arXiv subjects

Xinchen Zhang

Publications and source records attributed to Xinchen Zhang.

31 records · Page 2Linked to original sources

arXiv2024

RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models

Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose RealCompo, a new training-free and transferred-friendly text-to-image generation framework, which aims to leverage the respective advantages of text-to-image models and spatial-aware image diffusion models (e.g., layout, keypoints and segmentation maps) to enhance both realism and compositionality of the generated images. An intuitive and novel balancer is proposed to dynamically balance the strengths of the two models in denoising process, allowing plug-and-play use of any model without extra training. Extensive experiments show that our RealCompo consistently outperforms state-of-the-art text-to-image models and spatial-aware image diffusion models in multiple-object compositional generation while keeping satisfactory realism and compositionality of the generated images. Notably, our RealCompo can be seamlessly extended with a wide range of spatial-aware image diffusion models and stylized diffusion models. Our code is available at: https://github.com/YangLing0818/RealCompo

cs.CV↗

arXiv2024

Breeding the Cat Through Superposition of Two Schrodinger Kittens Based on Coupled Waveguides

Optical Schrodinger's cat (SC) is highly anticipated because of the potential of realizing fault-tolerant quantum computing, but the practical merit is only shown when the amplitude is larger than 2. However, such high-amplitude cats have not been prepared due to the limitations rooted in the existing method. Here, we demonstrate a principle that a large SC-like state can be generated by the superposition of two kittens in which two nearby coherent states interfere and grow to an enlarged coherent-like state. Further, we propose a scheme to breed the cat beyond the limitation in the former works with a high probability by realizing the superposition of two SCs in coupled waveguides. The principle and scheme demonstrated here provide a new perspective on understanding quantum superposition in phase space and a better solution for the efficient generation of SCs on chips.

quant-ph↗

arXiv2024

HealthPrism: A Visual Analytics System for Exploring Children's Physical and Mental Health Profiles with Multimodal Data

The correlation between children's personal and family characteristics (e.g., demographics and socioeconomic status) and their physical and mental health status has been extensively studied across various research domains, such as public health, medicine, and data science. Such studies can provide insights into the underlying factors affecting children's health and aid in the development of targeted interventions to improve their health outcomes. However, with the availability of multiple data sources, including context data (i.e., the background information of children) and motion data (i.e., sensor data measuring activities of children), new challenges have arisen due to the large-scale, heterogeneous, and multimodal nature of the data. Existing statistical hypothesis-based and learning model-based approaches have been inadequate for comprehensively analyzing the complex correlation between multimodal features and multi-dimensional health outcomes due to the limited information revealed. In this work, we first distill a set of design requirements from multiple levels through conducting a literature review and iteratively interviewing 11 experts from multiple domains (e.g., public health and medicine). Then, we propose HealthPrism, an interactive visual and analytics system for assisting researchers in exploring the importance and influence of various context and motion features on children's health status from multi-level perspectives. Within HealthPrism, a multimodal learning model with a gate mechanism is proposed for health profiling and cross-modality feature importance comparison. A set of visualization components is designed for experts to explore and understand multimodal data freely. We demonstrate the effectiveness and usability of HealthPrism through quantitative evaluation of the model performance, case studies, and expert interviews in associated domains.

cs.HC↗

arXiv2024

AOC-IDS: Autonomous Online Framework with Contrastive Learning for Intrusion Detection

The rapid expansion of the Internet of Things (IoT) has raised increasing concern about targeted cyber attacks. Previous research primarily focused on static Intrusion Detection Systems (IDSs), which employ offline training to safeguard IoT systems. However, such static IDSs struggle with real-world scenarios where IoT system behaviors and attack strategies can undergo rapid evolution, necessitating dynamic and adaptable IDSs. In response to this challenge, we propose AOC-IDS, a novel online IDS that features an autonomous anomaly detection module (ADM) and a labor-free online framework for continual adaptation. In order to enhance data comprehension, the ADM employs an Autoencoder (AE) with a tailored Cluster Repelling Contrastive (CRC) loss function to generate distinctive representation from limited or incrementally incoming data in the online setting. Moreover, to reduce the burden of manual labeling, our online framework leverages pseudo-labels automatically generated from the decision-making process in the ADM to facilitate periodic updates of the ADM. The elimination of human intervention for labeling and decision-making boosts the system's compatibility and adaptability in the online setting to remain synchronized with dynamic environments. Experimental validation using the NSL-KDD and UNSW-NB15 datasets demonstrates the superior performance and adaptability of AOC-IDS, surpassing the state-of-the-art solutions. The code is released at https://github.com/xinchen930/AOC-IDS.

