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We use fast periodic control to realize finite-time Otto cycles exhibiting quantum advantage. Such periodic modulation of the working medium - bath interaction Hamiltonian during the thermalization strokes can give rise to non-Markovian…

Quantum Physics · Physics 2020-07-17 Arpan Das , Victor Mukherjee

We study the relaxation of a quantum system towards the thermal equilibrium using tools developed within the context of quantum information theory. We consider a model in which the system is a qubit, and reaches equilibrium after several…

Quantum Physics · Physics 2009-11-07 Valerio Scarani , Mario Ziman , Peter Stelmachovic , Nicolas Gisin , Vladimir Buzek

A reciprocating quantum refrigerator is studied with the purpose of determining the limitations of cooling to absolute zero. We find that if the energy spectrum of the working medium possesses an uncontrollable gap, then there is a minimum…

Quantum Physics · Physics 2009-09-08 Tova Feldmann , Ronnie Kosloff

Quantum coherence has been shown to impact the operational capabilities of quantum systems performing thermodynamic tasks in a significant way, and yet the possibility and conditions for genuine coherence-enhanced thermodynamic operation…

Quantum Physics · Physics 2025-10-08 José A. Almanza-Marrero , Gonzalo Manzano

The unavoidable irreversible losses of power in a heat engine are found to be of quantum origin. Following thermodynamic tradition a model quantum heat engine operating by the Otto cycle is analyzed. The working medium of the model is…

Quantum Physics · Physics 2009-11-13 Yair Rezek , Ronnie Kosloff

Modern technologies could soon make it possible to investigate the operation cycles of quantum heat engines by counting the photons that are emitted and absorbed by their working systems. Using the quantum jump approach to open-system…

Statistical Mechanics · Physics 2020-09-29 Paul Menczel , Christian Flindt , Kay Brandner

Identifying optimal thermodynamical processes has been the essence of thermodynamics since its inception. Here, we show that differentiable programming (DP), a machine learning (ML) tool, can be employed to optimize finite-time…

Quantum Physics · Physics 2022-03-24 Ilia Khait , Juan Carrasquilla , Dvira Segal

Cooling quantum systems is arguably one of the most important thermodynamic tasks connected to modern quantum technologies and an interesting question from a foundational perspective. It is thus of no surprise that many different…

In this thesis, we consider two simple but typical control problems and apply deep reinforcement learning to them, i.e., to cool and control a particle which is subject to continuous position measurement in a one-dimensional quadratic…

Quantum Physics · Physics 2022-12-15 Zhikang Wang

We present a classical control mechanism for Quantum devices using Reinforcement Learning. Our strategy is applied to the Quantum Approximate Optimization Algorithm (QAOA) in order to optimize an objective function that encodes a solution…

Quantum Physics · Physics 2019-11-25 Artur Garcia-Saez , Jordi Riu

The quest to identify the best heat engine has been at the center of science and technology. Thermoelectric nanoscale heat engines convert heat flows into useful work in the form of electrical power and promise the realization of on-chip…

Statistical Mechanics · Physics 2021-03-11 Yuto Ashida , Takahiro Sagawa

Thermodynamics in quantum circuits aims to find improved functionalities of thermal machines, highlight fundamental phenomena peculiar to quantum nature in thermodynamics, and point out limitations in quantum information processing due to…

Quantum thermodynamics is a powerful theoretical tool for assessing the suitability of quantum materials as platforms for novel technologies. In particular, the modeling of quantum cycles allows us to investigate the heat changes and work…

Quantum Physics · Physics 2024-11-20 Vinicius Gomes de Paula , Wanisson S. Santana , Clebson Cruz , Mario Reis

We study optimal control strategies to optimize the relaxation rate towards the fixed point of a quantum system in the presence of a non-Markovian dissipative bath. Contrary to naive expectations that suggest that memory effects might be…

Quantum machine learning models use encoding circuits to map data into a quantum Hilbert space. While it is well known that the architecture of these circuits significantly influences core properties of the resulting model, they are often…

Quantum Physics · Physics 2025-03-03 Frederic Rapp , David A. Kreplin , Marco F. Huber , Marco Roth

We present a measurement-based quantum thermal machine that extracts work from the back-action of generalized quantum measurements whose working medium is a coupled two-level quantum system. Specifically, we derive universal optimization…

Quantum Physics · Physics 2026-03-27 Chinonso Onah , Obinna Uzoh , Obinna Abah

Model bias is an inherent limitation of the current dominant approach to optimal quantum control, which relies on a system simulation for optimization of control policies. To overcome this limitation, we propose a circuit-based approach for…

Quantum Physics · Physics 2022-03-31 V. V. Sivak , A. Eickbusch , H. Liu , B. Royer , I. Tsioutsios , M. H. Devoret

We propose a three-qubit setup for the implementation of a variety of quantum thermal machines where all heat fluxes and work production can be controlled. An important configuration that can be designed is that of an absorption…

During their operation, due to shifts in environmental conditions, devices undergo various forms of detuning from their optimal settings. Typically, this is addressed through control loops, which monitor variables and the device…

Quantum Physics · Physics 2024-04-17 T. Crosta , L. Rebón , F. Vilariño , J. M. Matera , M. Bilkis

Developments in the thermodynamics of small quantum systems envisage non-classical thermal machines. In this scenario, energy fluctuations play a relevant role in the description of irreversibility. We experimentally implement a quantum…

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