Results 11 to 20 of about 59 (59)

Measure‐valued processes for energy markets

open access: yesMathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero   +3 more
wiley   +1 more source

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

open access: yesCommunications on Pure and Applied Mathematics, Volume 79, Issue 8, Page 1973-2102, August 2026.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

Stability of a Fully Discrete Local Discontinuous Galerkin Method for the Generalized Benjamin–Ono Equation

open access: yesNumerical Methods for Partial Differential Equations, Volume 42, Issue 4, July 2026.
ABSTRACT The main purpose of this paper is to design a fully discrete local discontinuous Galerkin (LDG) scheme for the generalized Benjamin–Ono equation. First, we prove the L2$$ {L}^2 $$‐stability for the proposed semi‐discrete LDG scheme and obtained a suboptimal order of convergence for power nonlinear flux.
Mukul Dwivedi, Tanmay Sarkar
wiley   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

open access: yesAdvanced Science, Volume 13, Issue 33, 15 June 2026.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich   +2 more
wiley   +1 more source

Information Flow in Geophysical Systems

open access: yesJournal of Advances in Modeling Earth Systems, Volume 18, Issue 6, June 2026.
Abstract We present a new framework for analyzing the evolution of information in geophysical systems. Understanding how information, and its counterpart, uncertainty, propagates is central to predictability studies and has significant implications for applications such as forecast uncertainty quantification and risk management. It also offers valuable
P. J. van Leeuwen
wiley   +1 more source

Impact of Uncertain Parameters on Navier–Stokes Equations With Heat Transfer via Polynomial Chaos Expansion

open access: yesInternational Journal for Numerical Methods in Fluids, Volume 98, Issue 5, Page 557-577, May 2026.
This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element‐Volume method.
N. Nouaime   +3 more
wiley   +1 more source

Chitosan–Alginate Polyelectrolyte Systems: From Classical Release Models to the D‐PARMO Framework

open access: yesMacromolecular Materials and Engineering, Volume 311, Issue 5, May 2026.
Classical empirical models fail to predict the dynamic in vivo behavior of chitosan‐alginate nanocarriers. Bridging this translational gap, the novel D‐PARMO framework replaces purely descriptive curve‐fitting with a mechanistically informed operational model.
Parastoo Rekab, Akeem Adeyemi Oladipo
wiley   +1 more source

Robust Inverse Material Design With Physical Guarantees Using the Voigt‐Reuss Net

open access: yesInternational Journal for Numerical Methods in Engineering, Volume 127, Issue 7, 15 April 2026.
ABSTRACT We apply the Voigt‐Reuss net, a spectrally normalized neural surrogate introduced in [38], for forward and inverse mechanical homogenization with a key guarantee that all predicted effective stiffness tensors satisfy Voigt‐Reuss bounds in the Löwner sense during training, inference, and gradient‐driven optimization.
Sanath Keshav, Felix Fritzen
wiley   +1 more source

Red Blood Cell Membrane Mechanics Using Discrete Exterior Calculus (DEC) and Optimization

open access: yesInternational Journal for Numerical Methods in Biomedical Engineering, Volume 42, Issue 4, April 2026.
We present a novel DEC approach for calculating RBC shapes applicable to other cell types and membrane problems. We derive an energy minimization equation that can be solved semi‐implicitly, and a Lie derivative method to control node spacing. This novel work should aid computational modeling in many biological situations.
Keith C. Afas, Daniel Goldman
wiley   +1 more source

Accelerating Conjugate Gradient Solvers for Homogenization Problems With Unitary Neural Operators

open access: yesInternational Journal for Numerical Methods in Engineering, Volume 127, Issue 5, 15 March 2026.
ABSTRACT Rapid and reliable solvers for parametric partial differential equations (PDEs) are needed in many scientific and engineering disciplines. For example, there is a growing demand for composites and architected materials with heterogeneous microstructures.
Julius Herb, Felix Fritzen
wiley   +1 more source

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