cs.CR↗

arXiv2023

Quantum PT-Phase Diagram in a Non-Hermitian Photonic Structure

Photonic structures have an inherent advantage to realize PT-phase transition through modulating the refractive index or gain-loss. However, quantum PT properties of these photonic systems have not been comprehensively studied yet. Here, in a bi-photonic structure with loss and gain simultaneously existing, we analytically obtained the quantum PT-phase diagram under the steady state condition. To characterize the PT-symmetry or -broken phase, we define an Hermitian exchange operator expressing the exchange between quadrature variables of two modes. If inputting several-photon Fock states into a PT-broken bi-waveguide splitting system, most photons will concentrate in the dominant waveguide with some state distributions. Quantum PT-phase diagram paves the way to the quantum state engineering, quantum interferences, and logic operations in non-Hermitian photonic systems.

physics.optics↗

arXiv2022

Gain-gain and gain-lossless PT-symmetry broken from PT-phase diagram

Parity-time (PT) symmetry and broken in micro/nano photonic structures have been investigated extensively as they bring new opportunities to control the flow of light based on non-Hermitian optics. Previous studies have focused on the situations of PT-symmetry broken in loss-loss or gain-loss coupling systems. Here, we theoretically predict the gain-gain and gain-lossless PT-broken from phase diagram, where the boundaries between PT-symmetry and PT-broken can be clearly defined in the full-parameter space including gain, lossless and loss. For specific micro/nano photonic structures, such as coupled waveguides, we give the transmission matrices of each phase space, which can be used for beam splitting. Taking coupled waveguides as an example, we obtain periodic energy exchange in PT-symmetry phase and exponential gain or loss in PT-broken phase, which are consistent with the phase diagram. The scenario giving a full view of PT-symmetry or broken, will not only deepen the understanding of fundamental physics, but also will promote the breakthrough of photonic applications like optical routers and beam splitters.

physics.optics↗

arXiv2016

Are We Approaching the Fundamental Limits of Wireless Network Densification?

The single most important factor behind the data rate increases experienced by users of wireless networks over the past few decades has been densification, namely adding more base stations and access points and thus getting more spatial reuse of the spectrum. This trend is set to continue into 5G and presumably beyond. However, at some point further densification will no longer be able to provide exponentially increasing data rates. Like the end of Moore's Law, this would have massive implications on the entire technology landscape, which depends ever more heavily on wireless connectivity. When and why will this happen? How might we prolong this from occurring for as long as possible? These are the questions explored in this paper.

cs.IT↗

arXiv2016

A 3-D Spatial Model for In-building Wireless Networks with Correlated Shadowing

Consider orthogonal planes in the 3-D space representing floors and walls in a large building. These planes divide the space into rooms where a wireless infrastructure is deployed. This paper is focused on the analysis of the correlated shadowing field created by this wireless infrastructure through the set of walls and floors. When the locations of the planes and of the wireless nodes are governed by Poisson processes, we obtain a simple stochastic model which captures the non-uniform nature of node deployment and room sizes. This model, which we propose to call the Poisson building, captures the complex in-building shadowing correlations, is scalable in the number of dimensions and is tractable for network performance analysis. It allows an exact mathematical characterization of the interference distribution in both infinite and finite buildings, which further leads to closed-form expressions for the coverage probabilities in in-building cellular networks and the success probability of in-building underlay D2D transmissions.

cs.IT↗

arXiv2015

SINR and Throughput Scaling in Ultradense Urban Cellular Networks

We consider a dense urban cellular network where the base stations (BSs) are stacked vertically as well as extending infinitely in the horizontal plane, resulting in a greater than two dimensional (2D) deployment. Using a dual-slope path loss model that is well supported empirically, we extend recent 2D coverage probability and potential throughput results to 3 dimensions. We prove that the "critical close-in path loss exponent" $α_0$ where SINR eventually decays to zero is equal to the dimensionality $d$, i.e. $α_0 \leq 3$ results in an eventual SINR of 0 in a 3D network. We also show that the potential (i.e. best case) aggregate throughput decays to zero for $α_0 < d/2$. Both of these scaling results also hold for the more realistic case that we term ${3\rm{D}^{+}}$, where there are no BSs below the user, as in a dense urban network with the user on or near the ground.

cs.IT↗

arXiv2015

Joint Rate and SINR Coverage Analysis for Decoupled Uplink-Downlink Biased Cell Associations in HetNets

