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

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 […]

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