To help expedite the use of quantum processing units, ORNL researchers developed an advanced software framework.
A team of ORNL researchers has used the DCA++ application, a popular code for predicting the performance of quantum materials, to verify two performance-enhancing strategies.
Kokkos is a programming model and library for writing performance-portable code in C++.
A new method was developed for the discovery of fundamental descriptors for gas adsorption through deep learning neural network (DNN) approach. This approach has great potential to identify structural parameters for gas adsorption.
A team from Oak Ridge and Los Alamos National Laboratories led a demonstration of quantum key distribution systems that harness the power of quantum mechanics to authenticate data and encrypt messages with a secret key to securely transmit locked in
Researchers at ORNL have developed new solvers for implicit time discretization of a simplified Boltzmann-Poisson system.
The upcoming Square Kilometre Array (SKA) will be the largest radio telescope in the world. An international team recently used Summit, the worlds most powerful supercomputer, to simulate the massive amounts of data the SKA will produce.
A learning-based approximation strategy has been developed to accelerate parameter studies for non-classical models of diffusion.
ORNL researchers have developed a quantum chemistry simulation benchmark to evaluate the performance of quantum devices and guide the development of applications for future quantum computers.
Developed a deep-learning approach to automatically create libraries of structural and electronic properties of atomic defects in 2D materials.