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We propose Comprehensive Robust Dynamic Mode Decomposition (CR-DMD), a novel framework that robustifies the entire DMD process - from mode extraction to dimensional reduction - against mixed noise. Although standard DMD widely used for…

Signal Processing · Electrical Eng. & Systems 2026-01-19 Yuki Nakamura , Shingo Takemoto , Shunsuke Ono

The Refinement Calculus of Reactive Systems (RCRS) is a compositional formal framework for modeling and reasoning about reactive systems. RCRS provides a language which allows to describe atomic components as symbolic transition systems or…

Logic in Computer Science · Computer Science 2018-02-09 Viorel Preoteasa , Iulia Dragomir , Stavros Tripakis

Many multi-planet systems have been discovered in recent years. Some of them are in mean-motion resonances (MMR). Planet formation theory was successful in explaining the formation of 2:1, 3:1 and other low resonances as a result of…

Earth and Planetary Astrophysics · Physics 2014-11-20 Hanno Rein , John C. B. Papaloizou

The residual cutting (RC) method has been proposed as an outer-inner loop iteration for efficiently solving large and sparse linear systems of equations arising in solving numerically problems of elliptic partial differential equations.…

Numerical Analysis · Mathematics 2026-03-23 Toshihiko Abe

The Rayleigh conjecture about convergence up to the boundary of the series representing the scattered field in the exterior of an obstacle $D$ is widely used by engineers in applications. However this conjecture is false for some obstacles.…

Numerical Analysis · Mathematics 2007-05-23 A. G. Ramm , S. Gutman

We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note…

Artificial Intelligence · Computer Science 2011-06-27 A. T. Cemgil , B. Kappen

Pattern formation in systems with a conserved quantity is considered by studying the appropriate amplitude equations. The conservation law leads to a large-scale neutral mode that must be included in the asymptotic analysis for pattern…

Pattern Formation and Solitons · Physics 2009-10-31 P. C. Matthews , S. M. Cox

This paper studies the problem of risk-averse receding horizon motion planning for agents with uncertain dynamics, in the presence of stochastic, dynamic obstacles. We propose a model predictive control (MPC) scheme that formulates the…

Systems and Control · Electrical Eng. & Systems 2024-04-02 Anushri Dixit , Mohamadreza Ahmadi , Joel W. Burdick

Physical reservoir computing (RC) is a machine learning algorithm that employs the dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this paper, we introduce a quantum RC system that employs the dynamics…

Neural and Evolutionary Computing · Computer Science 2024-03-05 A. H. Abbas , Ivan S. Maksymov

Clustering is fundamental for gaining insights from complex networks, and spectral clustering (SC) is a popular approach. Conventional SC focuses on second-order structures (e.g., edges connecting two nodes) without direct consideration of…

Machine Learning · Computer Science 2018-12-27 Yan Ge , Haiping Lu , Pan Peng

Resonances are ubiquitous phenomena in nature, and physicists have developed many methods to explore resonant states. Of particular note is the complex momentum representation(CMR) method, which has been developed and widely used in the…

High Energy Physics - Phenomenology · Physics 2025-03-03 Wen-Wan He , Mao Song , Jian-You Guo , Xuan Luo , Gang Li

The kinetic Monte Carlo method is a standard approach for simulating physical systems whose dynamics are stochastic or that evolve in a probabilistic manner. Here we show how to calculate the system time for such simulations.

Computational Physics · Physics 2008-01-14 Clinton DeW. Van Siclen

Capture into mean motion resonance (MMR) is an important dynamical mechanism as it shapes the final architecture of a planetary system. We simulate systems of two or three planets undergoing migration with varied initial parameters such as…

Earth and Planetary Astrophysics · Physics 2023-01-11 Kaltrina Kajtazi , Antoine C. Petit , Anders Johansen

Medical time-series data are characterized by irregular sampling, high noise levels, missing values, and strong inter-feature dependencies. Recurrent neural networks (RNNs), particularly gated architectures such as Long Short-Term Memory…

Machine Learning · Computer Science 2026-03-03 Maitri Krishna Sai

Based on a simple but effective regularization-renormalization method (RRM), the running coupling constants (RCC) of fermions with masses in quantum electrodynamics (QED) and quantum chromodynamics (QCD) are calculated by renormalization…

High Energy Physics - Phenomenology · Physics 2007-05-23 Guang-jiong Ni , Guo-hong Yang , Rong-tang Fu , Haibin Wang

In acoustics, higher-order-in-time equations arise when taking into account a class of thermal relaxation laws in the modeling of sound wave propagation. In this work, we analyze initial boundary value problems for a family of such…

Analysis of PDEs · Mathematics 2023-02-16 Mostafa Meliani

Stepped wedge cluster randomized trials (SW-CRTs) with binary outcomes are increasingly used in prevention and implementation studies. Marginal models represent a flexible tool for analyzing SW-CRTs with population-averaged interpretations,…

Methodology · Statistics 2021-01-05 Fan Li , Hengshi Yu , Paul J. Rathouz , Elizabeth L. Turner , John S. Preisser

A general scheme, which includes constructions of coarse-grained (CG) models, weighted ensemble dynamics (WED) simulations and cluster analyses (CA) of stable states, is presented to detect dynamical and thermodynamical properties in…

Soft Condensed Matter · Physics 2008-12-04 Xin Zhou

We describe the public release of the Cluster Monte Carlo Code (CMC) a parallel, star-by-star $N$-body code for modeling dense star clusters. CMC treats collisional stellar dynamics using H\'enon's method, where the cumulative effect of…

\textbf{Background} The reach of \textit{ab initio} theory has greatly increased in recent decades. However, predicting the location of the drip lines remains challenging due to uncertainties in nuclear forces and difficulties in describing…

Nuclear Theory · Physics 2026-01-23 A. Sehovic , K. Fossez , H. Hergert