arXiv Machine Learning August 20, 2026 By Gustav J L J\"ager, Martin B Plenio, Hans-Martin Rieser

Quantum Tensor Network Learning with DMRG

Read the original on arXiv Machine Learning →

The paper introduces a quantum tensor network learning framework that employs matrix product states (MPS) as a machine‑learning architecture, adding a global normalization condition to interpret the MPS as a quantum state. It compares two optimization strategies—gradient descent and a DMRG‑adapted method—to identify locally optimal tensors and evaluates their effectiveness.

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