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Simulating work extraction in a dinuclear quantum battery using a variational quantum algorithm.

Lucas Q Galvão1,2, Ana Clara das Neves3, Maron F Anka2

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This study uses quantum computational methods to analyze quantum batteries, finding that while they can store energy, environmental noise and temperature significantly impact their performance and precision for practical applications.

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Area of Science:

  • Quantum Computing
  • Quantum Thermodynamics
  • Quantum Technologies

Background:

  • Developing energy-efficient quantum technologies requires understanding quantum system thermodynamics.
  • Quantum batteries offer a promising avenue for energy storage in quantum devices.

Purpose of the Study:

  • To investigate quantum properties and work extraction in a dinuclear quantum battery model using quantum computational methods.
  • To assess the feasibility of quantum batteries in near-term devices, considering noisy environments and temperature effects.

Main Methods:

  • Application of variational quantum algorithms to a dinuclear quantum battery model.
  • Analysis of quantum properties and work extraction processes.
  • Evaluation of performance in simulated noisy environments and varying temperatures.

Main Results:

  • Variational quantum algorithms accurately reproduced key experimental trends.
  • Noisy environments were found to reduce the accuracy of stored energy evaluation.
  • Precise work extraction was observed primarily at low temperatures, with limited accuracy at ambient conditions.

Conclusions:

  • Quantum batteries show potential for energy storage, but environmental noise and temperature are critical limitations.
  • The presented quantum computational protocol offers insights into quantum battery performance but requires further optimization for practical, room-temperature applications.