Efficiency optimization in quantum computing: balancing thermodynamics and computational performance

Tomasz Śmierzchalski, Zakaria Mzaouali, Sebastian Deffner, Bartłomiej Gardas

This repository contains code used to produce results reported in Efficiency optimization in quantum computing: balancing thermodynamics and computational performance. We investigate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer under reverse-annealing with and without pausing. Our demonstration on the D-Wave 2000Q annealer shows that the combination of reverse-annealing and pausing leads to improved computational efficiency while minimizing the thermodynamic cost compared to reverse-annealing alone. Moreover, we find that the magnetic field has a positive impact on the performance of the quantum annealer during reverse-annealing but becomes detrimental when pausing is involved. Our results, which are reproducible, provide strategies for optimizing the performance and energy consumption of quantum annealing systems employing reverse-annealing protocols.