18 citations · 56 across the 6 of their papers we have counts for
6 papers
TensorKrowch: Smooth integration of tensor networks in machine learning
José Ramón Pareja Monturiol, David Pérez-García, Alejandro Pozas-Kerstjens
Tensor networks are factorizations of high-dimensional tensors into networks of smaller tensors. They have applications in physics and mathematics, and recently have been proposed…
The minimal canonical form of a tensor network
Arturo Acuaviva, Visu Makam, Harold Nieuwboer +4
Tensor networks have a gauge degree of freedom on the virtual degrees of freedom that are contracted. A canonical form is a choice of fixing this degree of freedom. For matrix prod…
Dynamical quantum phase transitions from random matrix theory
David Pérez-García, Leonardo Santilli, Miguel Tierz
We uncover a novel dynamical quantum phase transition, using random matrix theory and its associated notion of planar limit. We study it for the isotropic XY Heisenberg spin chain.…
Matrix Product Operator Algebras II: Phases of Matter for 1D Mixed States
Alberto Ruiz-de-Alarcón, José Garre-Rubio, András Molnár +1
The classification of topological phases of matter is fundamental to understand and characterize the properties of quantum materials. In this paper we study phases of matter in one…
Matrix product operator algebras I: representations of weak Hopf algebras and projected entangled pair states
Andras Molnar, Alberto Ruiz de Alarcón, José Garre-Rubio +3
Matrix Product Operators (MPOs) are tensor networks representing operators acting on 1D systems. They model a wide variety of situations, including communication channels with memo…
Privacy-preserving machine learning with tensor networks
Alejandro Pozas-Kerstjens, Senaida Hernández-Santana, José Ramón Pareja Monturiol +4
Tensor networks, widely used for providing efficient representations of low-energy states of local quantum many-body systems, have been recently proposed as machine learning archit…