Quantum computing prepwork made faster with graph-based data grouping algorithm

Quantum computing prepwork made faster with graph-based data grouping algorithm

Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they're so different from today's computers that scientists need to figure out the best ways to feed them information to take full advantage. The data must be packed in new ways, customized for quantum treatment.

PNNL Develops Picasso Algorithm to Accelerate Quantum Data Preparation by 85% Using Graph Coloring and Clique Partitioning - Quantum Computing Report

Pacific Northwest National Laboratory (PNNL) has introduced a new algorithm, Picasso, that significantly reduces the computational resources required to prepare data for hybrid quantum-classical computing systems. The algorithm, which employs advanced techniques in graph coloring and clique partitioning, addresses a longstanding bottleneck in quantum information preparation by cutting down the required quantum input data by [...] The post PNNL D…

‘Sparsification’: PNNL Preps Data for Quantum

Quantum computing holds great promise in such such as computational chemistry and high-speed networking. But they’re so different from classical HPC systems that scientists are working out how to feed them quantum-ready data. Researchers at Pacific Northwest National Laboratory are developing an algorithm, called Picasso, designed to handle that task. The post ‘Sparsification’: PNNL Preps Data for Quantum appeared first on High-Performance Compu…

‘Sparsification’: PNNL Preps Data For Quantum - Data Intelligence

Quantum computing holds great promise in such such as computational chemistry and high-speed networking. But they’re so different from classical HPC systems that scientists are working out how to feed them quantum-ready data. Researchers at Pacific Northwest National Laboratory are developing an algorithm, called Picasso, designed for that task. The code, published recently on GitHub after it was presented at the IEEE International Symposium on …