Load balancing by proactively offloading users onto small and otherwise lightly-loaded cells is critical for tapping the potential of dense heterogeneous cellular networks (HCNs). Offloading has mostly been studied for the downlink, where it is generally assumed that a user offloaded to a small cell will communicate with it on the uplink as well. The impact of coupled downlink-uplink offloading is not well understood. Uplink power control and spatial interference correlation further complicate the mathematical analysis as compared to the downlink. We propose an accurate and tractable model to characterize the uplink SINR and rate distribution in a multi-tier HCN as a function of the association rules and power control parameters. Joint uplink-downlink rate coverage is also characterized. Using the developed analysis, it is shown that the optimal degree of channel inversion (for uplink power control) increases with load imbalance in the network. In sharp contrast to the downlink, minimum path loss association is shown to be optimal for uplink rate. Moreover, with minimum path loss association and full channel inversion, uplink SIR is shown to be invariant of infrastructure density. It is further shown that a decoupled association---employing differing association strategies for uplink and downlink---leads to significant improvement in joint uplink-downlink rate coverage over the standard coupled association in HCNs.

cs.IT↗

arXiv2015

A Stochastic Geometry Analysis of Inter-cell Interference Coordination and Intra-cell Diversity

Inter-cell interference coordination (ICIC) and intra-cell diversity (ICD) play important roles in improving cellular downlink coverage. Modeling cellular base stations (BSs) as a homogeneous Poisson point process (PPP), this paper provides explicit finite-integral expressions for the coverage probability with ICIC and ICD, taking into account the temporal/spectral correlation of the signal and interference. In addition, we show that in the high-reliability regime, where the user outage probability goes to zero, ICIC and ICD affect the network coverage in drastically different ways: ICD can provide order gain while ICIC only offers linear gain. In the high-spectral efficiency regime where the SIR threshold goes to infinity, the order difference in the coverage probability does not exist, however the linear difference makes ICIC a better scheme than ICD for realistic path loss exponents. Consequently, depending on the SIR requirements, different combinations of ICIC and ICD optimize the coverage probability.

cs.IT↗

arXiv2015

Downlink Cellular Network Analysis with Multi-slope Path Loss Models

Existing cellular network analyses, and even simulations, typically use the standard path loss model where received power decays like $\|x\|^{-α}$ over a distance $\|x\|$. This standard path loss model is quite idealized, and in most scenarios the path loss exponent $α$ is itself a function of $\|x\|$, typically an increasing one. Enforcing a single path loss exponent can lead to orders of magnitude differences in average received and interference powers versus the true values. In this paper we study \emph{multi-slope} path loss models, where different distance ranges are subject to different path loss exponents. We focus on the dual-slope path loss function, which is a piece-wise power law and continuous and accurately approximates many practical scenarios. We derive the distributions of SIR, SNR, and finally SINR before finding the potential throughput scaling, which provides insight on the observed cell-splitting rate gain. The exact mathematical results show that the SIR monotonically decreases with network density, while the converse is true for SNR, and thus the network coverage probability in terms of SINR is maximized at some finite density. With ultra-densification (network density goes to infinity), there exists a \emph{phase transition} in the near-field path loss exponent $α_0$: if $α_0 >1$ unbounded potential throughput can be achieved asymptotically; if $α_0 <1$, ultra-densification leads in the extreme case to zero throughput.

cs.IT↗

arXiv2014

The Performance of Successive Interference Cancellation in Random Wireless Networks

This paper provides a unified framework to study the performance of successive interference cancellation (SIC) in wireless networks with arbitrary fading distribution and power-law path loss. An analytical characterization of the performance of SIC is given as a function of different system parameters. The results suggest that the marginal benefit of enabling the receiver to successively decode k users diminishes very fast with k, especially in networks of high dimensions and small path loss exponent. On the other hand, SIC is highly beneficial when the users are clustered around the receiver and/or very low-rate codes are used. Also, with multiple packet reception, a lower per-user information rate always results in higher aggregate throughput in interference-limited networks. In contrast, there exists a positive optimal per-user rate that maximizes the aggregate throughput in noisy networks. The analytical results serve as useful tools to understand the potential gain of SIC in heterogeneous cellular networks (HCNs). Using these tools, this paper quantifies the gain of SIC on the coverage probability in HCNs with non-accessible base stations. An interesting observation is that, for contemporary narrow-band systems (e.g., LTE and WiFi), most of the gain of SIC is achieved by canceling a single interferer.

cs.IT↗