We introduce qprof, a new and extensible quantum program profiler able to generate profiling reports of quantum circuits written using various quantum computing frameworks. We describe the internal structure and working of qprof and provide practical examples on quantum circuits with increasing complexity along with benchmarks of the tool execution time on large circuits. This tool will allow researchers to visualise their quantum algorithm implementation in a different and complementary way and reliably localise the bottlenecks for efficient code optimisation.

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.