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.

New apps help researchers with statistical analyses of data.

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

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.

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

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

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

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

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.

Research.com ranked PNNL joint appointee George Karniadakis as one of the top mathematicians in the world.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

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

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.

Tiffany Kaspar’s work has advanced the discovery and understanding of oxide materials, helping develop electronics, quantum computing, and energy production. She strives to communicate her science to the public.

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

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