Latest Articles for Computational Methods

A look at total variation distance and its significance in probability distributions.

New methods improve predictions in complex systems, especially in geoscience.

Explore how Quantum Monte Carlo can transform economic modeling and analysis.

New techniques improve simulations of the Schwinger model using quantum computing.

A new approach to improve molecular property predictions in AI using task addition.

Researchers develop a method for efficient calculations in quantum spin chains at high temperatures.

New methods improve model performance with fewer data points.

New methods for efficiently analyzing network changes in weighted graphs.

A new method for improving GNNs in molecular analysis.

A new method enhances active learning for better machine learning performance.

New method enhances simulation accuracy of the solar atmosphere and fluid interactions.

Exploring energy corrections and vacuum polarization in muonic atomic systems.

A fresh perspective on analyzing material responses using susceptibility in quantum chemistry.

Explore how Conway's cosmological theorem transforms number sequences through audioactive derivation.

Researchers use machine learning to enhance predictions of infinite nuclear matter efficiently.

Recent developments in quantum algorithms and hardware show great potential for efficiency.

A look into sextic and Morse potentials in quantum mechanics.

GenCFD uses AI to improve fluid flow computation, enhancing speed and accuracy.

Qudits are changing the landscape of quantum computing by enabling superior information processing.

New techniques streamline the evaluation of complex Feynman integrals using supercomputers.

Study explores how strain affects the magnetic properties of 1T-VSe.

This article explores edge-bicolored graphs and their significance in mathematics and physics.

Introducing grid point approximation for handling large datasets effectively.

Examining the merging of specialized machine learning models and their collaboration.

A program reduces complex tensor integrals for particle interaction calculations.

A simplified look at how LQFT helps us study tiny particles.

A fresh look at the quantum Hopfield model reveals new insights.

Discovering new phases in Kondo lattices through spins and simulations.

KANs offer flexibility and efficiency in machine learning compared to MLPs.

Learn how the LOD method simplifies complex multiscale challenges.

Exploring new methods to analyze complex materials using Density Functional Theory.

A new method streamlines material calculations for better and faster results.

Researchers tackle complexities in stellarator design using magnetic axis exploration.

Researchers enhance quantum simulation using TRG and HOTRG methods.

Learn how arithmetic sampling improves text generation in language models.

A fresh approach improves dynamic mode decomposition for noisy fluid flow data.

Scientists use eigenpair-splitting to solve quantum challenges efficiently.

Scientists study Rydberg atoms to unlock secrets of quantum phases and transitions.

This article explores how quantum annealing aids in understanding nuclear structures.

Researchers utilize deep learning to predict properties of photonic crystals efficiently.