Tootfinder

Analysis of divergent dynamics of exactly factorized electron-nuclear wavefunctions
Julian Stetzler (Department of Chemistry,Biochemistry, University of South Carolina, Columbia, USA), Sophya Garashchuk (Department of Chemistry,Biochemistry, University of South Carolina, Columbia, USA), Vitaly A. Rassolov (Department of Chemistry,Biochemistry, University of South Carolina, Columbia, USA)

Analysis of divergent dynamics of exactly factorized electron-nuclear wavefunctions
The Exact Factorization (XF) of molecular wavefunctions can be viewed as an 'electronic wavepacket' framework for quantum dynamics. It is an appealing alternative to the conventional non-adiabatic dynamics, unfolding in the space of coupled electronic eigenstates. However, implementation of the non-linear XF equations for general systems presents a formidable challenge: the XF counterparts to the non-adiabatic coupling involve division by the nuclear probability density, which leads to severe n…

Bayesian Nonparametric Dynamical Clustering of Time Series
Adri\'an P\'erez-Herrero, Paulo F\'elix, Jes\'us Presedo, Carl Henrik Ek
https://arxiv.org/abs/2510.06919

Bayesian Nonparametric Dynamical Clustering of Time Series
We present a method that models the evolution of an unbounded number of time series clusters by switching among an unknown number of regimes with linear dynamics. We develop a Bayesian non-parametric approach using a hierarchical Dirichlet process as a prior on the parameters of a Switching Linear Dynamical System and a Gaussian process prior to model the statistical variations in amplitude and temporal alignment within each cluster. By modeling the evolution of time series patterns, the method…

On the decoherence of Majorana zero modes mediated by gapless fermions
Sauri Bhattacharyya, Marco Grilli, Bernard van Heck
https://arxiv.org/abs/2510.07893 https://

On the decoherence of Majorana zero modes mediated by gapless fermions
We study the decoherence of a collection of Majorana zero modes weakly coupled to a gapless reservoir of non-interacting fermions. Using the Born-Markov approximation, we derive a Lindblad master equation for the dissipative dynamics of the Majorana zero modes. Due to the long-range coupling between Majorana zero modes mediated by the gapless reservoir, the Lindblad jump operators are non-local linear combinations of the Majorana operators. We show that, as a consequence, the dissipative dynami…

NLDSI-BWE: Non Linear Dynamical Systems-Inspired Multi Resolution Discriminators for Speech Bandwidth Extension
Tarikul Islam Tamiti, Anomadarshi Barua
https://arxiv.org/abs/2510.01109

NLDSI-BWE: Non Linear Dynamical Systems-Inspired Multi Resolution Discriminators for Speech Bandwidth Extension
In this paper, we design two nonlinear dynamical systems-inspired discriminators -- the Multi-Scale Recurrence Discriminator (MSRD) and the Multi-Resolution Lyapunov Discriminator (MRLD) -- to \textit{explicitly} model the inherent deterministic chaos of speech. MSRD is designed based on Recurrence representations to capture self-similarity dynamics. MRLD is designed based on Lyapunov exponents to capture nonlinear fluctuations and sensitivity to initial conditions. Through extensive design opt…

Very High Frequency Interpolation for Direct Torque Control
Rafael Kourdis, Maciej St\k{e}pie\'n, J\'er\^ome Manhes, Nicolas Mansard, Steve Tonneau, Philippe Sou\`eres, Thomas Flayols
https://arxiv.org/abs/2509.24175

Very High Frequency Interpolation for Direct Torque Control
Torque control enables agile and robust robot motion, but deployment is often hindered by instability and hardware limits. Here, we present a novel solution to execute whole-body linear feedback at up to 40 kHz on open-source hardware. We use this to interpolate non-linear schemes during real-world execution, such as inverse dynamics and learned torque policies. Our results show that by stabilizing torque controllers, high-frequency linear feedback could be an effective route towards unlocking …

