Tensor Networks provide efficient representation for quantum states and the basis for variational algorithms for finding the ground-state and thermal-states of quantum many-body Hamiltonians.
learn moreFrustrated spin systems are a unique and ideal platform for hosting exotic phases of matter such as quantum spin liquids, valence-bond crystals, and other interesting types of quantum paramagnets.
learn moreTopological quantum codes such as the Kitaev model and topological color codes are not only potential candidates for fault-tolerant quantum computation but also ideal playgrounds for characterizing quantum spin liquids, their anyonic excitations, and fractionalization mechanism.
learn moreQuantum-Inspired methods based on tensor networks and also pure quantum approaches such as QAOA or VQE are the future of optimization and quantum technology.
learn moreQuantum Computers and quantum-inspired approaches based on the tensor network can enhance and boost the machine learning tasks such as classification, clustering and even training of deep neural networks.
learn moreA great part of our research at IASBS involves developing advanced and computationally fast algorithms for simulating physics problems. Our main computational resource is the GAVAZANG HPC cluster
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