This Master’s thesis investigates the utilization of the XACC framework in combination with Message-Passing-Interface (MPI) principles in an attempt to accelerate the Quantum Approximate Optimization Algorithm (QAOA) in hybrid quantum computing architectures. QAOA has emerged as a promising approach for solving optimization problems by combining classical and quantum resources. However, as the scale and complexity of these problems increase, the computational demands of QAOA become significant. This research aims to explore how MPI, can enhance the performance and scalability of QAOA. To achieve this objective, a framework is developed that leverages the XACC infrastructure to distribute workloads, execute QAOA computations on different (quantum) backends, and collect and analyze the results. This comprehensive literature review is conducted to analyze the state-of-the-art methodologies, challenges, and potential opportunities in the integration of QAOA and MPI into XACC. The paper encompasses studies on QAOA, hybrid quantum computing architectures, and the capabilities of XACC. By building upon the existing body of knowledge, this research aims to provide insights into the benefits and limitations of utilizing MPI in the context of QAOA in hybrid quantum computing architectures by providing an empirically tested hybrid quantum algorithm. The outcomes of this research are expected to contribute to understanding the performance and scalability improvements that can be achieved by leveraging MPI in QAOA computations. The evaluation of the effectiveness of distributing classical QAOA workloads and analyzing the results will provide valuable insights into the potential of MPI in accelerating QAOA computations. The findings will also shed light on the suitability of QAOA in solving larger and more complex optimization problems in practical applications. Overall, this paper aims to explore the integration of MPI and QAOA through XACC, providing a deeper understanding of the benefits and limitations of utilizing MPI as a tool to enhance the performance and scalability of QAOA in hybrid quantum computing architectures.     «

This Master’s thesis investigates the utilization of the XACC framework in combination with Message-Passing-Interface (MPI) principles in an attempt to accelerate the Quantum Approximate Optimization Algorithm (QAOA) in hybrid quantum computing architectures. QAOA has emerged as a promising approach for solving optimization problems by combining classical and quantum resources. However, as the scale and complexity of these problems increase, the computational demands of QAOA become significant....     »