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Lixin Tian

Publications and source records attributed to Lixin Tian.

At least 19 recordsLinked to original sources
arXiv2024

Time persistence of climate and carbon flux networks

The persistence of the global climate system is critical for assuring the sustainability of the natural ecosystem and the further development of the prosperity of socio-economics. In this paper, we develop a framework and analyze the time persistence of the yearly networks of climate and carbon flux, based on cross-correlations between sites, using daily data from China, the contiguous United States, and the Europe land region during 2000-2019. There are many studies on time persistence of single nodes, e.g., climate variables at a given location, however persistence at a network level has been rarely discussed. Here we develop a framework to study time persistence of network and we apply it to climate and carbon flux. Our framework for determining the persistence is based on analyzing the similarity between the network structures, i.e., the links of climate and carbon flux in different years of systems using the Jaccard index. Our Jaccard results reveal that the similarity of climate and carbon flux networks in different years are within the range of 0.51$\pm$ 0.09 (p-value<0.05), implying that the climate and carbon flux networks studied in the Earth's climate system are generally persistent and in a steady state. Our results suggest that close to 50% of the links appear regularly in different years. We find a very small decay in similarity when the gap between the years increases. However, we observe unique behavior of less similarity to other years in the carbon flux network of the Chinese region during the years 2004-2005 and 2015-2016. This seems to reflect China's carbon reduction policies in these specific years. Analyzing the persistence and evolution of the climate and carbon flux networks, enhance our understanding of the spatial and temporal evolution of the global climate system.

physics.ao-ph↗
arXiv2023

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.

cs.CV↗
arXiv2022

Emergence of scaling in dockless bike-sharing systems

Fundamental laws of human mobility have been extensively studied, yet we are still lacking a comprehensive understanding of the mobility patterns of sharing conveyances. Since travellers would highly probably no longer possess their own conveyances in the near future, the interplay between travellers and sharing bikes is a central question for developing more sustainable transportation. Dockless bike-sharing systems that record detailed information of every trip provide us a unique opportunity for revealing the hidden patterns behind riding activities. By treating each bike as an individual entity, we reveal that distributions of mobility indicators of bikes are quite different from humans; and mobility patterns are even inconsistent across cities. All above discrepancies can be well explained by a choice model that is characterized by a universal scaling. Our model unveils that instead of choosing among the newest bikes, the distribution of rank values of selected bikes on usage condition manifests a truncated power-law and is quite stable across several cities despite various diversities. Our framework would have broad implications in sharing economy and contribute towards developing a greener, healthier, and more sustainable future city.

physics.soc-ph↗
arXiv2021

Option to survive or surrender: carbon asset management and optimization in thermal power enterprises from China

Carbon emission right allowance is a double-edged sword, one edge is to reduce emission as its original design intention, another edge has in practice slain many less developed coal-consuming enterprises, especially for those in thermal power industry. Partially governed on the hilt in hands of the authority, body of this sword is the prices of carbon emission right. How should the thermal power plants dance on the blade motivates this research. Considering the impact of price fluctuations of carbon emission right allowance, we investigate the operation of Chinese thermal power plant by modeling the decision-making with optimal stopping problem, which is established on the stochastic environment with carbon emission allowance price process simulated by geometric Brownian motion. Under the overall goal of maximizing the ultimate profitability, the optimal stopping indicates the timing of suspend or halt of production, hence the optimal stopping boundary curve implies the edge of life and death with regard to this enterprise. Applying this methodology, real cases of failure and survival of several Chinese representative thermal power plants were analyzed to explore the industry ecotope, which leads to the findings that: 1) The survival environment of existed thermal power plants becomes severer when facing more pressure from the newborn carbon-finance market. 2) Boundaries of survival environment is mainly drawn by the technical improvements for rising the utilization rate of carbon emission. Based on the same optimal stopping model, outlook of this industry is drawn with a demarcation surface defining the vivosphere of thermal power plants with different levels of profitability. This finding provides benchmarks for those enterprises struggling for survival and policy makers scheming better supervision and necessary intervene.

