Contraction strategies of Tensor Networks for Quantum Circuit simulations

In the last years, the classical simulation of quantum systems is growing as a good approach to provide effcient approximations to quantum computers that are in the way of reaching quantum supremacy. An effcient way of performing simulations is through the use of tensor networks which can be described as a countable collection of tensors connected by contractions. The main advantage of this approach is that a quantum circuit can be easily mapped into a tensor network. This work studies the contraction of tensor networks that correspond to quantum circuits with different geometries and sizes. The method used to find the contraction path also affects the results, so the same circuits have been contracted for each path finding method. The information extracted is the size of the largest intermediate tensor in the contraction rather than computing the contraction itself. In the results it has been seen that the method used, the geometry and the size of a circuit have an impact on the size of the largest intermediate tensor of a contraction