Tootfinder

One- and two-dimensional solitons under the action of the inverted cubic-quintic nonlinearity
Liangwei Zeng, Boris A. Malomed, Dumitru Mihalache, Xing Zhu
https://arxiv.org/abs/2509.17441

One- and two-dimensional solitons under the action of the inverted cubic-quintic nonlinearity
The usual cubic-quintic (CQ) nonlinearity is proved to sustain one- and two-dimensional (1D and 2D) broad (flat-top) solitons. In this work, we demonstrate that 1D and 2D soliton families can be supported, in the semi-infinite bandgap (SIBG), by the interplay of a lattice potential and the nonlinearity including self-defocusing cubic and self-focusing quintic terms, with the sign combination inverted with respect to the usual CQ nonlinearity. The families include fundamental and dipole solitons…

Fractional Dynamics with Non-Local Scaling
Vasily E. Tarasov
https://arxiv.org/abs/2509.15228 https://arxiv.org/pdf/2509.15228

Fractional Dynamics with Non-Local Scaling
Nonlinear fractional dynamics with scale invariance in continuous and discrete time approaches are described. We use non-integer-order integro-differential operators that can be interpreted as generalizations of scaling (dilation) differential operator for the case of non-locality. Nonlinear integro-differential equations with Hadamard type operators of non-integer orders with respect to time and periodic sequence of kicks are considered. Exact solutions of these equations are derived without u…

Phase-Pole-Free Images and Smooth Coil Sensitivity Maps by Regularized Nonlinear Inversion
Moritz Blumenthal, Martin Uecker
https://arxiv.org/abs/2508.04685 https://

Phase-Pole-Free Images and Smooth Coil Sensitivity Maps by Regularized Nonlinear Inversion
Purpose: Phase singularities are a common problem in image reconstruction with auto-calibrated sensitivities due to an inherent ambiguity of the estimation problem. The purpose of this work is to develop a method for detecting and correcting phase poles in non-linear inverse (NLINV) reconstruction of MR images and coil sensitivity maps. Methods: Phase poles are detected in individual coil sensitivity maps by computing the curl in each pixel. A weighted average of the curl in each coil is comput…

Image Inpainting based on Visual-Neural-Inspired Specific Object-of-Interest Imaging Technology
Yonghao Wu, Jun Li
https://arxiv.org/abs/2508.12808 https://

Image Inpainting based on Visual-Neural-Inspired Specific Object-of-Interest Imaging Technology
This study addresses the bottlenecks of conventional holistic image inpainting methods -- susceptibility to informational redundancy and low computational efficiency under occlusions and complex backgrounds -- by proposing a novel three-stage framework: "Specific Object-of-Interest Imaging -- Coarse Structural imaging -- Fine Textural Refinement". First, the Network with Object-Imaging Module (NOIM) precisely delineates target structures from degraded inputs while actively suppressing backgroun…

Periodic orbits underlying spatiotemporal chaos in the Lugiato-Lefever model
Andrey Gelash, Savyaraj Deshmukh, Andrey Shusharin, Tobias M. Schneider, Tobias J. Kippenberg
https://arxiv.org/abs/2509.10283

Periodic orbits underlying spatiotemporal chaos in the Lugiato-Lefever model
We obtain and investigate theoretically a broad family of stable and unstable time-periodic orbits-oscillating Turing rolls (OTR)-in the Lugiato-Lefever model of optical cavities. Using the dynamical systems tools developed in fluid dynamics, we access the OTR solution branches in parameter space and elucidate their bifurcation structure. By tracking these exact invariant solutions deeply into the chaotic region of the modulation instability, we connect the main dynamical regimes of the Lugiato…

Deep Neural Networks can eliminate Spiral-wave Turbulence in Cardiac Tissue Models
Vasanth Kumar Babu, Rahul Pandit
https://arxiv.org/abs/2509.09806 https://

Deep Neural Networks can eliminate Spiral-wave Turbulence in Cardiac Tissue Models
Ventricular arrhythmias, like ventricular tachycardia (VT) and ventricular fibrillation (VF), precipitate sudden cardiac death (SCD), which is the leading cause of mortality in the industrialised world. Thus, the elimination of VT and VF is a problem of paramount importance, which is studied experimentally, theoretically, and numerically. Numerical studies use partial-differential-equation models, for cardiac tissue, which admit solutions with spiral- or broken-spiral-wave solutions that are th…

Inverse problems for dynamic patterns in coupled oscillator networks: When larger networks are simpler
Oleh E. Omel'chenko
https://arxiv.org/abs/2507.21942 https://

Inverse problems for dynamic patterns in coupled oscillator networks: When larger networks are simpler
Networks of coupled phase oscillators are one of the most studied dynamical systems with numerous applications in physics, chemistry, biology, and engineering. Their typical behaviour looks like a partially synchronized dynamic pattern, where some oscillators behave almost identically, while others behave differently relative to each other. In the case of large networks, the properties of these patterns can often be analysed using a kind of mean-field approach (called thermodynamic limit or con…

Replaced article(s) found for nlin.PS. https://arxiv.org/list/nlin.PS/new
[1/1]:
- One- and two-dimensional solitons under the action of the inverted cubic-quintic nonlinearity
Liangwei Zeng, Boris A. Malomed, Dumitru Mihalache, Xing Zhu

Multifractal features of multimodal cardiac signals: Nonlinear dynamics of exercise recovery
A. Maluckov, D. Stojanovic, M. Miletic, Lj. Hadzievski, J. Petrovic
https://arxiv.org/abs/2509.23317

Multifractal features of multimodal cardiac signals: Nonlinear dynamics of exercise recovery
We investigate the recovery dynamics of healthy cardiac activity after physical exertion using multimodal biosignals recorded with a polycardiograph. Multifractal features derived from the singularity spectrum capture the scale-invariant properties of cardiovascular regulation. Five supervised classification algorithms - Logistic Regression (LogReg), Suport Vector Machine with RBF kernel (SVM-RBF), k-Nearest Neighbors (kNN), Decision Tree (DT), and Random Forest (RF) - were evaluated to disting…