2 citations · 5 across the 6 of their papers we have counts for
7 papers
Diversifying time evolution of matrix product states using BUGs
Kornél Kapás, Dominik Sulz, Charlotte Verhoeven +3
Time evolution of tensor-network states is a central tool for studying nonequilibrium dynamics in strongly correlated quantum systems. In the past decade, using the time-dependent…
A Tensor-Train Framework for Bayesian Inference in High-Dimensional Systems: Applications to MIMO Detection and Channel Decoding
Luca Schmid, Dominik Sulz, Shrinivas Chimmalgi +1
Bayesian inference in high-dimensional discrete-input additive noise models is a fundamental challenge in communication systems, as the support of the required joint a posteriori p…
A parallel Basis Update and Galerkin Integrator for Tree Tensor Networks
Gianluca Ceruti, Jonas Kusch, Christian Lubich +1
Computing the numerical solution to high-dimensional tensor differential equations can lead to prohibitive computational costs and memory requirements. To reduce the memory and com…
Low-rank Tree Tensor Network Operators for Long-Range Pairwise Interactions
Gianluca Ceruti, Daniel Kressner, Dominik Sulz
Compactly representing and efficently applying linear operators are fundamental ingredients in tensor network methods for simulating quantum many-body problems and solving high-dim…
Fast and Robust Expectation Propagation MIMO Detection via Preconditioned Conjugated Gradient
Luca Schmid, Dominik Sulz, Laurent Schmalen
We study the expectation propagation (EP) algorithm for symbol detection in massive multiple-input multiple-output (MIMO) systems. The EP detector shows excellent performance but s…
Numerical simulations of long-range open quantum many-body dynamics with tree tensor networks
Dominik Sulz, Christian Lubich, Gianluca Ceruti +2
Open quantum systems provide a conceptually simple setting for the exploration of collective behavior stemming from the competition between quantum effects, many-body interactions,…
Rank-adaptive time integration of tree tensor networks
Gianluca Ceruti, Christian Lubich, Dominik Sulz
A rank-adaptive integrator for the approximate solution of high-order tensor differential equations by tree tensor networks is proposed and analyzed. In a recursion from the leaves…