1 code implementation • 10 Mar 2023 • Gorka Muñoz-Gil, Andrea López-Incera, Lukas J. Fiderer, Hans J. Briegel
Recognizing the interconnected nature of these challenges, this work addresses them simultaneously by exploring optimal foraging strategies through a reinforcement learning framework.
no code implementations • 31 Jan 2023 • Fulvio Flamini, Marius Krumm, Lukas J. Fiderer, Thomas Müller, Hans J. Briegel
Variational quantum algorithms represent a promising approach to quantum machine learning where classical neural networks are replaced by parametrized quantum circuits.
1 code implementation • 25 Oct 2021 • Sofiene Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko
In this work, we identify a constructive framework that captures all standard models based on parametrized quantum circuits: that of linear quantum models.
no code implementations • 4 Mar 2020 • Lukas J. Fiderer, Jonas Schuff, Daniel Braun
Quantum metrology promises unprecedented measurement precision but suffers in practice from the limited availability of resources such as the number of probes, their coherence time, or non-classical quantum states.
no code implementations • 22 Aug 2019 • Jonas Schuff, Lukas J. Fiderer, Daniel Braun
Recently proposed quantum-chaotic sensors achieve quantum enhancements in measurement precision by applying nonlinear control pulses to the dynamics of the quantum sensor while using classical initial states that are easy to prepare.