Latest Articles for Computational Methods

A lightweight algorithm enhances simulation accuracy for radiation damage in silicon detectors.

Research on qutrits reveals improved performance for quantum operations, particularly the Toffoli gate.

Research on quantum spin liquids and complex magnetic states using the spin-Kitaev-Heisenberg model.

New techniques enhance our ability to study superlattices and their electronic properties.

New slip-wall models improve accuracy and efficiency in simulating turbulent flows.

Exploring the connection between topological defects and biological systems in active nematics.

This article highlights key methods improving turbomachinery design through computer simulations.

A deep dive into magnetism through the Landau-Lifshitz equation analysis.

A novel approach for efficient simulation of quasi-2D Coulomb systems is introduced.

Research reveals complex electron behaviors in MATBG using advanced computational techniques.

A new method improves efficiency in quantum circuit design.

A new method improves nuclear structure predictions by accounting for three-body interactions.

Analyzing numerical methods in materials science for phase-field problems.

A look at how patch dynamics improves multiscale modelling techniques.

Discover how random features simplify complex calculations in machine learning.

Combining AI and HPC enhances simulations for scientific research.

A new method for estimating edge density in random graphs while ensuring privacy.

This study examines the relationship between Hopf-Galois structures and field extensions.

A look at using dynamical stabilization in QCD simulations to improve accuracy.

Learn about IPMs and how MLMC enhances their performance across various applications.

A new method efficiently handles shock formations in Burgers' equation.

Exploring the role of triangulations in understanding Calabi-Yau manifolds.

Combining quantum and classical methods to tackle fluid motion equations.

Innovative method integrates electron density for improved molecular property predictions.

Research on accurate binding energy methods enhances understanding of atomic nuclei.

A fresh approach reveals how tiny particles interact under various conditions.

Exploring the role of DMC in studying 2D materials.

Examining properties and applications of Lorentzian polynomials in mathematics.

FAdam optimizes machine learning training with enhanced techniques for better results.

Researchers leverage machine learning to predict important Hubbard parameters for materials.

An overview of DMFT and its role in studying strongly interacting electron systems.

A new method for classification using hypergraphs improves data categorization accuracy.

A look into how Ising machines enhance optimization techniques.

This article discusses the advantages of the Chebyshev Spectral Neural Network for solving differential equations.

A novel approach for analyzing triplet data in particle physics experiments.

This article investigates integral behavior related to the Riemann zeta function.

Exploring the potential of quantum computing in fluid dynamics simulations.

Analyzing convergence of SGD with momentum through time window-based methods.

Learn how Bayesian online learning adapts models with incoming data.

This article reviews methods to enhance least-squares problem accuracy using different precision levels.