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Task 1.4: Tensor Networks for Quantum Systems

Task lead: Enrique Rico Ortega
This task will develop and apply quantum-inspired methodology, in particular Tensor Network algorithms, to simulate quantum many-body problems unreachable by classic approaches and benchmark future applications of quantum hardware on low-entangled systems to O(100) qubits, progressing towards the development of a software stack for quantum machine learning model design, simulation, and deployment.
Publications and other resources
– Workshop on Tensor Networks and (Quantum) Machine Learning for High-Energy Physics