activity
20182023
most citedSelf-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks

46 citations · 201 across the 7 of their papers we have counts for

collaborators
Showing quant-phShow all

5 papers · 1 filter

quant-ph2023★ 18 cited

Variational quantum algorithm for ergotropy estimation in quantum many-body batteries

Duc Tuan Hoang, Friederike Metz, Andreas Thomasen +3

Quantum batteries are predicted to have the potential to outperform their classical counterparts and are therefore an important element in the development of quantum technologies.…

quant-ph2022★ 46 cited

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks

Friederike Metz, Marin Bukov

Quantum many-body control is a central milestone en route to harnessing quantum technologies. However, the exponential growth of the Hilbert space dimension with the number of qubi…

quant-ph2021★ 38 cited

Variational Quantum Anomaly Detection: Unsupervised mapping of phase diagrams on a physical quantum computer

Korbinian Kottmann, Friederike Metz, Joana Fraxanet +1

One of the most promising applications of quantum computing is simulating quantum many-body systems. However, there is still a need for methods to efficiently investigate these sys…

quant-ph2021★ 41 cited

Adiabatic critical quantum metrology cannot reach the Heisenberg limit even when shortcuts to adiabaticity are applied

Karol Gietka, Friederike Metz, Tim Keller +1

We show that the quantum Fisher information attained in an adiabatic approach to critical quantum metrology cannot lead to the Heisenberg limit of precision and therefore regular q…

quant-ph2020★ 21 cited

Universal and optimal coin sequences for high entanglement generation in 1D discrete time quantum walks

Aikaterini Gratsea, Friederike Metz, Thomas Busch

Entanglement is a key resource in many quantum information applications and achieving high values independently of the initial conditions is an important task. Here we address the…