activity
20142026
most citedHigher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes

248 citations · 845 across the 36 of their papers we have counts for

collaborators

36 papers

nlin.AO2026

Symmetry-based selection rules for higher-order interactions in coupled oscillators

Iván Léon, Riccardo Muolo, Yuanzhao Zhang +1

Pairwise interactions among general nonlinear oscillators can be reduced, via phase reduction, to a Kuramoto-type phase coupling . For higher-order interactions,…

cs.LG2026

Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization

Xiaoyuan Cheng, Wenxuan Yuan, Zhancun Mu +5

Model-based reinforcement learning (RL) can be effectively supported at scale through the use of world models. However, in practice, scaling such approaches remains fundamentally l…

cond-mat.stat-mech2026

Anomalous scaling in redirection networks

Harrison Hartle, P. L. Krapivsky, S. Redner +1

In networks that grow by isotropic redirection (IR), a new node selects an initial target node uniformly at random and attaches to a randomly chosen neighbor of the target. The eme…

eess.SY2025

From Inference to Control: Structure-Guided Control of Hypergraph Dynamics

Robin Delabays, Yuanzhao Zhang, Can Chen +2

Controllability determines whether a system's state can be guided toward any desired configuration, making it a fundamental prerequisite for designing effective control strategies.…

nlin.AO2025

Tempological Control of Network Dynamics

Yuanzhao Zhang, Sean P. Cornelius

Feedback control is an effective strategy for stabilizing a desired state and has been widely adopted in maintaining the stability of systems such as flying birds and power grids.…

cs.LG2025

Information Shapes Koopman Representation

Xiaoyuan Cheng, Wenxuan Yuan, Yiming Yang +4

The Koopman operator provides a powerful framework for modeling dynamical systems and has attracted growing interest from the machine learning community. However, its infinite-dime…

nlin.AO2025

Mixed higher-order coupling stabilizes new states

Per Sebastian Skardal, Federico Battiston, Maxime Lucas +3

Understanding how higher-order interactions affect collective behavior is a central problem in nonlinear dynamics and complex systems. Most works have focused on a single higher-or…

nlin.AO2025★ 16 cited

Collective dynamics on higher-order networks

Federico Battiston, Christian Bick, Maxime Lucas +3

Higher-order interactions that nonlinearly couple more than two nodes are important in many networked systems, and their effects on collective dynamics are increasingly being studi…

q-bio.CB2025

Ignition criteria for trigger waves in cell signaling

Brandon H. Schlomann, William S. DeWitt, Yuanzhao Zhang +1

To rapidly coordinate collective behaviors in tissues, cells communicate with one another through traveling fronts of signaling activity called trigger waves. The stimulus threshol…

cs.LG2025★ 3 cited

Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing

Declan A. Norton, Yuanzhao Zhang, Michelle Girvan

Machine learning techniques offer an effective approach to modeling dynamical systems solely from observed data. However, without explicit structural priors -- built-in assumptions…

math-ph2025

The size of the sync basin resolved

Pablo Groisman, Cecilia De Vita, Julián Fernández Bonder +1

Sparsely coupled Kuramoto oscillators offer a fertile playground for exploring high-dimensional basins of attraction due to their simple yet multistable dynamics. For identical…

cs.LG2025

Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning

Yuanzhao Zhang, William Gilpin

Recent time-series foundation models exhibit strong abilities to predict physical systems. These abilities include zero-shot forecasting, in which a model forecasts future states o…

cond-mat.dis-nn2025★ 1 cited

Signature of glassy dynamics in dynamic modes decompositions

Zachary G. Nicolaou, Hangjun Cho, Yuanzhao Zhang +2

Glasses are traditionally characterized by their rugged landscape of disordered low-energy states and their slow relaxation towards thermodynamic equilibrium. Far from equilibrium,…

cs.LG2024★ 1 cited

Zero-shot forecasting of chaotic systems

Yuanzhao Zhang, William Gilpin

Time-series forecasting is a challenging problem that traditionally requires specialized models custom-trained for the specific task at hand. Recently, inspired by the success of l…

cs.LG2024★ 6 cited

How more data can hurt: Instability and regularization in next-generation reservoir computing

Yuanzhao Zhang, Edmilson Roque dos Santos, Huixin Zhang +1

It has been found recently that more data can, counter-intuitively, hurt the performance of deep neural networks. Here, we show that a more extreme version of the phenomenon occurs…

physics.soc-ph2024★ 31 cited

Hypergraph reconstruction from dynamics

Robin Delabays, Giulia De Pasquale, Florian Dörfler +1

A plethora of methods have been developed in the past two decades to infer the underlying network structure of an interconnected system from its collective dynamics. However, metho…

nlin.AO2023★ 37 cited

Deeper but smaller: Higher-order interactions increase linear stability but shrink basins

Yuanzhao Zhang, Per Sebastian Skardal, Federico Battiston +2

A key challenge of nonlinear dynamics and network science is to understand how higher-order interactions influence collective dynamics. Although many studies have approached this q…

nlin.AO2022

A minimal model of peripheral clocks reveals differential circadian re-entrainment in aging

Yitong Huang, Yuanzhao Zhang, Rosemary Braun

The mammalian circadian system comprises a network of cell-autonomous oscillators, spanning from the central clock in the brain to peripheral clocks in other organs. These clocks a…

cs.LG2022★ 29 cited

Catch-22s of reservoir computing

Yuanzhao Zhang, Sean P. Cornelius

Reservoir Computing (RC) is a simple and efficient model-free framework for forecasting the behavior of nonlinear dynamical systems from data. Here, we show that there exist common…

nlin.AO2022★ 248 cited

Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes

Yuanzhao Zhang, Maxime Lucas, Federico Battiston

Higher-order networks have emerged as a powerful framework to model complex systems and their collective behavior. Going beyond pairwise interactions, they encode structured relati…

cond-mat.dis-nn2021

Comment on "Failure of the simultaneous block diagonalization technique applied to complete and cluster synchronization of random networks"

Yuanzhao Zhang

In their recent preprint [arXiv:2108.07893v1], S. Panahi, N. Amaya, I. Klickstein, G. Novello, and F. Sorrentino tested the simultaneous block diagonalization (SBD) technique on sy…

nlin.AO2021★ 6 cited

Forget Partitions: Cluster Synchronization in Directed Networks Generate Hierarchies

Fiona M. Brady, Yuanzhao Zhang, Adilson E. Motter

We present a scalable approach for simplifying the stability analysis of cluster synchronization patterns on directed networks. When a network has directional couplings, decomposit…

nlin.AO2021

Basins with tentacles

Yuanzhao Zhang, Steven H. Strogatz

To explore basin geometry in high-dimensional dynamical systems, we consider a ring of identical Kuramoto oscillators. Many attractors coexist in this system; each is a twisted per…

nlin.AO2021★ 54 cited

Random heterogeneity outperforms design in network synchronization

Yuanzhao Zhang, Jorge L. Ocampo-Espindola, István Z. Kiss +1

A widely held assumption on network dynamics is that similar components are more likely to exhibit similar behavior than dissimilar ones and that generic differences among them are…