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Classically, solution theories for state-dependent delay equations are developed in spaces of continuous or continuously differentiable functions. The former can be technically challenging to apply in as much as suitably Lipschitz…

Classical Analysis and ODEs · Mathematics 2025-02-04 Johanna Frohberg , Marcus Waurick

We extend a contraction mapping argument for ordinary state-dependent delay differential equations to evolutionary partial differential equations in the sense of R. Picard, that is, to equations of the form $\bigl(\partial_{t}…

Analysis of PDEs · Mathematics 2025-11-20 Bernhard Aigner , Marcus Waurick

This paper concerns autonomous boundary value problems for 1D semilinear hyperbolic PDEs. For time-periodic classical solutions, which satisfy a certain non-resonance condition, we show the following: If the PDEs are continuous with respect…

Analysis of PDEs · Mathematics 2025-12-10 Irina Kmit , Lutz Recke

We consider state-dependent delay equations (SDDE) obtained by adding delays to a planar ordinary differential equation with a limit cycle. These situations appear in models of several physical processes, where small delay effects are…

Dynamical Systems · Mathematics 2021-08-13 Jiaqi Yang , Joan Gimeno , Rafael de la Llave

Periodic orbits and associated bifurcations of singularly perturbed state-dependent delay differential equations (DDEs) are studied when the profiles of the periodic orbits contain jump discontinuities in the singular limit. A definition of…

Dynamical Systems · Mathematics 2017-06-01 A. R. Humphries , D. A. Bernucci , R. Calleja , N. Homayounfar , M. Snarski

Partial differential equations (PDEs) govern physical phenomena across the full range of scientific scales, yet their computational solution remains one of the defining challenges of modern science. This critical review examines two mature…

Machine Learning · Computer Science 2026-03-10 Mohammad Nooraiepour , Jakub Wiktor Both , Teeratorn Kadeethum , Saeid Sadeghnejad

Using probabilistic methods, we establish a-priori estimates for two classes of quasilinear parabolic systems of partial differential equations (PDEs). We treat in particular the case of a nonlinearity which has quadratic growth in the…

Probability · Mathematics 2023-04-05 Joe Jackson

In this paper we consider a class of differential equations with state-dependent delays. We show first and second-order differentiability of the solution with respect to parameters in a pointwise sense and also using the C-norm on the…

Dynamical Systems · Mathematics 2012-01-04 Ferenc Hartung

We investigate the structure of the set of $T$-periodic solutions to periodically perturbed coupled delay differential equations on differentiable manifolds. By using fixed point index and degree-theoretic methods we prove the existence of…

Classical Analysis and ODEs · Mathematics 2014-11-19 Luca Bisconti , Marco Spadini

In this paper, we consider the dynamics of solutions to complex-valued evolutionary partial differential equations (PDEs) and show existence of heteroclinic orbits from nontrivial equilibria to zero via computer-assisted proofs. We also…

Dynamical Systems · Mathematics 2022-03-02 Jonathan Jaquette , Jean-Philippe Lessard , Akitoshi Takayasu

We construct stable periodic solutions for a simple form nonlinear delay differential equation (DDE) with a periodic coefficient. The equation involves one underlying nonlinearity with the multiplicative periodic coefficient. The well-known…

Dynamical Systems · Mathematics 2024-02-14 Anatoli Ivanov , Sergiy Shelyag

Let $r>0, n\in\mathbb{N}, {\bf k}\in\mathbb{N}$. Consider the delay differential equation $$ x'(t)=g(x(t-d_1(Lx_t)),\ldots,x(t-d_{{\bf k}}(Lx_t))) $$ for $g:(\mathbb{R}^n)^{{\bf k}}\supset V\to\mathbb{R}^n$ continuously differentiable, $L$…

Dynamical Systems · Mathematics 2021-09-16 Hans-Otto Walther

In this note we consider local invariant manifolds of functional differential equations representing differential equations with state-dependent delay. Starting with a local center-stable and a local center-unstable manifold of the…

Dynamical Systems · Mathematics 2015-03-31 Eugen Stumpf

We study parabolic stochastic partial differential equations (SPDEs), driven by two types of operators: one linear closed operator generating a $C_0-$semigroup and one linear bounded operator with Wick-type multiplication, all of them set…

Probability · Mathematics 2023-03-16 Tijana Levajkovic , Stevan Pilipovic , Dora Selesi , Milica Zigic

We show convergence of solutions to equilibria for quasilinear and fully nonlinear parabolic evolution equations in situations where the set of equilibria is non-discrete, but forms a finite-dimensional $C^1$-manifold which is normally…

Analysis of PDEs · Mathematics 2016-12-20 Jan Pruess , Gieri Simonett , Rico Zacher

Delays are ubiquitous in applied problems, but often do not arise as the simple constant discrete delays that analysts and numerical analysts like to treat. In this chapter we show how state-dependent delays arise naturally when modeling…

Dynamical Systems · Mathematics 2025-11-11 A. R. Humphries , A. S. Eremin , Z. Wang

For a wave equation with pure delay, we study an inhomogeneous initial-boundary value problem in a bounded 1D domain. Under smoothness assumptions, we prove unique existence of classical solutions for any given finite time horizon and give…

Analysis of PDEs · Mathematics 2014-01-23 Denys Khusainov , Michael Pokojovy , Elvin Azizbayov

In this paper, the convergence of the solutions for a discretized linear state-based static peridynamic system to the corresponding continuous solution is analytically proven. To obtain an implementable model, we further apply…

Numerical Analysis · Mathematics 2026-03-04 Lukas Pflug , Michael Stingl , Max Zetzmann

We study quasilinear degenerate parabolic-hyperbolic stochastic partial differential equations with general multiplicative noise within the framework of kinetic solutions. Our results are twofold: First, we establish new regularity results…

Probability · Mathematics 2017-09-19 Benjamin Gess , Martina Hofmanová

We utilize extreme-learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individually using a single model. Despite requiring only few data…

Machine Learning · Computer Science 2024-08-20 Hans Harder , Jean Rabault , Ricardo Vinuesa , Mikael Mortensen , Sebastian Peitz