Latest Articles for Computational Science

Machine learning techniques enhance understanding of quantum systems and phase transitions.

A novel method enhances GNN performance with noisy data.

New method improves efficiency in studying protein structures and interactions.

Exploring the complexities of anomalous diffusion through advanced mathematical modeling.

New techniques improve eigenvalue calculations for complex matrices efficiently.

Investigating methods for applying boundary conditions in the Schrödinger equation simulations.

Quantum computing techniques improve calculations of molecular energies.

This article presents a novel approach for solving nonconservative hyperbolic systems accurately.

Learn how PINNs integrate physics with neural networks to solve complex equations.

A look at how DGGs improve understanding of dynamic interactions in systems.

New approaches in drug design prioritize molecule synthesizability for better outcomes.

Investigating critical points in QCD under extreme conditions using high-precision numerical methods.

Combining matrix product states and Chebyshev polynomials for efficient function approximation.

New methods simplify the simulation of open quantum systems in quantum physics.

Exploring quantum phase estimation using a particle in a magnetic field.

New methods offer efficient solutions for operator exponentials in various fields.

Researchers improve neural PDE models using pretrained lower-dimensional equations for better performance.

Learn how lossy compression and AMR improve data handling in simulations.

New methods enhance understanding of protein charge interactions and behavior.

Techniques for improving the accuracy of numerical solutions in science and engineering.

Introducing methods to improve energy stability and positivity in gradient flows.

A new boundary condition enhances simulations of magnetic reconnection in space environments.

New HOBO solver addresses higher-order optimization in quantum computing.

Introducing a new method for predicting DNA-binding sites in proteins using deep learning.

A new method speeds up model order reduction, enhancing efficiency in complex simulations.

This study enhances TDDFT calculations using multiple GPUs for larger molecular systems.

COLOSS simplifies nuclear scattering research through advanced computational techniques.

A new model improves understanding of electrochemical interfaces through machine learning.

A new hybrid model combines two approaches for better disease spread insights.

Explore key concepts of Grassmann, flag, and Stiefel manifolds and their applications.

CGRL tackles challenges in GNNs, improving classification despite popularity bias and noise.

Research introduces a self-interaction potential to enhance Density Functional Theory predictions.

Learn how deep backward dynamic programming addresses nonlinear partial differential equations.

An overview of the complexities in modeling neutron star merger events.

Introducing PSNE, a method to improve network embeddings efficiently and effectively.

Machine learning speeds up potential energy surface calculations for molecules like ethanol.

Research shows enhanced performance in language models using adaptive test-time computation.

A look at high-order numerical methods for fluid dynamics.

A new method improves predictions of protein functions using advanced techniques.

AI is streamlining the process of creating quantum circuits through better synthesis methods.