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We investigate the ability of simple diagnostics based on Lagrangian descriptor (LD) computations of initially nearby orbits to detect chaos in conservative dynamical systems with phase space dimensionality higher than two. In particular,…

Earth and Planetary Astrophysics · Physics 2023-08-09 Sebastian Zimper , Arnold Ngapasare , Malcolm Hillebrand , Matthaios Katsanikas , Stephen R. Wiggins , Charalampos Skokos

The leader-following consensus of multiple linear time invariant (LTI) systems under switching topology is considered. The leader-following consensus problem consists of designing for each agent a distributed protocol to make all agents…

Optimization and Control · Mathematics 2012-11-08 Wei Ni , Xiaoli Wang , Chun Xiong

Amorphous ice phases are key constituents of water's complex structural landscape. This study investigates the polyamorphic nature of water, focusing on the complexities within low-density amorphous ice (LDA), high-density amorphous ice…

Disordered Systems and Neural Networks · Physics 2023-12-25 Zoé Faure Beaulieu , Volker L. Deringer , Fausto Martelli

Characterizing the nonlocal nature of quantum states is a central challenge in the practical application of large-scale quantum computation and simulation. Quantum mutual information (QMI), a fundamental nonlocal measure, plays a key role…

Quantum Physics · Physics 2025-11-25 Hao Liao , Xuanqin Huang , Ping Wang

Meaningful topological invariants for mixed quantum states are challenging to identify as there is no unique way to define them, and most choices do not directly relate to physical observables. Here, we propose a simple pragmatic approach…

Quantum Gases · Physics 2017-12-13 Charles-Edouard Bardyn

We present a self-consistent theory of Anderson localization that yields a simple algorithm to obtain \emph{typical local density of states} as an order parameter, thereby reproducing the essential features of a phase-diagram of…

Disordered Systems and Neural Networks · Physics 2009-11-07 V. Dobrosavljevic , A. A. Pastor , Branislav K. Nikolic

In this paper, we present a novel framework to synthesize robust strategies for discrete-time nonlinear systems with random disturbances that are unknown, against temporal logic specifications. The proposed framework is data-driven and…

Systems and Control · Electrical Eng. & Systems 2025-04-29 Ibon Gracia , Luca Laurenti , Manuel Mazo , Alessandro Abate , Morteza Lahijanian

This work provides a data-driven framework that combines coprime factorization with a lifting linearization technique to model the discrepancy between a nonlinear system and its nominal linear approximation using a linear time-invariant…

Systems and Control · Electrical Eng. & Systems 2025-02-25 Sourav Sinha , Mazen Farhood

In social sciences, studies are often based on questionnaires asking participants to express ordered responses several times over a study period. We present a model-based clustering algorithm for such longitudinal ordinal data. Assuming…

Methodology · Statistics 2024-01-29 Francesco Amato , Julien Jacques , Isabelle Prim-Allaz

Classical and quantum Markov networks -- including Gibbs states of commuting local Hamiltonians -- are characterized by the vanishing of conditional mutual information (CMI) between spatially separated subsystems. Adding local dissipation…

Quantum Physics · Physics 2025-02-20 Yifan Zhang , Sarang Gopalakrishnan

We show how to generalize the concepts of identifying and classifying symmetry protected topological phases in 1D to the case of an arbitrary mixed state. The pure state concepts are reviewed using a concrete spin-1 model. For the mixed…

Strongly Correlated Electrons · Physics 2014-09-15 Evert P. L. van Nieuwenburg , Sebastian D. Huber

Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This paper proposed a longitudinal higher-order diagnostic classification modeling approach for measuring…

Methodology · Statistics 2018-09-19 Peida Zhan , Hong Jiao , Dandan Liao

We provide a mutual information lower bound that can be used to analyze the effect of training in models with unknown parameters. For large-scale systems, we show that this bound can be calculated using the difference between two…

Information Theory · Computer Science 2021-08-21 Xiangbo Meng , Kang Gao , Bertrand M. Hochwald

Quantum information spreading and scrambling in many-body systems attract interests these days. Tripartite mutual information (TMI) based on operator-based entanglement entropy (EE) is an efficient tool for measuring them. In this paper, we…

Quantum Physics · Physics 2022-09-23 Takahiro Orito , Yoshihito Kuno , Ikuo Ichinose

We present an extension of Landau's theory of phase transitions by incorporating the topology of the order parameter. When the order parameter comprises several components arising from multiplicity in the same irreducible representation of…

Superconductivity · Physics 2025-06-24 Canon Sun , Joseph Maciejko

Recent years have seen the concept of global symmetry extended to non-invertible (or categorical) symmetries, for which composition of symmetry generators is not necessarily invertible. Such non-invertible symmetries lead to a…

Strongly Correlated Electrons · Physics 2024-05-17 Lakshya Bhardwaj , Lea E. Bottini , Sakura Schafer-Nameki , Apoorv Tiwari

In this paper we establish a general first-order statistical framework for the detection of a common signal impinging on spatially distributed receivers. We consider three types of channel models: 1) the propagation channel is completely…

Signal Processing · Electrical Eng. & Systems 2023-02-15 Todd McWhorter , Louis Scharf , Margaret Cheney

In many real-world decision problems there is partially observed, hidden or latent information that remains fixed throughout an interaction. Such decision problems can be modeled as Latent Markov Decision Processes (LMDPs), where a latent…

Machine Learning · Computer Science 2024-06-27 Jeongyeol Kwon , Shie Mannor , Constantine Caramanis , Yonathan Efroni

Causal analysis based on non-uniform embedding schemes is an important way to detect the underlying interactions between dynamic systems. However, there are still some obstacles to estimate high-dimensional conditional mutual information…

Methodology · Statistics 2020-02-19 Ziyu Jia , Youfang Lin , Zehui Jiao , Yan Ma , Jing Wang

We present a novel M-theoretic approach of constructing and classifying anyonic topological phases of matter, by establishing a correspondence between (2+1)d topological field theories and non-hyperbolic 3-manifolds. In this construction,…

High Energy Physics - Theory · Physics 2020-12-30 Gil Young Cho , Dongmin Gang , Hee-Cheol Kim
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