43 citations · 74 across the 16 of their papers we have counts for
16 papers
Fluid-network relations: decay laws meet with spatial self-similarity, scale-invariance, and control scaling
Yang Tian, Pei Sun, Yizhou Xu
Diverse implicit structures of fluids are discovered lately, providing opportunities to study the physics of fluids applying network analysis. Although considerable works devote to…
Fast renormalizing the structures and dynamics of ultra-large systems via random renormalization group
Yang Tian, Yizhou Xu, Pei Sun
Criticality and symmetry, studied by the renormalization groups, lie at the heart of modern physics theories of matters and complex systems. However, surveying these properties wit…
Theoretical foundations of studying criticality in the brain
Yang Tian, Zeren Tan, Hedong Hou +6
Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information processing capacities in the brain. While co…
Simplex path integral and simplex renormalization group for high-order interactions
Aohua Cheng, Yunhui Xu, Pei Sun +1
Modern theories of phase transitions and scale-invariance are rooted in path integral formulation and renormalization group (RG). Despite the applicability of these approaches on s…
Laplacian dynamics of convergent and divergent swarm behaviors
Yang Tian, Yunhui Xu, Pei Sun
Swarming phenomena are ubiquitous in various physical, biological, and social systems, where simple local interactions between individual units lead to complex global patterns. A c…
Thermodynamics of percolation in interacting systems
Yizhou Xu, Pei Sun, Yang Tian
Interacting systems can be studied as the networks where nodes are system units and edges denote correlated interactions. Although percolation on network is a unified way to model…
Koopman neural operator as a mesh-free solver of non-linear partial differential equations
Wei Xiong, Xiaomeng Huang, Ziyang Zhang +3
The lacking of analytic solutions of diverse partial differential equations (PDEs) gives birth to a series of computational techniques for numerical solutions. Although numerous la…
KoopmanLab: machine learning for solving complex physics equations
Wei Xiong, Muyuan Ma, Xiaomeng Huang +3
Numerous physics theories are rooted in partial differential equations (PDEs). However, the increasingly intricate physics equations, especially those that lack analytic solutions…
Statistical Physics of Deep Neural Networks: Initialization toward Optimal Channels
Kangyu Weng, Aohua Cheng, Ziyang Zhang +2
In deep learning, neural networks serve as noisy channels between input data and its representation. This perspective naturally relates deep learning with the pursuit of constructi…
Bridging the information and dynamics attributes of neural activities
Yang Tian, Guoqi Li, Pei Sun
The brain works as a dynamic system to process information. Various challenges remain in understanding the connection between information and dynamics attributes in the brain. The…
Network comparison via encoding, decoding, and causality
Yang Tian, Hedong Hou, Guangzheng Xu +2
Quantifying the relations (e.g., similarity) between complex networks paves the way for studying the latent information shared across networks. However, fundamental relation metric…
A unified theory of information transfer and causal relation
Yang Tian, Hedong Hou, Yaoyuan Wang +2
Information transfer between coupled stochastic dynamics, measured by transfer entropy and information flow, is suggested as a physical process underlying the causal relation of sy…
Self-organized critical dynamics of RNA virus evolution
Xiaofei Ge, Kaichao You, Zeren Tan +3
RNA virus (e.g., SARS-CoV-2) evolves in a complex manner. Studying RNA virus evolution is vital for understanding molecular evolution and medicine development. Scientists lack, how…
Thermodynamics of Encoding and Encoders
Yang Tian, Pei Sun
Non-isolated systems have diverse coupling relations with the external environment. These relations generate complex thermodynamics and information transmission between the system…
Information Evolution in Complex Networks
Yang Tian, Guoqi Li, Pei Sun
Many biological phenomena or social events critically depend on how information evolves in complex networks. However, a general theory to characterize information evolution is yet…
Fourier-domain transfer entropy spectrum
Yang Tian, Yaoyuan Wang, Ziyang Zhang +1
We propose the Fourier-domain transfer entropy spectrum, a novel generalization of transfer entropy, as a model-free metric of causality. For arbitrary systems, this approach syste…