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Mechanically nonlinear energy harvesters driven by broadband vibrations modeled as white noise are investigated. We derive an upper bound on output power versus load resistance and show that, subject to mild restrictions that we make…

Adaptation and Self-Organizing Systems · Physics 2013-05-03 Einar Halvorsen

We investigate how a single resonator with a time-modulated component extracts power from an external ambient source. However, the collected power is largely dependent on the precise choice of the modulation signal frequency. We focus on…

Applied Physics · Physics 2023-03-21 Alireza Nikzamir , Kasra Rouhi , Alexander Figotin , Filippo Capolino

Policymakers commonly employ non-pharmaceutical interventions to manage the scale and severity of pandemics. Of non-pharmaceutical interventions, social distancing policies -- designed to reduce person-to-person pathogenic spread -- have…

Physics and Society · Physics 2021-03-23 Demetris Avraam , Nick Obradovich , Niccoló Pescetelli , Manuel Cebrian , Alex Rutherford

This paper analyzes the impact of parametric uncertainties on the dynamics of bistable energy harvesters, focusing on obtaining statistical information about how each parameter's variability affects the energy harvesting process. To model…

Dynamical Systems · Mathematics 2023-10-18 João Pedro Norenberg , Americo Cunha , Samuel da Silva , Paulo Sergio Varoto

We consider a spectrum sharing scenario, where a secondary network coexists with a primary network of multiple transceivers. The secondary network consists of an energy-constrained decode-and-forward secondary relay which assists the…

Information Theory · Computer Science 2015-09-03 Sanket S. Kalamkar , Adrish Banerjee

The Jarzynski equality is one of the most influential results in the field of non equilibrium statistical mechanics. This celebrated equality allows to calculate equilibrium free energy differences from work distributions of nonequilibrium…

Statistical Mechanics · Physics 2017-09-13 Shahaf Asban , Saar Rahav

Obtaining reliable state preparation protocols is a key step towards practical implementation of many quantum technologies, and one of the main tasks in quantum control. In this work, different reinforcement learning approaches are used to…

Quantum Physics · Physics 2024-09-04 Manuel Guatto , Gian Antonio Susto , Francesco Ticozzi

Statistical properties of environments experienced by biological signaling systems in the real world change, which necessitate adaptive responses to achieve high fidelity information transmission. One form of such adaptive response is gain…

Molecular Networks · Quantitative Biology 2012-05-01 Ilya Nemenman

A fundamental problem in quantum thermodynamics is to properly quantify the work extractable from out-of-equilibrium systems. While for closed systems, maximum quantum work extraction is defined in terms of the ergotropy functional, this…

Quantum Physics · Physics 2024-10-22 Riccardo Castellano , Donato Farina , Vittorio Giovannetti , Antonio Acin

We pose an engineering challenge of controlling an Ensemble of Energy Devices via coordinated, implementation-light and randomized on/off switching as a problem in Non-Equilibrium Statistical Mechanics. We show that Mean Field Control} with…

Systems and Control · Computer Science 2020-02-19 David Métivier , Michael Chertkov

When a system is driven out of equilibrium by a time-dependent protocol that modifies the Hamiltonian, it follows a nonequilibrium path. Samples of these paths can be used in nonequilibrium work theorems to estimate equilibrium quantities,…

Statistical Mechanics · Physics 2009-05-29 David D. L. Minh

We study power control for an energy harvesting communication system with independent and identically distributed Bernoulli energy arrivals. It is assumed that the transmitter is equipped with a finite-sized rechargeable battery and is able…

Information Theory · Computer Science 2019-04-30 Ali Zibaeenejad , Jun Chen

We investigate a measurement-feedback process of repeated operations with time delay. During a finite-time interval, measurement on the system is performed and the feedback protocol derived from the measurement outcome is applied with time…

Statistical Mechanics · Physics 2020-01-08 Chulan Kwon , Jaegon Um , Hyunggyu Park

Feedback control actively dissipates uncertainty from a dynamical system by means of actuation. We develop a notion of "control capacity" that gives a fundamental limit (in bits) on the rate at which a controller can dissipate the…

Information Theory · Computer Science 2017-01-17 Gireeja Ranade , Anant Sahai

Recent developments in statistical mechanics have allowed the estimation of equilibrium free energies from the statistics of work measurements during processes that drive the system out of equilibrium. Here a different class of processes is…

Statistical Mechanics · Physics 2009-11-11 Artur B. Adib

Digital control has become increasingly prevalent in modern systems, making continuous-time plants controlled by discrete-time (digital) controllers ubiquitous and crucial across industries, including aerospace, automotive, and…

Systems and Control · Electrical Eng. & Systems 2023-10-10 Taoran Wu , Dejin Ren , Shuyuan Zhang , Lei Wang , Bai Xue

Quantum feedback control protocols can improve the operation of quantum devices. Here we examine the performance of a purification protocol when there are imperfections in the controls. The ideal feedback protocol produces an $x$ eigenstate…

Quantum Physics · Physics 2011-08-11 Joshua Combes , Howard M. Wiseman

Obtaining reliable feedback from the environment is a fundamental capability for intelligent agents to evaluate the correctness of their actions and to accumulate reusable knowledge. However, most existing approaches rely on predefined…

Artificial Intelligence · Computer Science 2026-01-09 Hong Su

This paper is concerned with the design of optimal control for finite-dimensional control-affine nonlinear dynamical systems. We introduce an optimal control problem that specifically optimizes nonlinear observability in addition to…

Systems and Control · Computer Science 2017-08-03 Atiye Alaeddini , Kristi A. Morgansen , Mehran Mesbahi

We address how to exploit power control data, gathered from a monitored environment, for performing power control in an unexplored environment. We adopt offline deep reinforcement learning, whereby the agent learns the policy to produce the…

Systems and Control · Electrical Eng. & Systems 2020-08-07 Mohammad G. Khoshkholgh , Halim Yanikomeroglu