ORCID Profile
0000-0002-6318-579X
Current Organisation
Arak University
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Publisher: Springer Science and Business Media LLC
Date: 13-12-2018
Publisher: Elsevier BV
Date: 06-2023
Publisher: IOP Publishing
Date: 28-09-2023
Publisher: Institution of Engineering and Technology (IET)
Date: 10-2013
Publisher: Elsevier BV
Date: 08-2022
Publisher: Springer Science and Business Media LLC
Date: 21-12-2022
Publisher: IEEE
Date: 23-02-2021
Publisher: IOP Publishing
Date: 16-02-2023
Abstract: Expanding utilization of entangled states in quantum technologies, such as quantum information, is a motivating force of developing new methods for enhancement and stabilization of quantum entanglement. This study focuses on using asymmetric lawsto control the entangled states of a quantum systemconsistingof two atoms, each confined in a cavity.The effect of asymmetry laws has been explored in three different scenarios. First, the effect of an asymmetric drive Hamiltonian on a closed quantum system, in which neither the cavity nor the atoms exhibit losses, is studied. Here, the eigenvalues and eigenstates of the total system Hamiltonian have been obtained and the time evolution of the system state has been derived. Also, the fidelity of the system in terms of the asymmetric drive Hamiltonian has been derived analytically. In the second scenario, the stationary solution of an open quantum system, which includes losses in a master equation approach, is derived and the concurrence is studied in terms of the asymmetric drive Hamiltonian and coupling constant. The last scenario is devoted to applying feedback rulesto an open quantum system where some heuristic feedback control laws have been proposed. The simulation results show the concurrence boosting in a larger range of driving field and feedback strength when applying the introduced feedback rules.
Publisher: IEEE
Date: 23-02-2021
Publisher: Springer Science and Business Media LLC
Date: 10-09-2022
Publisher: Elsevier BV
Date: 07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 04-2020
Publisher: IOP Publishing
Date: 14-07-2022
Abstract: This paper presents a cavity-assisted coherent feedback scheme to cool a mechanical resonator to the ground-state in a weak optomechanical coupling setup. Based on the theory of sideband cooling, resolved sideband regime is a mandatory condition for the ground-state cooling (GSC) in optomechanical systems. Assisted cooling and feedback cooling methods have been proposed and shown to be beneficial for cooling in unresolved sideband cases. In this paper, a cooling method is proposed by combining both approaches. In the proposed method, a coherent feedback loop is added to a cavity-assisted optomechanical system to enhance the cooling performance. The proposed feedback aims to reach the mechanical ground-state in the unresolved sideband regime (USR). Rate equations of the mechanical resonator are derived, and then, by applying Fermi’s golden rule and analyzing the fluctuation spectrum of the optical force, optimal conditions for cooling are obtained. Results show that applying coherent feedback, improves the cooling performance of the system significantly and it is possible to achieve GSC in USR. Moreover, it is shown that the proposed method is capable of cooling the mechanical resonator to much lower energy levels than it is achievable in cavity assisted method.
Publisher: IEEE
Date: 10-2019
Publisher: Elsevier BV
Date: 11-2020
Publisher: Wiley
Date: 10-10-2018
DOI: 10.1002/RNC.3964
Publisher: Elsevier BV
Date: 05-2023
Publisher: Институт проблем управления им. В. А. Трапезникова РАН
Date: 2021
Publisher: IEEE
Date: 10-2019
Publisher: Springer Science and Business Media LLC
Date: 05-2022
Publisher: Walter de Gruyter GmbH
Date: 26-07-2022
Abstract: Lime is a significant material in many industrial processes, including steelmaking by blast furnace. Lime production through rotary kilns is a standard method in industries, yet it has depreciation, high energy consumption, and environmental pollution. A model of the lime production process can help to not only increase our knowledge and awareness but also can help reduce its disadvantages. This paper presents a black-box model by Artificial Neural Network (ANN) for the lime production process considering pre-heater, rotary kiln, and cooler parameters. To this end, actual data are collected from Zobahan Isfahan Steel Company, Iran, which consists of 746 data obtained in a duration of one year. The proposed model considers 23 input variables, predicting the amount of produced lime as an output variable. The ANN parameters such as number of hidden layers, number of neurons in each layer, activation functions, and training algorithm are optimized. Then, the sensitivity of the optimum model to the input variables is investigated. Top-three input variables are selected on the basis of one-group sensitivity analysis and their interactions are studied. Finally, an ANN model is developed considering the top-three most effective input variables. The mean square error of the proposed models with 23 and 3 inputs are equal to 0.000693 and 0.004061, respectively, which shows a high prediction capability of the two proposed models.
Publisher: Elsevier BV
Date: 06-2021
Location: Iran (Islamic Republic of)
No related grants have been discovered for Abolghasem Daeichian.