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Description
One of the biggest challenges in computational physics is the simulation of strongly correlated systems, in particular frustrated and fermionic systems. Borrowing ideas and tools from quantum information and condensed matter physics, a new generation of simulation techniques for many-body systems, the so-called tensor network algorithms (e.g. PEPS, MERA), have been proposed in the last few years. These tensor networks enable an efficient representation of ground states of Hamiltonians with local interactions, which (usually) obey the so-called "area law" of the entanglement entropy. In this (informal) lecture I will give an introduction to the basic concepts of tensor network (TN) algorithms, including details about the structure, optimization and evaluation of tensor networks.