In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.
The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.
Germany Harris, Dewayne Maye, Sarah Olocha, Shaniya Pettway, and Rayonna Redmon became the first interns of the Minority Serving Institution Partnership Program Partnership for Radiation Studies Consortium at PNNL.
A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.
Advancing the science of radiation, especially among students at minority-serving institutions, is the goal of one of the Department of Energy’s newest consortia.
PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.