Latest Articles for Computational Science

Krylov methods evolve to simplify complex quantum system analysis.

A new emulator improves accuracy and efficiency in studying nuclear reactions.

New methods enhance efficiency in solving particle transport equations.

ProteinGPT simplifies protein study through an interactive chat system.

A hybrid filter enhances numerical methods for better accuracy in discontinuous regions.

This article discusses using tensor decomposition to improve PINNs for solving complex equations.

New techniques improve efficiency in modeling complex systems.

Exploring communication methods within multi-GPU supercomputers for enhanced performance.

An exploration of the intricate training processes in two-layer narrow neural networks.

A hybrid approach improves wave equation computations in various fields.

A look into eigenvalue problems and methods for their resolution.

G2C3 improves simulations of plasma microturbulence in fusion devices using neural networks.

Explore the structure and applications of 2-quasi best match graphs in biology.

Combining DEER data with AlphaFold2 enhances protein shape predictions.

Combining Parareal and neural networks offers a quicker way to solve ODEs.

Examining how averaged dynamics and randomness improve learning models.

Discover the importance and flexibility of intrinsically disordered proteins in biology.

Researchers use lattice QCD to uncover nucleon properties and their fundamental interactions.

A new method to simplify simulations in agent-based models by combining similar agents.

Neural networks enhance solutions for complex partial differential equations.

Examining turbulence with a focus on Ekman-Navier-Stokes equations and numerical simulations.

A novel approach using Galerkin-Boltzmann and neural networks to analyze fluid behavior.

New quantum method improves molecular energy calculations significantly.

Techniques like manifold learning help scientists interpret large datasets effectively.

Advanced Python code facilitates the study of transversity PDFs in particle physics.

A study on ionisation in hydrogen using classical molecular dynamics simulations.

Combining domain decomposition and operator inference for faster simulations.

TomoPicker simplifies finding particles in Cryo-ET images, reducing manual work significantly.

Research examines complex quantum states in lattice gauge theories using the Schwinger model.

Exploring the fusion of machine learning and molecular mechanics for better simulations.

Researchers use machine learning to predict information spread in quantum systems.

Introducing JuliaQCD, software for simulating quark and gluon interactions in QCD.

Streamlining digital twins through reduced order models and high-performance computing.

This article discusses the vibrational states of methanol and their significance.

Learn how specialized basis sets enhance molecular property predictions.

Explores the impact of PQAE and QAE on quantum data processing.

BaNDyT combines simulations and networks to advance protein research.

New methods combine neural networks and finite element techniques to improve fluid flow simulations.

Combining traditional methods with AI to enhance PDE solutions.

A new method combines HPC, quantum computing, and AI for chemistry.