Quantum computing: Quantum architectures and applications
In the near future, quantum computers are expected to significantly reduce the computational complexity of several crucial applications. With a view to explore and propose near-term solutions, the group's research focuses on two main streams, intended to work in junction: the development of classical emulators and the formulation of new algorithms.
For the former, CPU and GPU applications are under investigation to approximate the behavior of quantum machines, together with innovative digital architectures for FPGAs. The derived systems can overcome the limitations of currently available hardware (i.e., the influence of non-ideal phenomena, reduced processing capabilities, and high access and operating costs), and can be exploited as on-premise platforms, more affordable than real quantum devices but sufficiently performing to test and prototype quantum computing applications.
For the latter, the formalism of quantum computing is adopted to find a computational advantage for several hard problems. In particular, application-specific Quadratic Unconstrained Binary Optimization (QUBO) models are developed, along with new approaches for Quantum Machine Learning and Quantum Image Processing. The definition of such algorithms follows the entire application chain, from encoding the input information to the final execution on the target machine (quantum or quantum-inspired).
- PE7_3 Simulation engineering and modelling
- PE7_4 (Micro and nano) systems engineering
- PE7_5 (Micro and nano) electronic, optoelectronic and photonic components
- Quantum computing
- Quantum Optimisation
- Quantum Machine Learning
- Quantum Emulation