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

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

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.

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.

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

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.

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

Williams will present on quantum technologies at The Economist’s Commercialising Quantum conference and the Quantum Tech Congress.

Fu brings expertise in identifying defects in quantum materials to the PNNL.

Dr. Joseph Williams explained the importance of quantum technologies in space at the University of Washington.

A hybrid computing approach for solving quantum chemical problems offers a practical bridge between classical and quantum computing.

Williams brings his deep understanding of the technology industry and PNNL’s quantum and national security expertise to this Technical Advisory Committee.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

PNNL’s Karol Kowalski leads one of the 29 projects selected to receive a total of $73 million in funding.

The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.

PNNL senior electrical engineer, Amy Qiao, tapped to serve IEEE Photonics Society Emerging Technologies Task Force.