In Distributed Quantum Computing (DQC), individual quantum processors – limited in the number of qubits – work together to solve computational tasks exceeding the computational resources available within a single processing device. Within QIA, UNIPR is doing research on DQC, with the purpose to implement network services that enable the execution of distributed quantum programs on real quantum networks. The success of a distributed quantum computation depends on a number of factors, including the quality of physical qubits and gates of the quantum nodes, the entanglement routing effectiveness of the quantum network, the efficiency of the execution manager that schedules DQC jobs for execution.

In this context, the intern will be working on a research study regarding the benchmarking of DQC platforms, considering a number of significant metrics. The intern will review the existing literature and try to devise possible extensions of existing benchmarking approaches to the DQC case, but also novel benchmarking approaches specifically designed for DQC systems. The correctness, effectiveness and efficiency of the proposed approaches will be evaluated both theoretically and in simulation. At the end of the internship period, the intern will provide a report describing the research activity carried out, as well as the developed source code.

The ideal candidate is a PhD student with some expertise in quantum algorithms, quantum software development, and Python.

References:

[1] D. Ferrari, S. Carretta, M. Amoretti. A Modular Quantum Compilation Framework for Distributed Quantum Computing, IEEE Transactions on Quantum Engineering, vol. 4, 2023

[2] D. Ferrari, M. Amoretti. A Design Framework for Distributed Quantum Computing Simulation, arXiv:2306.11539, 2023

[3] T. Tomesh et al. SupermarQ: a Scalable Quantum Benchmark Suite, IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2022