81 citations · 99 across the 4 of their papers we have counts for
6 papers
Reinforcement learning for ion shuttling on trapped-ion quantum computers
Maximilian Schier, Lea Richtmann, Christian Staufenbiel +4
Scalable trapped-ion quantum computing is commonly realized with modular chips that feature distinct zones with specific functionalities, such as storage, state preparation, and ga…
Stabilizing quantum simulations of lattice gauge theories by dissipation
Tobias Schmale, Hendrik Weimer
Simulations of lattice gauge theories on noisy quantum hardware inherently suffer from violations of the gauge symmetry due to coherent and incoherent errors of the underlying phys…
Real-time hybrid quantum-classical computations for trapped-ions with Python control-flow
Tobias Schmale, Bence Temesi, Niko Trittschanke +7
In recent years, the number of hybrid algorithms that combine quantum and classical computations has been continuously increasing. These two approaches to computing can mutually en…
Backend compiler phases for trapped-ion quantum computers
Tobias Schmale, Bence Temesi, Alakesh Baishya +6
A promising architecture for scaling up quantum computers based on trapped ions are so called Quantum Charged-Coupled Devices (QCCD). These consist of multiple ion traps, each desi…
Efficient quantum state tomography with convolutional neural networks
Tobias Schmale, Moritz Reh, Martin Gärttner
Modern day quantum simulators can prepare a wide variety of quantum states but the accurate estimation of observables from tomographic measurement data often poses a challenge. We…
Exploring phase space with Neural Importance Sampling
Enrico Bothmann, Timo Janßen, Max Knobbe +2
We present a novel approach for the integration of scattering cross sections and the generation of partonic event samples in high-energy physics. We propose an importance sampling…