A new approach broadens the reach of quantum computers to previously challenging systems.

A multi-institutional team of wind energy experts led by PNNL assessed the scientific grand challenges for offshore wind and provided recommendations for closing gaps in models.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.

PNNL wind energy experts have published the Distributed Wind Market Report: 2022 Edition, supplying key findings that can help businesses, communities, and homeowners make informed decisions.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

Quantum simulators help navigate noise on GPU-based HPC systems.

PNNL researchers utilized the Peeters-Devreese-Soldatov formulation to improve the accuracy of calculations for quantum chemistry.

A team of researchers developed a simulation approach to identify how atomic structures can affect the phonon transport of energy and information in quantum systems near absolute zero temperatures.

Using the connected moments mathematical technique decreases the time and computational power needed for performing quantum computing simulations.