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A novel finite element method for the approximation of Maxwell's equations over hybrid two-dimensional grids is studied. The choice of appropriate basis functions and numerical quadrature leads to diagonal mass matrices which allow for…

Numerical Analysis · Mathematics 2022-09-22 Herbert Egger , Bogdan Radu

OpenCAEPoro is a parallel numerical simulation software developed in C++ for simulating multiphase and multicomponent flows in porous media. The software utilizes a set of general-purpose compositional model equations, enabling it to handle…

Mathematical Software · Computer Science 2024-06-18 Shizhe Li , Chen-Song Zhang

This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from…

Numerical Analysis · Mathematics 2024-10-17 Kiefer Green , Harbir Antil

We present techniques for successfully performing numerical relativity simulations of binary black holes with fourth-order accuracy. Our simulations are based on a new coding framework which currently supports higher order finite…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Y. Zlochower , J. G. Baker , M. Campanelli , C. O. Lousto

Here we present a program aimed at free-energy calculations in molecular systems. It consists of a series of routines that can be interfaced with the most popular classical molecular dynamics (MD) codes through a simple patching procedure.…

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on applications in computational mechanics and design optimization. We leverage Mat\'ern-type…

Computational Engineering, Finance, and Science · Computer Science 2024-08-09 Tobias Duswald , Brendan Keith , Boyan Lazarov , Socratis Petrides , Barbara Wohlmuth

This study aims to develop a simulation framework for rotating detonation engines (RDEs) using multicomponentFluid solver in OpenFOAM v12 and to demonstrate reducing the computational costs by adaptive mesh refinement (AMR) and dynamic load…

Computational Physics · Physics 2025-08-25 Keunjae Kwak , Hyoungwoo Kim , Je Ir Ryu , Donh-Hyuk Shin

The advent of modern cloud services along with the huge volume of data produced on a daily basis, have set the demand for fast and efficient data processing. This demand is common among numerous application domains, such as deep learning,…

Machine Learning · Computer Science 2020-01-14 Athanasios Stratikopoulos , Juan Fumero , Zoran Sevarac , Christos Kotselidis

Recent research has shown that large language models (LLMs) can utilize low-precision floating point (FP) quantization to deliver high efficiency while maintaining original model accuracy. In particular, recent works have shown the…

Hardware Architecture · Computer Science 2025-06-05 Faraz Tahmasebi , Yian Wang , Benji Y. H. Huang , Hyoukjun Kwon

We present an implementation of arbitrary-precision numerical integration with rigorous error bounds in the Arb library. Rapid convergence is ensured for piecewise complex analytic integrals by use of the Petras algorithm, which combines…

Mathematical Software · Computer Science 2018-02-23 Fredrik Johansson

The supercomputing platforms available for high performance computing based research evolve at a great rate. However, this rapid development of novel technologies requires constant adaptations and optimizations of the existing codes for…

High Energy Physics - Lattice · Physics 2017-02-23 Marina Krstic Marinkovic , Luka Stanisic

Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be…

Quantitative Methods · Quantitative Biology 2023-11-29 Fabian Fröhlich , Daniel Weindl , Yannik Schälte , Dilan Pathirana , Łukasz Paszkowski , Glenn Terje Lines , Paul Stapor , Jan Hasenauer

Optimizing high-performance power electronic equipment, such as power converters, requires multiscale simulations that incorporate the physics of power semiconductor devices and the dynamics of other circuit components, especially in…

Systems and Control · Electrical Eng. & Systems 2025-01-20 Qingyuan Shi , Chijie Zhuang , Jiapeng Liu , Bo Lin , Xiyu Peng , Dan Wu , Zhicheng Liu , Rong Zeng

A novel algorithm that produces a quad layout based on imposed set of singularities is proposed. In this paper, we either use singularities that appear naturally, e.g., by minimizing Ginzburg-Landau energy, or use as an input user-defined…

Quantum computers promise to solve several categories of problems faster than classical computers ever could. Current research mostly focuses on qubits, i.e., systems where the unit of information can assume only two levels. However, the…

Quantum Physics · Physics 2023-08-25 Kevin Mato , Stefan Hillmich , Robert Wille

Quantum computing has traditionally centered around the discrete variable paradigm. A new direction is the inclusion of continuous variable modes and the consideration of a hybrid continuous-discrete approach to quantum computing. In this…

Achieving reliable performance on early fault-tolerant quantum hardware will depend on protocols that manage noise without incurring prohibitive overhead. We propose a novel framework that integrates quantum computation with the…

Quantum Physics · Physics 2026-03-10 IlKwon Sohn , Changyeol Lee , Wooyeong Song , Kwangil Bae , Wonhyuk Lee

This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive…

Computational Engineering, Finance, and Science · Computer Science 2019-04-30 Eric Neiva , Santiago Badia , Alberto F. Martín , Michele Chiumenti

We present a composable design scheme for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. Our object-oriented approach is based on constructing an expressive set of common data…

Large language models (LLMs) have revolutionized AI applications, yet their enormous computational demands severely limit deployment and real-time performance. Quantization methods can help reduce computational costs, however, attaining the…

Machine Learning · Computer Science 2025-09-03 Shaobo Ma , Chao Fang , Haikuo Shao , Zhongfeng Wang