Stability of surfactant-laden double-layered viscoelastic fluids flowing over an inclined plane
Md. Mouzakkir Hossain, Mohamin B. M. Khan, Youchuang Chao
https://arxiv.org/abs/2510.04250

Stability of surfactant-laden double-layered viscoelastic fluids flowing over an inclined plane
The linear dynamics and instability mechanisms of double-layered weakly viscoelastic fluid flowing over an inclined plane are analyzed in the presence of insoluble surfactant at both the free surface and interface. The constitutive equation of the non-Newtonian flow field follows the rheological property of Walters' $B^{''}$ model. The Orr-Sommerfeld-type boundary value problem is derived using the classical normal-mode approach and numerically solved within the framework of the Chebyshev spect…

Vector Resonant Relaxation and Statistical Closure Theory. II. One-loop Closure
Sofia Flores, Jean-Baptiste Fouvry
https://arxiv.org/abs/2509.22164 https://

Vector Resonant Relaxation and Statistical Closure Theory. II. One-loop Closure
We use stellar dynamics as a testbed for statistical closure theory. We focus on the process of "Vector Resonant Relaxation," a long-range, non-linear, and correlated relaxation mechanism that drives the reorientation of stellar orbital planes around a supermassive black hole. This process provides a natural setting to evaluate the predictive power of generic statistical closure schemes for dynamical correlation functions, in the fully non-linear and non-perturbative regime. We develop a numeri…

Machine learning approach to single-shot multiparameter estimation for the non-linear Schr\"odinger equation
Louis Rossignol, Tangui Aladjidi, Myrann Baker-Rasooli, Quentin Glorieux
https://arxiv.org/abs/2509.18479

Machine learning approach to single-shot multiparameter estimation for the non-linear Schrödinger equation
The nonlinear Schrödinger equation (NLSE) is a fundamental model for wave dynamics in nonlinear media ranging from optical fibers to Bose-Einstein condensates. Accurately estimating its parameters, which are often strongly correlated, from a single measurement remains a significant challenge. We address this problem by treating parameter estimation as an inverse problem and training a neural network to invert the NLSE mapping. We combine a fast numerical solver with a machine learning approach…

A Single-Equation Approach to Classifying Neuronal Operational Modes
Lindsey Knowles, Cesar Ceballos, Rodrigo Pena
https://arxiv.org/abs/2510.01386 https://

A Single-Equation Approach to Classifying Neuronal Operational Modes
The neural coding is yet to be discovered. The neuronal operational modes that arise with fixed inputs but with varying degrees of stimulation help to elucidate their coding properties. In neurons receiving in vivo stimulation, we show that two operation modes can be described with simplified models: the coincidence detection mode and the integration mode. Our derivations include a simplified polynomial model with non-linear coefficients betam that captures the subthreshold dynamics of these mo…

Hierarchical Analysis and Control of Epidemic Spreading over Networks using Dissipativity and Mesh Stability
Shirantha Welikala, Hai Lin, Panos J. Antsaklis
https://arxiv.org/abs/2509.24665

Hierarchical Analysis and Control of Epidemic Spreading over Networks using Dissipativity and Mesh Stability
Analyzing and controlling spreading processes are challenging problems due to the involved non-linear node (subsystem) dynamics, unknown disturbances, complex interconnections, and the large-scale and multi-level nature of the problems. The dissipativity concept provides a practical framework for addressing such concerns, thanks to the energy-based representation it offers for subsystems and the compositional properties it provides for the analysis and control of interconnected (networked) syst…

A Penalized Distributed Lag Non-Linear Lee-Carter Framework for Regional Weekly Mortality Forecasting
Jens Robben, Karim Barigou
https://arxiv.org/abs/2509.24087 https://…

A Penalized Distributed Lag Non-Linear Lee-Carter Framework for Regional Weekly Mortality Forecasting
Accurate forecasts of weekly mortality are essential for public health and the insurance industry. We develop a forecasting framework that extends the Lee-Carter model with age- and region-specific seasonal effects and penalized distributed lag non-linear components that capture the delayed and non-linear effects of heat, cold, and influenza on mortality. The model accommodates overdispersed mortality rates via a negative binomial distribution. We model the temporal dynamics of the latent facto…

