In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

Erik Lentz and Christian Boutan will research quantum information science-enabled discoveries in high energy physics with these awards.

Developing a new scheme to more efficiently solve quantum chemistry problems.

PNNL was recognized for its significant contributions to projects at the Secretary’s Honor Awards Ceremony in Washington, D.C.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

A potential quantum advantage for fluid dynamics simulations from molecular to atmospheric scales with a new formula for success.

The Testing Risks of AI for National Security Taskforce will address critical safety and security concerns related to artificial intelligence.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

The search for dark matter includes expertise in radio frequency signal detection, quantum sensing, and high-energy physics at PNNL.

Protecting critical systems such as the electrical grid from cyber-based risks to the supply chain is the focus of a new PNNL conference.

Operators of critical infrastructure are trained to respond to cyberattacks using scale models of water treatment plants, freight rail yards, and more.

Ryan Eddy, director of homeland security programs at PNNL, was recognized as one of 50 trailblazers by Homeland Security Today.

ARQUIN computational pipeline provides a holistic framework for simulating a system with distributed quantum computing ingredients.

At PNNL, researchers are taking a wider look at the system through the supply chain’s lifecycle and subcomponents to determine the big-picture risks.

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.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.

Bylaska and team will aim to make computational design of functional materials more targeted, impactful, and user friendly through this award.