3 citations · 8 across the 8 of their papers we have counts for
8 papers · 1 filter
Fast two-dimensional tensor-network contraction via subspace iteration
Yining Zhang, Philippe Corboz
The corner transfer matrix renormalization group (CTMRG) is one of the standard contraction methods for infinite projected entangled-pair states (iPEPS), but its computational cost…
Topological and Trivial Valence-Bond Orders in Higher-Spin Kitaev Models
Xing-Yu Zhang, Qi Yang, Philippe Corboz +2
We investigate the quantum phases of higher-spin Kitaev models using tensor network methods. Our results reveal distinct bond-ordered phases for spin-1, spin-, and sp…
Accelerating two-dimensional tensor network optimization by preconditioning
Xing-Yu Zhang, Qi Yang, Philippe Corboz +2
We revisit gradient-based optimization for infinite projected entangled pair states (iPEPS), a tensor network ansatz for simulating many-body quantum systems. This approach is hind…
Efficient iPEPS Simulation on the Honeycomb Lattice via QR-based CTMRG
Qi Yang, Philippe Corboz
We develop a QR-based corner transfer matrix renormalization group (CTMRG) framework for contracting infinite projected entangled-pair states (iPEPS) on honeycomb lattices. Our met…
Accelerating two-dimensional tensor network contractions using QR decompositions
Yining Zhang, Qi Yang, Philippe Corboz
Infinite projected entangled-pair states (iPEPS) provide a powerful tool for studying strongly correlated systems directly in the thermodynamic limit. A core component of the algor…
Exploiting the Hermitian symmetry in tensor network algorithms
Oscar van Alphen, Stijn V. Kleijweg, Juraj Hasik +1
Exploiting symmetries in tensor network algorithms plays a key role for reducing the computational and memory costs. Here we explain how to incorporate the Hermitian symmetry in do…