Related papers: Optimizing measurement-based cooling by reinforcem…
Heat-bath algorithmic cooling (AC) of spins is a theoretically powerful effective cooling approach, that (ideally) cools spins with low polarization exponentially better than cooling by reversible entropy manipulations alone. Here, we…
Cooling a mechanical mode to its motional ground state opens up avenues for both scientific and technological advancements in the field of quantum meteorology and information processing. We propose a multi-parameter optimization scheme for…
Using a semi-classical approach, we describe an on-chip cooling protocol for a micro-mechanical resonator by employing a superconducting flux qubit. A Lorentz force, generated by the passive back-action of the resonator's displacement, can…
We study microwave-driven cooling in a superconducting flux qubit subjected to environment noises. For the weak decoherence, our analytical results agree well with the experimental observations near the degeneracy point and show that the…
This thesis investigates dataset downsampling as a strategy to optimize energy efficiency in recommender systems while maintaining competitive performance. With increasing dataset sizes posing computational and environmental challenges,…
A model for the cooling properties of a nanocantilever by a free electron beam is presented for a capacitive interaction. The optimal parameters for position sensing and cooling applications are estimated from previous experimental…
Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting…
A sideband cooling strategy that incorporates (i) the dynamics induced by structured (non-Markovian) environments in the target and auxiliary systems and (ii) the optimally-time-modulated interaction between them is developed. For the…
We propose an adaptive phase technique for the parametric cooling of mechanical resonances. This involves the detection of the mechanical quadratures, followed by a sequence of periodic controllable adjustments of the phase of a parametric…
A new global analytical model of the heat dissipation process that occurs in passively-cooled embedded systems is introduced, and we explicit under what circumstances the traditional assumption that exponential cooling laws apply in such…
Machine-learning techniques are emerging as a valuable tool in experimental physics, and among them, reinforcement learning offers the potential to control high-dimensional, multistage processes in the presence of fluctuating environments.…
Reinforcement learning (RL) techniques have been developed to optimize industrial cooling systems, offering substantial energy savings compared to traditional heuristic policies. A major challenge in industrial control involves learning…
We consider an optimization problem related to semi-active damping of vibrating systems. The main problem is to determine the best damping matrix able to minimize influence of the input on the output of the system. We use a minimization…
Resolved sideband cooling is a standard technique for cooling trapped ions below the Doppler limit to near their motional ground state. Yet, the most common methods for sideband cooling implicitly rely on low Doppler-cooled temperatures and…
Recent years have witnessed the great successes of embedding-based methods in recommender systems. Despite their decent performance, we argue one potential limitation of these methods -- the embedding magnitude has not been explicitly…
Electric water heaters have the ability to store energy in their water buffer without impacting the comfort of the end user. This feature makes them a prime candidate for residential demand response. However, the stochastic and nonlinear…
We consider a molecular single electron transistor coupled to a vibrational mode. For some values of the bias and gate voltage transport is possible only by absorption of one ore more phonons. The system acts then as a cooler for the…
We analyze the performance of optomechanical cooling of a mechanical resonator in the presence of a degenerate optical parametric amplifier within the optomechanical cavity, which squeezes the cavity light. We demonstrate that this allows…
The performance of a radiatively cooled instrument is investigated in the context of optomechanical quantum experiments, where the environment of a macroscopic particle in a quantum-superposition has to be cooled to less than 20\,K in deep…
Reinforcement learning is employed to optimize the periodic forcing signal of a pulsed blowing system that controls flow separation in a fully-turbulent $Re_\theta = 1000$ diffuser flow. Based on the state of the wind tunnel experiment that…