Article
Physics, Fluids & Plasmas
Hanshuang Chen, Yanfei Ye
Summary: This study investigates discrete-time random walks on networks subject to time-dependent stochastic resetting. The results demonstrate that time-modulated resetting protocols can be more advantageous in accelerating the completion of a target search process compared to constant-probability resetting.
Article
Physics, Multidisciplinary
J. Klinger, R. Voituriez, O. Benichou
Summary: We derive a universal and exact asymptotic form of the splitting probability for symmetric continuous jump processes, which highlights the importance of microscopic dynamics and provides explicit predictions for characterizing the effective random process in light scattering.
PHYSICAL REVIEW LETTERS
(2022)
Article
Chemistry, Multidisciplinary
Ilia A. Solov'yov, Gennady Sushko, Ida Friis, Andrey V. Solov'yov
Summary: This paper discusses the application of stochastic dynamics in complex systems and its implementation in MBN Explorer. It introduces the basic concepts and theories of stochastic dynamics and provides several examples to demonstrate its applicability in different systems.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2022)
Article
Mechanics
Tian Zhou, Pece Trajanovski, Pengbo Xu, Weihua Deng, Trifce Sandev, Ljupco Kocarev
Summary: We investigate a one-dimensional Brownian search with trapping. The particle's diffusion equation is described by a memory kernel in the general waiting time probability density function. We determine the general form of the first arrival time density, search reliability, and efficiency, and examine various special cases of the memory kernel. We also analyze the Levy search with trapping for single and multiple targets, as well as combined Levy-Brownian search strategies for a single target. These findings are general and have implications for studying optimal search strategies and the spread of contamination in animal foraging or environmental settings.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2022)
Article
Mathematics, Interdisciplinary Applications
Pablo Medina, Sebastian C. Carrasco, Maria Sara Jofre, Jose Rogan, Juan Alejandro Valdivia
Summary: This study investigates the possibility of characterizing city transportation using the analogy of diffusing particles. By using a cellular automata model in a road network, the dynamics of vehicles in a city are recreated. The mean velocity and diffusion coefficient are calculated through statistical analysis of the parametric curves generated by car movements. The study also discusses the potential use of the diffusion coefficient to characterize a city, similar to the traditional use of mean speed and flux rate, and explores methods to calculate this quantity in a smart city.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Mechanics
Paul C. Bressloff
Summary: This paper develops the theory of drift-diffusion on a semi-infinite Cayley tree with stochastic resetting, exploring phase transitions in optimal resetting rates and identifying the critical velocities associated with these transitions. The critical velocity of the LD transition serves as an upper bound for other critical velocities, with only the critical velocity of the LD transition having a simple universal dependence on the coordination number.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Mathematics, Applied
Gabriel G. da Rocha, Ervin K. Lenzi
Summary: In this study, we investigate a diffusion process by simultaneously considering stochastic resetting and linear reaction kinetics. We initially discuss the formalism for a single species and then extend it to multiple species. By analyzing a general probability density function for the random walk, we obtain diverse behaviors for the waiting time and jumping probability distributions. These distributions' behaviors have implications for the diffusion-like equations derived from this approach and can be connected to different fractional operators with singular or nonsingular kernels. We also demonstrate that diffusion-like equations can exhibit a wide range of behaviors associated with various processes, particularly anomalous diffusion.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Review
Mathematics
Guo-Qiang Cai, Ronghua Huan, Weiqiu Zhu
Summary: This paper systematically presents three methods to generate two correlated stationary Gaussian processes, including the method of linear filters, the method of series expansion with random amplitudes, and the method of series expansion with random phases. These methods aim to match the power spectral density for each process with different levels of correlation information. The advantages and disadvantages of each method are discussed.
Article
Physics, Multidisciplinary
Giulia Cencetti, Diego Andres Contreras, Marco Mancastroppa, Alain Barrat
Summary: Contagion processes on networks can be described as simple or complex contagion, but it is difficult to determine the underlying mechanism based on empirical data. We propose a strategy to distinguish between these mechanisms by observing the order of node infection and its correlation with local topology. Our results enhance understanding of contagion processes and offer a method to differentiate between different contagion mechanisms with limited information.