econ.GN↗
arXiv2021

Predicting hyperlinks via hypernetwork loop structure

While links in simple networks describe pairwise interactions between nodes, it is necessary to incorporate hypernetworks for modeling complex systems with arbitrary-sized interactions. In this study, we focus on the hyperlink prediction problem in hypernetworks, for which the current state-of-art methods are latent-feature-based. A practical algorithm via topological features, which can provide understandings of the organizational principles of hypernetworks, is still lacking. For simple networks, local clustering or loop reflects the correlations among nodes; therefore, loop-based link prediction algorithms have achieved accurate performance. Extending the idea to hyperlink prediction faces several challenges. For instance, what is an effective way of defining loops for prediction is not clear yet; besides, directly comparing topological statistics of variable-sized hyperlinks could introduce biases in hyperlink cardinality. In this study, we address the issues and propose a loop-based hyperlink prediction approach. First, we discuss and define the loops in hypernetworks; then, we transfer the loop-features into a hyperlink prediction algorithm via a simple modified logistic regression. Numerical experiments on multiple real-world datasets demonstrate superior performance compared to the state-of-the-art methods.

cs.SI↗
arXiv2021

Optimal networks for dynamical spreading

The inverse problem of finding the optimal network structure for a specific type of dynamical process stands out as one of the most challenging problems in network science. Focusing on the susceptible-infected-susceptible type of dynamics on annealed networks whose structures are fully characterized by the degree distribution, we develop an analytic framework to solve the inverse problem. We find that, for relatively low or high infection rates, the optimal degree distribution is unique, which consists of no more than two distinct nodal degrees. For intermediate infection rates, the optimal degree distribution is multitudinous and can have a broader support. We also find that, in general, the heterogeneity of the optimal networks decreases with the infection rate. A surprising phenomenon is the existence of a specific value of the infection rate for which any degree distribution would be optimal in generating maximum spreading prevalence. The analytic framework and the findings provide insights into the interplay between network structure and dynamical processes with practical implications.

physics.soc-ph↗
arXiv2018

Stability of periodic peakons for the Novikov equation

The Novikov equation is an integrable Camassa-Holm type equation with cubic nonlinearity and admits the periodic peakons. In this paper, it is shown that the periodic peakons are the global periodic weak solutions to the Novikov equation and we also prove the orbital stability of the periodic peakons for Novikov equation. By using the invariants of the equation and controlling the extrema of the solution, it is demonstrated that the shapes of these periodic peakons are stable under small perturbations in the energy space.

math.AP↗
arXiv2018

Existence of peakons for a cubic generalization of the Camassa-Holm equation

In this paper, we study the following generalized Camassa-Holm equation with both cubic and quadratic nonlinearities: $$ m_{t}+k_{1}(3uu_{x}m+u^2m_{x})+k_{2}(2mu_{x}+m_{x}u)=0, \quad m=u-u_{xx}, $$ which is presented as a linear combination of the Novikov equation and the Camassa-Holm equation with constants $k_{1}$ and $k_{2}$. The model is a cubic generalization of the Camassa-Holm equation. It is shown that the equation admits single-peaked soliton and periodic peakons.

math.AP↗
arXiv2018

Resilience of networks with community structure behaves as if under an external field

Detecting and characterizing community structure plays a crucial role in the study of networked systems. However, there is still a lack of understanding of how community structure affects the systems' resilience and stability. Here, we develop a framework to study the resilience of networks with community structure based on percolation theory. We find both analytically and numerically that the interlinks (connections between the communities) affect the percolation phase transition in a manner similar to an external field in a ferromagnetic-paramagnetic spin system. We also study the universality class by defining the analogous critical exponents $δ$ and $γ$, and find that their values for various models and in real-world co-authors networks follow fundamental scaling relations as in physical phase transitions. The methodology and results presented here not only facilitate the study of resilience of networks but also brings a fresh perspective to the understanding of phase transitions under external fields.

physics.soc-ph↗
arXiv2018

Inferring dissipation from the violation of Fluctuation-Dissipation Theorem

The Harada-Sasa equality elegantly connects the energy dissipation rate of a moving object with its measurable violation of the Fluctuation-Dissipation Theorem (FDT). Although proven for Langevin processes, its validity remains unclear for discrete Markov systems whose forward and backward transition rates respond asymmetrically to external perturbation. A typical example is a motor protein called kinesin. Here we show generally that the FDT violation persists surprisingly in the high-frequency limit due to the asymmetry, resulting in a divergent FDT violation integral and thus a complete breakdown of the Harada-Sasa equality. A renormalized FDT violation integral still well predicts the dissipation rate when each discrete transition produces a small entropy in the environment. Our study also suggests a new way to infer this perturbation asymmetry based on the measurable high-frequency-limit FDT violation.

cond-mat.stat-mech↗
arXiv2017

Exact results of the limited penetrable horizontal visibility graph associated to random time series and its application