A general action for a particle in 2 1 anti-de Sitter space
Carles Batlle, Joaquim Gomis
https://arxiv.org/abs/2509.18959 https://arxiv.org/pdf/2509.18959

Analytical solution of a free-fermion chain with time-dependent ramps
Viktor Eisler, Riccarda Bonsignori, Stefano Scopa
https://arxiv.org/abs/2510.03112 https://

Analytical solution of a free-fermion chain with time-dependent ramps
We provide an exact analytical solution of the single-particle Schrödinger equation for a chain of non-interacting fermions subject to a time-dependent linear potential, with its slope varied as an arbitrary function of time. The resulting dynamics exhibit self-similar behavior, with a structure reminiscent of the domain wall melting problem, albeit characterized by a nontrivial time-dependent length scale and phase. Building on this solution, we derive hydrodynamic predictions for the evoluti…

A local limit theorem for a random walk in an intermittent dynamical environment
Juho Lepp\"anen
https://arxiv.org/abs/2509.15158 https://arxiv.org/pd…

A local limit theorem for a random walk in an intermittent dynamical environment
We study an extended dynamical system on the non-negative real line with piecewise linear non-uniformly expanding local dynamics. With a uniformly distributed initial state, the distribution of the successive states coincides with that of a random walk in an inhomogeneous environment. Under suitable conditions on the environment, we establish a central limit theorem and a (non-Gaussian) local limit theorem for the walk. Our approach builds on the work of Leskelä and Stenlund (Stochastic Proces…

On the Viability of Weak Energy Condition Violation in Parity-Violating Electrodynamics
Tao Huang
https://arxiv.org/abs/2509.18188 https://arxiv.org/pdf/25…

Superresolving Non-linear PDE Dynamics with Reduced-Order Autodifferentiable Ensemble Kalman Filtering For Turbulence Modeling and Flow Regulation
Mrigank Dhingra, Omer San
https://arxiv.org/abs/2509.12149

Superresolving Non-linear PDE Dynamics with Reduced-Order Autodifferentiable Ensemble Kalman Filtering For Turbulence Modeling and Flow Regulation
Accurately reconstructing and forecasting high-resolution (HR) states from computationally cheap low-resolution (LR) observations is central to estimation-and-control of spatio-temporal PDE systems. We develop a unified superresolution pipeline based on the reduced-order autodifferentiable Ensemble Kalman filter (ROAD-EnKF). The method learns a low-dimensional latent dynamics model and a nonlinear decoder from latent variables to HR fields; the learned pair is embedded in an EnKF, enabling simu…

High harmonic generation from a Bose-Einstein condensate
Philipp Stammer
https://arxiv.org/abs/2509.19022 https://arxiv.org/pdf/2509.19022

Anomalous statistics in the Langevin equation with fluctuating diffusivity: from Brownian yet non-Gaussian diffusion to anomalous diffusion and ergodicity breaking
Takuma Akimoto, Jae-Hyung Jeon, Ralf Metzler, Tomoshige Miyaguchi, Takashi Uneyama, Eiji Yamamoto
https://arxiv.org/abs/2509.12571

Anomalous statistics in the Langevin equation with fluctuating diffusivity: from Brownian yet non-Gaussian diffusion to anomalous diffusion and ergodicity breaking
Diffusive motion is a fundamental transport mechanism in physical and biological systems, governing dynamics across a wide range of scales -- from molecular transport to animal foraging. In many complex systems, however, diffusion deviates from classical Brownian behaviour, exhibiting striking phenomena such as Brownian yet non-Gaussian diffusion (BYNGD) and anomalous diffusion. BYNGD describes a frequently observed statistical feature characterised by the coexistence of linear mean-square disp…