PHYSICAL REVIEW LETTERS
(2023)
Article
Physics, Multidisciplinary
Eman A. AL-hada, Xiangong Tang, Weihua Deng
Summary: Stochastic processes play a significant role in various fields such as ecology, biology, chemistry, and computer science. Anomalies in diffusion, known as anomalous diffusion (AnDi), are important in transport dynamics. However, identifying AnDi can be challenging, and machine learning algorithms like convolutional neural networks can help tackle this issue.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Physics, Multidisciplinary
Axel Maso-Puigdellosas, Trifce Sandev, Vicenc Mendez
Summary: In this study, we investigate the dynamics of a random walker moving on a comb structure with stochastic resetting. We consider two types of resetting, global and local, and analyze their effects on the walker's mean squared displacement. Our findings show that the interplay between the waiting process and resetting leads to different diffusion behaviors, including normal diffusion, subdiffusion, and a crossover between them. Global resetting has a more drastic effect, either leading to constant displacement or two distinct regimes of subdiffusive motion.
Article
Physics, Multidisciplinary
Jiating Yu, Jiacheng Leng, Duanchen Sun, Ling-Yun Wu
Summary: Network models are widely used in various fields for their ability to represent relationships between variables. Network structure can be unclear due to factors like experimental noise and missing data, hindering downstream analyses such as community detection. Therefore, network denoising is necessary before analysis. However, the importance of network pre-processing for community detection has been neglected. In this study, a novel network denoising method, called Network Refinement (NR), was proposed to enhance the self-organization properties of complex networks through a global diffusion process. NR significantly improved the clarity of the network's mesoscale structure and boosted the performance of various community detection algorithms.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Yue Ren, Haijun Jiang, Jiarong Li, Binglong Lu
Summary: This paper investigates the finite-time synchronization issue of stochastic complex networks with random coupling delay and nonlinear coupling function. A quantized aperiodically intermittent control strategy is proposed, and the effectiveness and feasibility of the obtained results are demonstrated through a numerical example.
Article
Mathematics, Interdisciplinary Applications
Chengyi Tu, Jianhong Luo, Ying Fan, Xuwei Pan
Summary: Dimensionality reduction is a powerful tool for analyzing complex systems and uncovering their underlying mechanisms and phenomena. We have developed a framework for dimensionality reduction of stochastic complex dynamical networks, which can capture the essential features and long-term dynamics of the original system in a low-dimensional effective equation.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Physics, Multidisciplinary
Alejandro P. Riascos, Francisco Hernandez Padilla
Summary: In this paper, a framework for comparing differences in occupation probabilities of two random walk processes on networks is presented. The framework considers modifications of the network or the transition probabilities between nodes. A dissimilarity measure is defined using the eigenvalues and eigenvectors of the normalized Laplacian. The framework is used to examine differences in diffusive dynamics, the effect of new edges and rewiring in networks, and divergences in transport in degree-biased random walks and random walks with stochastic reset.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2023)
Article
Computer Science, Information Systems
Huan Li, Stacy Patterson, Yuhao Yi, Zhongzhi Zhang
IEEE TRANSACTIONS ON INFORMATION THEORY
(2020)
Article
Optics
Che Chen, Sang-Hyun Oh, Mo Li
Article
Optics
Qingyang Du, Jerome Michon, Bingzhao Li, Derek Kita, Danhao Ma, Haijie Zuo, Shaoliang Yu, Tian Gu, Anuradha Agarwal, Mo Li, Juejun Hu
PHOTONICS RESEARCH
(2020)
Article
Chemistry, Multidisciplinary
Daniel Tofan, Yukako Sakazaki, Kendahl L. Walz Mitra, Ruoming Peng, Seokhyeong Lee, Mo Li, Alexandra Velian
Summary: This study introduces a facile solution-phase protocol to modify the Lewis basic surface of few-layer black phosphorus (bP) and demonstrates the effectiveness of Al and Ga halides in preventing ambient degradation of bP. Various microscopic and spectroscopic methods are used to investigate the interaction between Lewis acids and the bP lattice, showing that the protocol opens a path for deterministic and persistent tuning of electronic properties in bP.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2021)
Article
Multidisciplinary Sciences
Changming Wu, Heshan Yu, Seokhyeong Lee, Ruoming Peng, Ichiro Takeuchi, Mo Li
Summary: Neuromorphic photonics is a promising hardware accelerator with potential speed and energy advantages in machine learning algorithms, particularly in analog computing tasks. Integration of nonvolatile phase-change materials enables essential programming and computing capabilities for on-chip optical computing, demonstrating high precision in waveguide spatial modes control for efficient MVM computation in neural networks.
