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quant-ph2026
Machine Learning Optimal Quantum Error Correction Thresholds
Dominik Seip, Luis Colmenarez, Markus Schmitt +1
As quantum computers remain susceptible to noise, QEC is essential for preserving logical information during computations. However, the performance of QEC codes breaks down beyond…
quant-ph2025
Reinforcement learning entangling operations on spin qubits
Mohammad Abedi, Markus Schmitt
High-fidelity control of one- and two-qubit gates past the error correction threshold is an essential ingredient for scalable quantum computing. We present a reinforcement learning…
quant-ph2025
Learning to stabilize nonequilibrium phases of matter with active feedback using partial information
Giovanni Cemin, Markus Schmitt, Marin Bukov
We investigate the role of information in active feedback control of quantum many-body systems using reinforcement learning. Active feedback breaks detailed balance, enabling the e…