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Getting large-scale quantum neural networks ready for quantum hardware

quant-ph · 2026-04-27 · unverdicted · novelty 5.0

Physics-informed quantum neural networks trained on noisy measurements can construct nontrivial decision boundaries to classify quantum states via order parameters and are suited for NISQ hardware due to links with Markovian open many-body systems.

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  • Solving the Peierls-Boltzmann transport equation with matrix product states cond-mat.mes-hall · 2026-04-07 · conditional · none · ref 16

    An optimized matrix product state representation with DMRG-inspired solver solves the Peierls-Boltzmann transport equation for crystalline silicon phonons with high fidelity at 10^{-3} compression and sublinear scaling in grid size.