activity
20082026
most citedTime-dependent variational principle for quantum lattices

869 citations · 6.9k across the 101 of their papers we have counts for

collaborators

103 papers

quant-ph2026

Finite-Element Matrix Product States for Continuum Models in One Dimension

Akshay Shankar, Karel Van Acoleyen, Jutho Haegeman

We present a matrix product state framework for simulating one-dimensional quantum many-body systems in the continuum using non-orthogonal single-particle basis sets. By mapping th…

quant-ph2026

Implicit differentiation of tensor network algorithms

Lander Burgelman, Anna Francuz, Paul Brehmer +4

The current leading approach to the variational optimization of projected entangled-pair states (PEPS) is based on automatic differentiation, which allows for a convenient evaluati…

quant-ph2026

Matrix Product Operator Encodings of the Magnus Expansion and Dyson Series

Victor Vanthilt, Maarten Van Damme, Jutho Haegeman +2

We introduce a matrix product operator (MPO) encoding of the Magnus expansion and the Dyson series for one-dimensional quantum lattice models with time-dependent Hamiltonians. The…

cond-mat.str-el2026

PEPSKit.jl: A Julia package for projected entangled-pair state simulations

Paul Brehmer, Lander Burgelman, Zheng-Yuan Yue +3

We present PEPSKitjl, a Julia package for simulating two-dimensional quantum many-body systems with infinite projected entangled-pair states (iPEPS). PEPSKitjl builds on the…

cond-mat.str-el2026★ 1 cited

Lowering the temperature of two-dimensional fermionic tensor networks with cluster expansions

Sander De Meyer, Atsushi Ueda, Yuchi He +2

Representing the time-evolution operator as a tensor network constitutes a key ingredient in several algorithms for studying quantum lattice systems at finite temperature or in a n…

cond-mat.str-el2026

Combining matrix product states and mean-field theory to capture magnetic order in quasi-1D cuprates

Quentin Staelens, Daan Verraes, Daan Vrancken +3

We study quasi-one-dimensional strongly correlated materials using a multi-step approach based on density functional theory, downfolding techniques, and tensor-network simulations.…