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.

A new approach validates quantum algorithms for low-energy nuclear physics applications

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

Clean hydrogen energy infrastructure is coming to the Pacific Northwest with a newly announced hydrogen hub, and PNNL experts are advising the work to come.

Newly developed ultra-low radiation cables reduce background noise for neutrino and dark matter detectors.

The papers were featured in the security and quantum sessions at the 2023 International Symposium on Computer Architecture.

DOE gives Hydrogen Program Special Award to PNNL's Hydrogen Safety Panel at department's 2023 Annual Merit Review and Peer Evaluation Meeting.

Researchers created the first open-source database of exotic materials eyed for use in quantum applications.

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

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.

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

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

A new testbed facility capable of testing superconducting qubit fidelity in a controlled environment free of stray background radiation will benefit quantum information sciences and the development of quantum computing.

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

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