Quantum information processing in large-scale photonic networks

This thesis focuses on optical quantum information processing in two parts. The first part focuses on photonic hardware. Large-scale photonic experiments require the generation of many indistinguishable single photons simultaneously. Traditionally, such photons are generated by spontaneous parametric down-conversion (SPDC). However, the suitability of such sources to generate many photons. We have identified the maximum limits of how many photons SPDC sources can be made. A second requirement of large-scale quantum photonics is having a network with many optical modes while maintaining low optical loss. Such networks are currently lacking. Therefore we introduce the possibility to use a rough surface scatterer for a quantum advantage experiment. Although such a network is far from universal, it has many modes and low loss. Another approach is to use integrated quantum photonics, which is fully reconfigurable and is a promising way of scaling up to large systems in an industrial setting. We have characterized a programmable low-loss 12-mode silicon nitride (SiN).

In the second part of the thesis, various proof-of-principle quantum experiments were performed on a 12 mode SiN integrated photonic chip. Firstly, it was shown that these networks can be used to simulate wave propagation through disordered networks. This unconventional approach allows for full experimental access and control to the physical process, which is essential for such experiments. Secondly, we introduced a semi-device independent witness protocol that can in-situ verify the indistinguishability of photons on the chip, which is an essential tool to have when the system size increases and can no longer be efficiently simulated classically. The last experiment is a quantum simulation where we show how a pure quantum state locally thermalizes in a closed system.