Abstract
A significant amount of research is currently devoted to quantum technologies, i.e., technologies that harness the complex features of quantum systems for practical purposes. Remarkably, these have the potential to shape the way we will live in the future by, for example, providing new ways of breaking the current cryptographic security measures or by exponentially enhancing the computational capability of computers. This, in turn, could serve as a means for studying phenomena so complex that they render classical computers completely unusable.With these promises at hand, methods that efficiently certify the correct functioning of quantum devices and computations become of paramount importance. Specifically, it is often required to assess a characterization of the quantum states that come out from a specific computation or experiment. The traditional method of quantum state tomography relies on a rather straightforward but brute-force approach to reconstruct the full density matrix that encodes a quantum state. This method is highly demanding because of the curse of dimensionality, according to which the number of required measurements scales with the system’s dimension, and thus exponentially with the number of qubits. As the quantum protocols demand a progressively higher number of qubits, overall, a complete characterization of quantum states through tomography loses its effectiveness, thus calling for a partial but simpler reconstruction of states.
Furthermore, an additional obstacle must be taken into account. In particular, the same complex features of the quantum realm that would help to navigate through the sea of potential applications hinder a growth of the current technological state of the art, which indeed is limited within the so-called NISQ (Noisy Intermediate-Scale Quantum) devices. These, as the name suggests, are characterized by inevitable noises and imperfections, and as such are not advanced enough for achieving a real quantum advantage in the near term.
In this Thesis we are going to discuss new techniques for the estimation of properties of unknown quantum states in the context of quantum information science. The protocols that we will present are flexible enough to not only include state tomography within them, but to also adapt to noises and imperfections present in the computational devices.
Date of Award | Dec 2024 |
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Original language | English |
Awarding Institution |
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Sponsors | CITI-GENS, Horizon 2020 |
Supervisor | Alessandro Ferraro (Supervisor) & Mauro Paternostro (Supervisor) |
Keywords
- quantum information
- machine learning
- Quantum technologies