Quantum Computing and Optimiziation
This project focuses on implementing and benchmarking quantum algorithms for solving large-scale optimization and linear algebra problems arising in applications such as artificial intelligence and machine learning. These tasks require substantial computational resources to simulate quantum circuits, evaluate performance across different problem instances, and compare quantum-inspired methods with state-of-the-art classical algorithms. Access to the university’s HPC cluster will enable efficient execution of quantum circuit simulations, large-dimensional linear algebra routines, and optimization benchmarks, supporting the development and evaluation of scalable quantum algorithms for real-world applications.