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From the 1 of 7 linked papers with an AI index.

most citedAccelerating two-dimensional tensor network contractions using QR decompositions

1 citations · 1 across the 2 of their papers we have counts for

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7 papers

cond-mat.str-el2026

Fast two-dimensional tensor-network contraction via subspace iteration

Yining Zhang, Philippe Corboz

The paper proposes a subspace-iteration CTMRG method that replaces large SVDs with smaller ones using QR-based projectors, greatly speeding up iPEPS tensor-network contractions and…

cond-mat.str-el20261 cited

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…

cond-mat.str-el2026

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…

cond-mat.str-el2025

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…

cond-mat.str-el2025

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…

cond-mat.stat-mech2025

Effective dimensional reduction of complex systems based on tensor networks

Wout Merbis, Madelon Geurts, Clélia de Mulatier +1

The exact treatment of Markovian models of complex systems requires knowledge of probability distributions exponentially large in the number of components . Mean-field approxima…