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We consider the Fast Fourier Transform (FFT) based numerical method for thin film magnetization problems [Vestg{\aa}rden and Johansen, SuST, 25 (2012) 104001], compare it with the finite element methods, and evaluate its accuracy. Proposed…

Computational Physics · Physics 2018-05-09 Leonid Prigozhin , Vladimir Sokolovsky

In many mechanical, electrical, and general physical systems evolving over time or space, spectral analysis methods as Fast Fourier Transform (FFT), Short Term Fourier Transform (STFT), Power Spectrum Density (PSD) plays a very important…

Signal Processing · Electrical Eng. & Systems 2023-06-21 Andreas Tuor , Nico Canzani , Tobias Rüggeberg , Stefan Gorenflo , Gerd Simons , Bruno Bättig , Daniel Iseli

Fast-Fourier Transform (FFT) methods have been widely used in solid mechanics to address complex homogenization problems. However, current FFT-based methods face challenges that limit their applicability to intricate material models or…

Materials Science · Physics 2024-10-15 Mohit Pundir , David S. Kammer

We present a general framework for the efficient simulation of realistic fermionic systems with modern machine learning inspired representations of quantum many-body states, towards a universal tool for ab initio electronic structure. These…

Strongly Correlated Electrons · Physics 2023-05-16 Yannic Rath , George H. Booth

In this paper, we use multithreaded fast Fourier transforms provided in three highly optimized packages, FFTW-2.1.5, FFTW-3.3.7, and Intel MKL FFT, to present a novel model-based parallel computing technique as a very effective and portable…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-08-17 Semyon Khokhriakov , Ravi Reddy , Alexey Lastovetsky

Recent research in deep learning (DL) has investigated the use of the Fast Fourier Transform (FFT) to accelerate the computations involved in Convolutional Neural Networks (CNNs) by replacing spatial convolution with element-wise…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Eduardo Reis , Thangarajah Akilan , Mohammed Khalid

Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…

Machine Learning · Computer Science 2025-10-03 Hung Le , Sherif Abbas , Minh Hoang Nguyen , Van Dai Do , Huu Hiep Nguyen , Dung Nguyen

A new "on the fly" method to perform Born-Oppenheimer ab initio molecular dynamics (AIMD) is presented. Inspired by Ehrenfest dynamics in time-dependent density functional theory, the electronic orbitals are evolved by a Schroedinger-like…

This review article was first published in 2008 as chapter 11 in the book "Fast Fourier Transforms," edited by C. S. Burrus, for the Connexions project at Rice University, which is sadly no longer online. It gives a high-level overview of…

Numerical Analysis · Mathematics 2026-03-02 Steven G. Johnson , Matteo Frigo

The use of reconfigurable computing, and FPGAs in particular, to accelerate computational kernels has the potential to be of great benefit to scientific codes and the HPC community in general. However, whilst recent advanced in FPGA tooling…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-06 Nick Brown , David Dolman

Performing full-resolution atomistic simulations of nucleic acid folding has remained a challenge for biomolecular modeling. Understanding how nucleic acids fold and how they transition between different folded structures as they unfold and…

Biomolecules · Quantitative Biology 2022-05-18 Chi H. Mak

Photoacoustic (PA) imaging has been widely applied in both preclinical and clinical applications. With a significantly increasing number of data acquisition channels, fast and high-quality image reconstruction for real-time PA imaging is an…

Medical Physics · Physics 2024-08-20 Zijian Gao , Yuting Shen , Daohuai Jiang , Fengyu Liu , Feng Gao , Fei Gao

The fractional Fourier transform (FrFT), a fundamental operation in physics that corresponds to a rotation of phase space by any angle, is also an indispensable tool employed in digital signal processing for noise reduction. Processing of…

There has been abundant research on the development of Approximate Circuits (ACs) for ASICs. However, previous studies have illustrated that ASIC-based ACs offer asymmetrical gains in FPGA-based accelerators. Therefore, an AC that might be…

Hardware Architecture · Computer Science 2020-12-29 Bharath Srinivas Prabakaran , Vojtech Mrazek , Zdenek Vasicek , Lukas Sekanina , Muhammad Shafique

This paper proposes several explicit and implicit multistep frequency response optimized integrators considering first or second order derivative. A prediction-based method aiming at accelerating a novel power system transient simulation…

Systems and Control · Electrical Eng. & Systems 2021-02-16 Sheng Lei , Alexander Flueck

Machine-learned interatomic potentials are revolutionising atomistic materials simulations by providing accurate and scalable predictions within the scope covered by the training data. However, generation of an accurate and robust training…

Materials Science · Physics 2025-07-30 Mariia Radova , Wojciech G. Stark , Connor S. Allen , Reinhard J. Maurer , Albert P. Bartók

The Number Theoretic Transform (NTT) is an indispensable tool for computing efficient polynomial multiplications in post-quantum lattice-based cryptography. It has strong resemblance with the Fast Fourier Transform (FFT), which is the most…

Cryptography and Security · Computer Science 2025-04-16 Rishabh Shrivastava , Chaitanya Prasad Ratnala , Durga Manasa Puli , Utsav Banerjee

This paper presents a complete video fusion system with hardware acceleration and investigates the energy trade-offs between computing in the CPU or the FPGA device. The video fusion application is based on the Dual-Tree Complex Wavelet…

Hardware Architecture · Computer Science 2016-02-09 Jose Nunez-Yanez , Tom Sun

Quantum chemistry simulations that accurately predict the properties of materials are among the most highly anticipated applications of quantum computing. It is widely believed that simulations running on quantum computers will allow for…

Deep learning (DL) has emerged as a rapidly developing advanced technology, enabling the performance of complex tasks involving image recognition, natural language processing, and autonomous decision-making with high levels of accuracy.…

Hardware Architecture · Computer Science 2026-03-11 Soumita Chatterjee , Sudip Ghosh , Tamal Ghosh , Hafizur Rahaman
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