13 citations · 13 across the 5 of their papers we have counts for
5 papers
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…
Modeling light-matter coupled systems with neural quantum states
Noe Salmeron, Marin Bukov, Markus Schmitt
Recent advances in cold atom manipulation enable the study of many-body systems where short-range interactions between neighboring atoms coexist with long-range interactions mediat…
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…
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…
Reinforcement learning pulses for transmon qubit entangling gates
Ho Nam Nguyen, Felix Motzoi, Mekena Metcalf +3
The utility of a quantum computer depends heavily on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular i…