Studying how changes on the transpilation and the number of shots can be used to optimize quantum circuits

Context: Quantum computing is an emerging technology with the potential to address problems that are unsolvable for classical systems.However, adapting quantum software to current hardware constraints remains a significant challenge, particularly when aiming for efficient and sustainable executions.Objective: This study explores how two strategies applied during the preparation and execution stages of quantum software development can affect the results and energy consumption of the executions of a simple quantum circuit.Method: We analyse the impact of (1) the explicit selection of physical qubits within a quantum device, and (2) the number of individual executions per measurement.For each strategy, 12 executions are performed.From each execution, the outcomes of the measurements (to calculate the success rate of each case), and the execution times are collected.Results: Our analysis shows that the selection of physical qubits has a significant effect, showing a 20% drop in success rate and an increase in execution time (and therefore energy consumption) between a suboptimal qubit allocation versus a better allocation.Furthermore, the number of shots influences the quality of the outcomes, the results suggest that there might be an optimal number of shots for each circuit.Conclusions: The strategies disclosed in this study seem to affect the final outcomes and runtime required to execute our simple circuit.These strategies should be analysed for more complex circuits, and we should also check how their combination might affect the final results.