Tootfinder

This https://arxiv.org/abs/2409.11330 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Parameter dependent rough SDEs with applications to rough PDEs
Rough stochastic differential equations (rough SDEs), recently introduced by Friz, Hocquet and Lê in arXiv:2106.10340, have emerged as a versatile tool to study "doubly" SDEs under partial conditioning (with motivation from pathwise filtering and control, volatility modelling in finance and mean-field stochastic dynamics with common noise ...). While the full dynamics may be highly non-Markovian, the conditional dynamics often are. In natural (and even linear) situations, the resulting stochas…

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
Iosif Lytras, Sotirios Sabanis, Ying Zhang
https://arxiv.org/abs/2506.04878

kTULA: A Langevin sampling algorithm with improved KL bounds under super-linear log-gradients
Motivated by applications in deep learning, where the global Lipschitz continuity condition is often not satisfied, we examine the problem of sampling from distributions with super-linearly growing log-gradients. We propose a novel tamed Langevin dynamics-based algorithm, called kTULA, to solve the aforementioned sampling problem, and provide a theoretical guarantee for its performance. More precisely, we establish a non-asymptotic convergence bound in Kullback-Leibler (KL) divergence with the …

Dynamically derived morphology from the recurrence patterns of close binary stars using Kepler data
Anisha R. V. Kashyap, D. Pawar, R. Misra, G. Ambika, Sandip V George
https://arxiv.org/abs/2506.04111

Dynamically derived morphology from the recurrence patterns of close binary stars using Kepler data
In this work, we propose a novel method to classify close binary stars, derived from the dynamical structure inherent in their light curves. We apply the technique to light curves of binaries from the revised Kepler Eclipsing binary catalog, selecting close binaries which have the standard morphology parameter, $c$, $\gt 0.5$ corresponding to semi-detached, over-contact and ellipsoidal systems. Using the method of time delay embedding, we recreate the non-linear dynamics underlying the data and…

This https://arxiv.org/abs/2410.09346 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance
We develop a systems approach based on an energy-landscape concept to differentiate interactions involving redox activities and conformational changes of proteins and nucleic acids interactions in multi-layered protein-DNA regulatory networks under light disturbance. Our approach is a data-driven modeling workflow using a physics-informed machine learning algorithm to train a non-linear mathematical model for interpreting gene expression dynamics and to lead discovery for protein regulators usi…

Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares
Aurora Poggi, Giuseppe Alessio D'Inverno, Hjalmar Brismar, Ozan \"Oktem, Matthieu Barreau, Kateryna Morozovska
https://arxiv.org/abs/2505.20327

Data-driven multi-agent modelling of calcium interactions in cell culture: PINN vs Regularized Least-squares
Data-driven discovery of dynamics in biological systems allows for better observation and characterization of processes, such as calcium signaling in cell culture. Recent advancements in techniques allow the exploration of previously unattainable insights of dynamical systems, such as the Sparse Identification of Non-Linear Dynamics (SINDy), overcoming the limitations of more classic methodologies. The latter requires some prior knowledge of an effective library of candidate terms, which is not…

Modeling extreme events and intermittency in turbulent diffusion with a mean gradient
Mustafa A Mohamad, Di Qi
https://arxiv.org/abs/2505.21688 https://

Modeling extreme events and intermittency in turbulent diffusion with a mean gradient
We study the statistical properties of passive tracer transport in turbulent flows with a mean gradient, emphasizing tracer intermittency and extreme events. An analytically tractable model is developed, coupling zonal and shear velocity components with both linear and nonlinear stochastic dynamics. Formulating the model in Fourier space, a simple explicit solution for the tracer invariant statistics is derived. Through this model we identify the resonance condition responsible for non-Gaussian…

Mechanisms of information communication and market price movements. The case of SP 500 market
Inga Ivanova, Grzegorz Rzadkowski
https://arxiv.org/abs/2505.09625

Mechanisms of information communication and market price movements. The case of SP 500 market
In this paper we analyze how market prices change in response to information processing among the market participants and how non-linear information dynamics drive market price movement. We analyze historical data of the SP 500 market for the period 1950 -2025 using the logistic Continuous Wavelet Transformation method. This approach allows us to identify various patterns in market dynamics. These patterns are conceptualized using a new theory of reflexive communication of information in a mark…