213 citations · 217 across the 4 of their papers we have counts for
6 papers
Efficient approximation for global functions of matrix product operators
Moritz August, Mari Carmen Banuls
Building on a previously introduced block Lanczos method, we demonstrate how to approximate any operator function of the form Trf (A) when the argument A is given as a Hermitian ma…
Taking gradients through experiments: LSTMs and memory proximal policy optimization for black-box quantum control
Moritz August, José Miguel Hernández-Lobato
In this work we introduce the application of black-box quantum control as an interesting rein- forcement learning problem to the machine learning community. We analyze the structur…
Neural-Network Quantum States, String-Bond States, and Chiral Topological States
Ivan Glasser, Nicola Pancotti, Moritz August +2
Neural-Network Quantum States have been recently introduced as an Ansatz for describing the wave function of quantum many-body systems. We show that there are strong connections be…
Towards a better understanding of the matrix product function approximation algorithm in application to quantum physics
Moritz August, Thomas Huckle
We recently introduced a method to approximate functions of Hermitian Matrix Product Operators or Tensor Trains that are of the form . Functions of this type occu…
On the Approximation of Functionals of Very Large Hermitian Matrices represented as Matrix Product Operators
Moritz August, Mari Carmen Bañuls, Thomas Huckle
We present a method to approximate functionals of very high-dimensional hermitian matrices represented as Matrix Product Operators (MPOs). Our method is bas…
Using Recurrent Neural Networks to Optimize Dynamical Decoupling for Quantum Memory
Moritz August, Xiaotong Ni
We utilize machine learning models which are based on recurrent neural networks to optimize dynamical decoupling (DD) sequences. DD is a relatively simple technique for suppressing…