NATURE COMMUNICATIONS
(2021)
Article
Physics, Applied
Yifei Zhang, Carlos Rios, Mikhail Y. Shalaginov, Mo Li, Arka Majumdar, Tian Gu, Juejun Hu
Summary: PCMs show unique optical and phase change properties, making them promising materials for integrated photonics and free-space optics. It is important to have a thorough understanding of their characteristics in photonic applications and explore new research frontiers in this field.
APPLIED PHYSICS LETTERS
(2021)
Article
Multidisciplinary Sciences
Changming Wu, Xiaoxuan Yang, Heshan Yu, Ruoming Peng, Ichiro Takeuchi, Yiran Chen, Mo Li
Summary: Researchers demonstrate a photonic generative network that can generate handwritten numbers and show resilience to hardware nonidealities. These results suggest the potential of more complex photonic generative networks based on photonic hardware.
Article
Nanoscience & Nanotechnology
Po-Liang Chen, Yueyang Chen, Tian-Yun Chang, Wei-Qing Li, Jia-Xin Li, Seokhyeong Lee, Zhuoran Fang, Mo Li, Arka Majumdar, Chang-Hua Liu
Summary: The extension of the operation wavelength of silicon photonics to the mid-infrared band is of great importance for fields such as health care, astronomy, and chemical sensing. However, a major challenge for mid-IR silicon photonics has been the lack of high-speed, high-responsivity, and low noise-equivalent power photodetectors. In this study, researchers demonstrated a van der Waals heterostructure mid-IR photodetector integrated on a silicon-on-insulator waveguide, which exhibited high responsivity and stable switching performance.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Multidisciplinary Sciences
Seokhyeong Lee, Ruoming Peng, Changming Wu, Mo Li
Summary: The authors report the realization of a programmable image sensor based on black phosphorus that can perform multispectral imaging and analog in-memory computing in the near- to mid-infrared range. The sensor enables in-sensor computing, reducing communication latency and power consumption. This multifunctional infrared image sensor has great potential for distributed and remote multispectral sensing applications.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Han Zhao, Bingzhao Li, Huan Li, Mo Li
Summary: This study demonstrates an efficient silicon-based acousto-optic modulator that performs large-scale complex-valued matrix-vector multiplications on synthetic frequency lattices. By harnessing the resonantly enhanced strong electro-optomechanical coupling, the modulator achieves full-range phase-coherent frequency conversions across the entire synthetic lattice, constituting a fully connected linear computing layer.
NATURE COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Changming Wu, Xiaoxuan Yang, Yiran Chen, Mo Li
Summary: The Bayesian neural network (BNN) combines neural networks and statistical modeling to perform posterior predictions and quantify prediction uncertainty. Integrated photonics is a promising hardware platform for energy-efficient, low latency, and parallel computing neural network accelerators. However, most photonic neural networks are deterministic models. In this study, we propose a photonic Bayesian neural network (P-BNN) architecture that extends the photonic neural network to a statistical model and utilizes optical noises. The P-BNN demonstrates advantages in prediction and outlier detection, showing promise for practical neural network applications.
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS
(2023)
Review
Nanoscience & Nanotechnology
Akshay Singh, Seong Soon Jo, Yifei Li, Changming Wu, Mo Li, R. Jaramillo
Article
Materials Science, Multidisciplinary
Ruoming Peng, Changming Wu, Huan Li, Xiaodong Xu, Mo Li
Proceedings Paper
Computer Science, Theory & Methods
Zuobai Zhang, Wanyue Xu, Zhongzhi Zhang
PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (WSDM '20)
(2020)
Article
Computer Science, Hardware & Architecture
Yuan Lin, Zhongzhi Zhang