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Feedback processes by active galactic nuclei in the centres of galaxy clusters appear to prevent large-scale cooling flows and impede star formation. However, the detailed heating mechanism remains uncertain. One promising heating scenario…

Cosmology and Nongalactic Astrophysics · Physics 2020-11-30 Kristian Ehlert , Rainer Weinberger , Christoph Pfrommer , Rüdiger Pakmor , Volker Springel

Dynamic simulation of elastic bodies is a longstanding task in engineering and computer graphics. In graphics, numerical integrators like implicit Euler and BDF2 are preferred due to their stability at large time steps, but they tend to…

Graphics · Computer Science 2026-02-10 Kevin You , Juntian Zheng , Minchen Li

We propose an efficient, accurate and reliable simulation scheme for the stochastic-alpha-beta-rho (SABR) model. The two challenges of the SABR simulation lie in sampling (i) integrated variance conditional on terminal volatility and (ii)…

Computational Finance · Quantitative Finance 2025-10-06 Jaehyuk Choi , Lilian Hu , Yue Kuen Kwok

We introduce a new Adaptive Integration Approach (AIA) to be used in a wide range of molecular simulations. Given a simulation problem and a step size, the method automatically chooses the optimal scheme out of an available family of…

Numerical Analysis · Computer Science 2016-11-23 Mario Fernández-Pendás , Elena Akhmatskaya , J. M. Sanz-Serna

The current-induced magnetisation dynamics in a ferromagnet at elevated temperatures can be described by the Landau--Lifshitz--Bloch (LLB) equation with spin-torque terms. In this paper, we focus on the regime above the Curie temperature.…

Numerical Analysis · Mathematics 2025-06-30 Agus L. Soenjaya

This paper proposes a computationally efficient simulation strategy for cold thermal energy storage (TES) systems based on phase change material (PCM). Taking as a starting point the recent design of a TES system based on PCM, designed to…

Systems and Control · Electrical Eng. & Systems 2024-02-07 G. Bejarano , M. Vargas , M. G. Ortega , F. Castaño , J. E. Normey-Rico

Iterative cycles of theoretical prediction and experimental validation are the cornerstone of the modern scientific method. However, the proverbial "closing of the loop" in experiment-theory cycles in practice are usually ad hoc, often…

In this paper, we propose an optimized field/circuit coupling approach for the simulation of magnetothermal transients in superconducting magnets. The approach improves the convergence of the iterative coupling scheme between a…

The initialization process of a novel power system transient simulation scheme for stability studies is put forward, by further developing a "time-domain harmonic power-flow algorithm". The initialization process is formulated as an…

Systems and Control · Electrical Eng. & Systems 2020-09-01 Sheng Lei , Alexander Flueck

We assess the capability of recently developed foundational atomistic models (FAMs) to simulate iron alloys under the extreme pressures and temperatures of Earth's core. Static equations of state of hexagonal close-packed (hcp) and…

Geophysics · Physics 2026-05-14 Tianqi Wan , Liangrui Wei , Zepeng Wu , Renata M. Wentzcovitch , Yang Sun

A variety of physical heating mechanisms are combined with radiative cooling to explore, via one dimensional hydrodynamic simulations, the expected thermal properties of the intracluster medium (ICM) in the context of the cooling flow…

Astrophysics · Physics 2009-11-13 Charlie Conroy , Jeremiah P. Ostriker

In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and…

We present a room-temperature Extreme High Vacuum (XHV) system engineered to support the long-duration operation of a trapped-ion quantum processor. Background-gas collisions impose limitations on trapped-ion performance and scalability by…

Electrical machines employing superconductors are attractive solutions in a variety of application domains. Numerical models are powerful and necessary tools to optimize their design and predict their performance. The electromagnetic…

Superconductivity · Physics 2018-07-04 Roberto Brambilla , Francesco Grilli , Luciano Martini , Marco Bocchi , Giuliano Angeli

This paper proposes a nonlinear magnetics model for Permanent Magnet Synchronous Machines (PMSMs) that accurately captures the effects of magnetic saturation in the machine iron and variations in rotor temperature on the permanent magnet…

Systems and Control · Electrical Eng. & Systems 2025-02-05 Kishan Srinivasan , Heath Hofmann , Jing Sun

We propose a simple scheme to construct composition-dependent interatomic potentials for multicomponent systems that when superposed onto the potentials for the pure elements can reproduce not only the heat of mixing of the solid solution…

Materials Science · Physics 2012-01-31 B. Sadigh , P. Erhart , A. Stukowski , A. Caro

Antiferromagnets (AFMs) are strong candidates for the future spintronic and memory applications largely because of their inherently fast dynamics and lack of stray fields, with Mn2Au being one of the most promising. For the numerical…

Materials Science · Physics 2022-06-20 Joel Hirst , Unai Atxitia , Sergiu Ruta , Jerome Jackson , Leon Petit , Thomas Ostler

A model predictive control (MPC) method for enhancing post-fault transient stability of a grid-forming (GFM) inverter based resources (IBRs) is developed in this paper. This proposed controller is activated as soon as the converter enters…

Systems and Control · Electrical Eng. & Systems 2023-11-09 Ali Arjomandi-Nezhad , Yifei Guo , Bikash C. Pal , Damiano Varagnolo

When modeling superconducting devices based on REBCO tapes andworking near or above the critical current value (i.e. I> Ic), the power-law model is not always accurate. In our previous works, we proposed the overcritical current model,…

We propose a general algorithmic framework for constrained matrix and tensor factorization, which is widely used in signal processing and machine learning. The new framework is a hybrid between alternating optimization (AO) and the…

Machine Learning · Statistics 2016-08-24 Kejun Huang , Nicholas D. Sidiropoulos , Athanasios P. Liavas
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