Quantum HPC co-location isn't necessary for most hybrid algorithms, a cross-lab study by AWS, NVIDIA, Lawrence Berkeley ...

Strongly correlated systems, such as transition-metal complexes, are central to catalysis and energy science, and remain challenging for classical algorithms because their ground states are not ...

Purdue University’s Artificial Intelligence Microcredentials offer quick and convenient online courses that cover the fundamentals of artificial intelligence and its applications. Every course ...

Dynamic complex matrix equation (DCME) is frequently encountered in the fields of mathematics and industry, and numerous recurrent neural network (RNN) models have been reported to effectively find ...

We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a ...

When trying to prove that two topological spaces are distinct, one often associates algebraic invariants such as groups, rings, and matrices to topological spaces. For manifolds, in dimension four, ...

We describe a novel iterative strategy for Kohn–Sham density functional theory calculations aimed at large systems (>1,000 electrons), applicable to metals and insulators alike. In lieu of explicit ...

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical ...

Abstract: This paper introduces a new algorithm to approximate non-orthogonal joint diagonalization (NOJD) of a set of complex matrices. This algorithm is based on the Frobenius norm formulation of ...