AbstractThe extraordinary success of quantum mechanics and its formalism has been established thanks to countless experiments with microscopic systems. Nevertheless, it is still not clear whether and when the quantum world ends, allowing for the emergence of classical phenomena. The extension of quantum properties to macroscopic system gives rise to paradoxes, as the well-known Schrödinger’s cat example. Among the alternatives to quantum mechanics, collapse models propose an objective modification of standard quantum theory to restore macrorealism at large scale. They predict a loss of coherence when scaling towards macroscopic systems, due to a spontaneous collapse mechanism included into the dynamics through non-linear stochastic modifications of the Schrödinger equation. Assessing and characterizing these models is a noteworthy endeavour in the exploration of the quantum-to-classical transition.
The overarching goal of this Thesis is to address some of these fundamental issues, by exploring the concept of macrorealism and probing collapse models, making use of optomechanical setups.
To answer the question whether a system has a quantum or classical dynamics, we will propose a theoretical test of Leggett-Garg inequalities, as tool to probe the macrorealism of an optomechanical system.
We will investigate collapse models through the study of the dynamics of an optomechanical cavity, looking for signatures in the noise spectrum. Further, we will use the hypothesis testing framework and quantum metrology tools to distinguish dynamical channels encoding the presence or the lack of the collapse.
Our findings show a violation of Leggett-Garg inequalities, suggesting that the demarcation line of the quantum domain can be pushed further to include larger systems. Our approaches for testing collapse models provide novel methodologies to better discriminate these effects and the results represent another step forward in the attempt of gaining a better understanding of the foundations of physics.
Thesis embargoed until 31 July 2023.
|Date of Award||Jul 2022|
|Sponsors||EU H2020 FET Project TEQ|
|Supervisor||Mauro Paternostro (Supervisor) & Alessandro Ferraro (Supervisor)|
- collapse models
- hypothesis testing