output
20022025
most citedSMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

83 citations

58 papers

quant-ph2025★ 19 cited

Landauer Principle and Thermodynamics of Computation

Pritam Chattopadhyay, Avijit Misra, Tanmoy Pandit +1

According to the Landauer principle, any logically irreversible process accompanies entropy production, which results in heat dissipation in the environment. Erasing of information…

quant-ph2024★ 9 cited

Robust double Bragg diffraction via detuning control

Rui Li, V. J. Martínez-Lahuerta, S. Seckmeyer +2

We present a theoretical model and numerical optimization of double Bragg diffraction, a widely used technique in atom interferometry. We derive an effective two-level-system Hamil…

math.AP2021★ 1 cited

A unified framework for Navier-Stokes Cahn-Hilliard models with non-matching densities

M. ten Eikelder, K. van der Zee, I. Akkerman +1

Over the last decades, many diffuse-interface Navier-Stokes Cahn-Hilliard models with non-matching densities have appeared in the literature. These models claim to describe the sam…

quant-ph2021★ 2 cited

Quantum Simulation of Conformal Field Theory

Tobias J. Osborne, Alexander Stottmeister

Conformal field theory, describing systems with scaling symmetry, plays a crucial role throughout physics. We describe a quantum algorithm to simulate the dynamics of conformal fie…

physics.ins-det2021

FPGA-based low-cost synchronized fiber network for experimental setups in space

Tim Oberschulte, Thijs Wendrich, Holger Blume

Custom experiment setups in physics often require control electronics to execute actions and measurements on a small time scale. When further constraints limit the experiment's env…

cs.LG2021★ 83 cited

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

Marius Lindauer, Katharina Eggensperger, Matthias Feurer +6

Algorithm parameters, in particular hyperparameters of machine learning algorithms, can substantially impact their performance. To support users in determining well-performing hype…