The limited penetrable horizontal visibility algorithm is a new time analysis tool and is a further development of the horizontal visibility algorithm. We present some exact results on the topological properties of the limited penetrable horizontal visibility graph associated with random series. We show that the random series maps on a limited penetrable horizontal visibility graph with exponential degree distribution $P(k)\sim exp[-λ(k-2ρ-2)], λ= ln[(2ρ+3)/(2ρ+2)],ρ=0,1,2,...,k=2ρ+2,2ρ+3,...$, independent of the probability distribution from which the series was generated. We deduce the exact expressions of the mean degree and the clustering coefficient and demonstrate the long distance visibility property. Numerical simulations confirm the accuracy of our theoretical results. We then examine several deterministic chaotic series (a logistic map, the H$\acute{e}$non map, the Lorentz system, and an energy price chaotic system) and a real crude oil price series to test our results. The empirical results show that the limited penetrable horizontal visibility algorithm is direct, has a low computational cost when discriminating chaos from uncorrelated randomness, and is able to measure the global evolution characteristics of the real time series.

stat.ME↗
arXiv2013

Robustness of Network of Networks with Interdependent and Interconnected links

Robustness of network of networks (NON) has been studied only for dependency coupling (J.X. Gao et. al., Nature Physics, 2012) and only for connectivity coupling (E.A. Leicht and R.M. D Souza, arxiv:0907.0894). The case of network of n networks with both interdependent and interconnected links is more complicated, and also more closely to real-life coupled network systems. Here we develop a framework to study analytically and numerically the robustness of this system. For the case of starlike network of n ER networks, we find that the system undergoes from second order to first order phase transition as coupling strength q increases. We find that increasing intra-connectivity links or inter-connectivity links can increase the robustness of the system, while the interdependency links decrease its robustness. Especially when q=1, we find exact analytical solutions of the giant component and the first order transition point. Understanding the robustness of network of networks with interdependent and interconnected links is helpful to design resilient infrastructures.

physics.soc-ph↗
arXiv2013

Percolation on interacting networks with feedback-dependency links

When real networks are considered, coupled networks with connectivity and feedback-dependency links are not rare but more general. Here we develop a mathematical framework and study numerically and analytically percolation of interacting networks with feedback-dependency links. We find that when nodes of between networks are lowly connected, the system undergoes from second order transition through hybrid order transition to first order transition as coupling strength increases. And, as average degree of each inter-network increases, first order region becomes smaller and second-order region becomes larger but hybrid order region almost keep constant. Especially, the results implies that average degree \bar{k} between intra-networks has a little influence on robustness of system for weak coupling strength, but for strong coupling strength corresponding to first order transition system become robust as \bar{k} increases. However, when average degree k of inter-network is increased, the system become robust for all coupling strength. Additionally, when nodes of between networks are highly connected, the hybrid order region disappears and the system first order region becomes larger and secondorder region becomes smaller. Moreover, we find that the existence of feedback dependency links between interconnecting networks makes the system extremely vulnerable by comparing non-feedback condition for the same parameters.

physics.soc-ph↗
arXiv2013

Orbital stability of peakons for a generalized Camassa-Holm equation with both quadratic and cubic nonlinearity

In this paper, we investigate the orbital stability problem of peakons for a modified Camassa-Holm equation with both quadratic and cubic nonlinearity. This equation was derived from integrable theory and admits peaked soliton (peakon) and multipeakon solutions. By constructing two suitable piecewise functions, we establish the polynomial inequality relating to two conserved quantities and the maximum of the solution to this equation. The error estimate between the maximum of the solution and the peakon then follows from the structure of the polynomial inequality. Finally, we prove that a wave starting close to the peakon remains close to some translate of it at all later times, that is, the shapes of these peakons are stable under small perturbations.

math.AP↗
arXiv2009

New exact travelling wave solutions for the K(2,2) equation with osmosis dispersion

In this paper, by using bifurcation method, we successfully find the K(2,2)equation with osmosis dispersion possess two new types of travelling wave solu tions called kink-like wave solutions and antikink-like wave solutions. They are defined on some semifinal bounded domains and possess properties of kink waves and anti-kink waves. Their implicit expressions are obtained. For some concrete data, the graphs of the implicit functions are displayed, and the numerical simulation of travelling wave system is made by Maple. The results show that our theoretical analysis agrees with the numerical simulation.

nlin.PS↗