Latest Articles for Computational Methods

Exploring quantum computing's role in solving power system dynamics efficiently.

A novel method enhances compressed sensing through mixed-integer optimization.

Utilizing the weak Galerkin method to achieve lower bounds for eigenvalues.

Researchers develop stabJGL for improved analysis of biological data networks.

A study on the Meshless Lattice Boltzmann Method in fluid simulations.

A look into real-time methods for tensor data analysis.

A new method improves understanding of fluid flow over surfaces.

Utilizing directed acyclic graphs to improve scattering amplitude calculations in particle physics.

BiSDL simplifies designing complex biological systems for researchers of all levels.

A new method for measuring discretization errors using Wishart distribution.

Learn how groups can effectively tackle complex problems through competitive search methods.

Introducing GradME: an innovative approach to tree reconstruction in phylogenetics.

An overview of skeins and their role in knot theory.

Improving the evaluation of Bayesian models through efficient calibration techniques.

This article presents an efficient method to minimize integral functionals in various fields.

A look into the significance and computation of non-linear optical properties.

A novel framework improves accuracy and efficiency in modeling binary-fluid interactions.

A new approach enhances thermal flow calculations in solar receivers.

New methods improve calculations of materials with strong electronic interactions.

A faster approach to particle simulations enhances data analysis for material structures.

New methods improve the simulation of dynamic electromagnetic materials and their applications.

Researchers are developing methods to streamline the HHL algorithm for quantum computers.

This study uses genetic algorithms to discover new Calabi-Yau manifolds from reflexive polytopes.

A novel approach refines predictions for materials like Mott insulators using DFPT.

This study explores the impact of memory effects in Kadanoff-Baym equations and HF-GKBA.

EDDPs enhance simulations and predictions in materials science.

A new framework enhances the training of graph convolutional networks through adaptive clustering.

New methods enhance simulation accuracy and efficiency using GPUs.

Researchers enhance quantum simulation using new methods for spin models.

SCALINN combines machine learning and physics for efficient predictions in complex systems.

A fresh approach improves accuracy in fluid dynamics modeling.

New methods enhance understanding of quantum systems through excited states and complex interactions.

Research enhances radical pair reactions using magnetic fields for improved outcomes.

This study examines the structural dynamics of triglycine using advanced techniques.

Examining loop structures in antiferromagnets and their temperature-dependent changes.

A method for estimating camera positions using few images.

A new method simplifies microstructure reconstruction using ellipsoidal shapes for improved material design.

Exploring iShiftML's impact on accurate NMR chemical shift predictions.

Exploring the significance of quantum phase transitions in the Potts chain model.

A deep look into the significance and applications of primitive normal pairs.