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Efficiency optimization in quantum computing: balancing thermodynamics and computational performance.

Tomasz Śmierzchalski1, Zakaria Mzaouali2, Sebastian Deffner3,4

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Reverse-annealing combined with pausing improves quantum annealer efficiency and minimizes thermodynamic cost. Magnetic fields aid reverse-annealing but hinder performance when pausing is used.

Keywords:
Quantum annealingQuantum computationQuantum thermodynamics

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Area of Science:

  • Quantum computing
  • Computational physics

Background:

  • Quantum annealers, like the D-Wave 2000Q, are specialized hardware for solving optimization problems.
  • Reverse-annealing is a technique to improve quantum annealing performance.
  • Understanding the thermodynamic cost is crucial for energy-efficient quantum computation.

Purpose of the Study:

  • To evaluate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer using reverse-annealing.
  • To investigate the impact of pausing during reverse-annealing.
  • To determine the effect of magnetic fields on reverse-annealing performance.

Main Methods:

  • Demonstration on the D-Wave 2000Q quantum annealer.
  • Comparison of reverse-annealing with and without pausing.
  • Analysis of computational efficiency and thermodynamic cost metrics.
  • Systematic variation of magnetic field strength.

Main Results:

  • Combining reverse-annealing with pausing significantly enhances computational efficiency.
  • This combination also minimizes the thermodynamic cost compared to reverse-annealing alone.
  • Magnetic fields positively impact reverse-annealing but negatively affect performance when pausing is employed.
  • Reproducible results demonstrating clear performance trends.

Conclusions:

  • Pausing during reverse-annealing offers a viable strategy for optimizing quantum annealer performance.
  • Strategies for minimizing energy consumption in quantum annealing systems are identified.
  • Findings provide practical insights for utilizing D-Wave annealers more effectively.