance and resource requirements of different quantum network paradigms. Our results will help guide the optimization of quantum hardware and components and shed light on the role of a robust control plane. We present our research findings on theoretical analysis and simulations of memory-based first-generation trapped-ion quantum repeaters and networks, and all-photonic entanglement-based quantum repeaters and networks. We study the relative performance in terms of entanglement generation rate and fidelity, as well as the resource requirements of these two different quantum network paradigms.

quant-ph

Global convergence for time-periodic systems with negative feedback and applications

For the discrete-time dynamical system generated by the Poincare map T of a time-periodic closed-loop negative feedback system, we present an amenable condition which enables us to obtain the global convergence of the orbits. This yields the global convergence to the harmonic periodic solutions of the corresponding time-periodic systems with negative feedback. Our approach is motivated by embedding the negative feedback system into a larger time-periodic monotone dynamical systems. We further utilize the theoretical results to obtain the global convergence to periodic solutions for the time periodically-forced gene regulatory models. Numerical simulations are exhibited to illustrate the feasibility of our theoretical results for this model.

math.DS

Quantum Networks for High Energy Physics

Quantum networks of quantum objects promise to be exponentially more powerful than the objects considered independently. To live up to this promise will require the development of error mitigation and correction strategies to preserve quantum information as it is initialized, stored, transported, utilized, and measured. The quantum information could be encoded in discrete variables such as qubits, in continuous variables, or anything in-between. Quantum computational networks promise to enable simulation of physical phenomena of interest to the HEP community. Quantum sensor networks promise new measurement capability to test for new physics and improve upon existing measurements of fundamental constants. Such networks could exist at multiple scales from the nano-scale to a global-scale quantum network.

quant-ph

Illinois Express Quantum Network (IEQNET): Metropolitan-scale experimental quantum networking over deployed optical fiber

The Illinois Express Quantum Network (IEQNET) is a program to realize metro-scale quantum networking over deployed optical fiber using currently available technology. IEQNET consists of multiple sites that are geographically dispersed in the Chicago metropolitan area. Each site has one or more quantum nodes (Q-nodes) representing the communication parties in a quantum network. Q-nodes generate or measure quantum signals such as entangled photons and communicate the results via standard, classical, means. The entangled photons in IEQNET nodes are generated at multiple wavelengths, and are selectively distributed to the desired users via optical switches. Here we describe the network architecture of IEQNET, including the Internet-inspired layered hierarchy that leverages software-defined-networking (SDN) technology to perform traditional wavelength routing and assignment between the Q-nodes. Specifically, SDN decouples the control and data planes, with the control plane being entirely classical. Issues associated with synchronization, calibration, network monitoring, and scheduling will be discussed. An important goal of IEQNET is demonstrating the extent to which the control plane can coexist with the data plane using the same fiber lines. This goal is furthered by the use of tunable narrow-band optical filtering at the receivers and, at least in some cases, a wide wavelength separation between the quantum and classical channels. We envision IEQNET to aid in developing robust and practical quantum networks by demonstrating metro-scale quantum communication tasks such as entanglement distribution and quantum-state teleportation.

quant-ph

G-NetMon: A GPU-accelerated Network Performance Monitoring System for Large Scale Scientific Collaborations

Network traffic is difficult to monitor and analyze, especially in high-bandwidth networks. Performance analysis, in particular, presents extreme complexity and scalability challenges. GPU (Graphics Processing Unit) technology has been utilized recently to accelerate general purpose scientific and engineering computing. GPUs offer extreme thread-level parallelism with hundreds of simple cores. Their data-parallel execution model can rapidly solve large problems with inherent data parallelism. At Fermilab, we have prototyped a GPU-accelerated network performance monitoring system, called G-NetMon, to support large-scale scientific collaborations. In this work, we explore new opportunities in network traffic monitoring and analysis with GPUs. Our system exploits the data parallelism that exists within network flow data to provide fast analysis of bulk data movement between Fermilab and collaboration sites. Experiments demonstrate that our G-NetMon can rapidly detect sub-optimal bulk data movements.

cs.NI

A Transport-Friendly NIC for Multicore/Multiprocessor Systems

Receive side scaling (RSS) is a network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments. However, existing RSS-enabled NICs lack a critical data steering mechanism that would automatically steer incoming network data to the same core on which its application process resides. This absence causes inefficient cache usage if an application is not running on the core on which RSS has scheduled the received traffic to be processed. In Linux systems, it cannot even ensure that packets in a TCP flow are processed by a single core, even if the interrupts for the flow are pinned to a specific core. This results in degraded performance. In this paper, we develop such a data steering mechanism in the NIC for multicore or multiprocessor systems. This data steering mechanism is mainly targeted at TCP, but it can be extended to other transport layer protocols. We term a NIC with such a data steering mechanism "A Transport Friendly NIC" (A-TFN). Experimental results have proven the effectiveness of A-TFN in accelerating TCP/IP performance.

cs.NI

Why Does Flow Director Cause Packet Reordering?

Intel Ethernet Flow Director is an advanced network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments and can automatically steer incoming network data to the same core on which its application process resides. However, our analysis and experiments show that Flow Director cannot guarantee in-order packet delivery in multiprocessing environments. Packet reordering causes various negative impacts. E.g., TCP performs poorly with severe packet reordering. In this paper, we use a simplified model to analyze why Flow Director can cause packet reordering. Our experiments verify our analysis.

cs.NI

Sorting Reordered Packets with Interrupt Coalescing

TCP performs poorly in networks with serious packet reordering. Processing reordered packets in the TCP layer is costly and inefficient, involving interaction of the sender and receiver. Motivated by the interrupt coalescing mechanism that delivers packets upward for protocol processing in blocks, we propose a new strategy, Sorting Reordered Packets with Interrupt Coalescing (SRPIC), to reduce packet reordering in the receiver. SRPIC works in the network device driver; it makes use of the interrupt coalescing mechanism to sort the reordered packets belonging to the same TCP stream in a block of packets before delivering them upward; each sorted block is internally ordered. Experiments have proven the effectiveness of SRPIC against forward-path reordering.

cs.NI