Using the corner-transfer matrix renormalization group to contract the tensor network that describes its partition function, we investigate the nature of the phase transitions of the hard-square model, one of the exactly solved models of statistical physics for which Baxter has found an integrable manifold. The motivation is twofold: assess the power of tensor networks for such models, and probe the 2D classical analog of a 1D quantum model of hard-core bosons that has recently attracted significant attention in the context of experiments on chains of Rydberg atoms. Accordingly, we concentrate on two planes in the 3D parameter space spanned by the activity and the coupling constants in the two diagonal directions. We first investigate the o...
The study of correlation effects in topological phases of matter can benefit from a multidisciplinar...
We apply variational tensor-network methods for simulating the Kosterlitz-Thouless phase transition ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
This thesis explores several aspects of the 2D Ising Model at both real and complex temperatures uti...
This thesis explores several aspects of the 2D Ising Model at both real and complex temperatures uti...
none7siWe investigate a model of hard-core bosons with infinitely repulsive nearest- and next-neares...
We investigate a model of hard-core bosons with infinitely repulsive nearest- and next-nearest-neigh...
We investigate a model of hard-core bosons with infinitely repulsive nearest- and next-nearest-neigh...
Several investigations are presented around the general topic of the ground state and low-energy beh...
The quantum Kibble-Zurek mechanism (QKZM) predicts universal dynamical behavior near the quantum pha...
Tensor network algorithms have emerged as a new approach in simulating strongly correlated quantum m...
In this paper we explore the practical use of the corner transfer matrix and its higher-dimensional ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We analyze the renormalization group fixed point of the two-dimensional Ising model at criticality. ...
Theory of quantum many-body systems plays a key role in understanding the properties of phases of ma...
The study of correlation effects in topological phases of matter can benefit from a multidisciplinar...
We apply variational tensor-network methods for simulating the Kosterlitz-Thouless phase transition ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
This thesis explores several aspects of the 2D Ising Model at both real and complex temperatures uti...
This thesis explores several aspects of the 2D Ising Model at both real and complex temperatures uti...
none7siWe investigate a model of hard-core bosons with infinitely repulsive nearest- and next-neares...
We investigate a model of hard-core bosons with infinitely repulsive nearest- and next-nearest-neigh...
We investigate a model of hard-core bosons with infinitely repulsive nearest- and next-nearest-neigh...
Several investigations are presented around the general topic of the ground state and low-energy beh...
The quantum Kibble-Zurek mechanism (QKZM) predicts universal dynamical behavior near the quantum pha...
Tensor network algorithms have emerged as a new approach in simulating strongly correlated quantum m...
In this paper we explore the practical use of the corner transfer matrix and its higher-dimensional ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We analyze the renormalization group fixed point of the two-dimensional Ising model at criticality. ...
Theory of quantum many-body systems plays a key role in understanding the properties of phases of ma...
The study of correlation effects in topological phases of matter can benefit from a multidisciplinar...
We apply variational tensor-network methods for simulating the Kosterlitz-Thouless phase transition ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...