NV centers in diamond are considered a promising platform for the development of end nodes in the Quantum Internet framework. Thanks to the optical addressability of the NV electronic spin, it can be used as a qubit to perform quantum information processing. On top of that, the electronic spin is surrounded by many carbon spins that can be addressed individually [1], forming a so-called quantum register. This enables the possibility of performing advanced protocols on large-scale quantum networks, such as quantum error correction, entanglement distillation and blind quantum computation.

The project investigates whether Machine Learning techniques can optimize the detection [2] and control of nuclear spins for quantum network applications. Basic knowledge of coding and AI is required, as well as interest in the underlying physics of such platforms.

We also have other project opportunities within the Hanson-Taminiau Networks team, for any inquiries send an email to M.iuliano[at]tudelft.nl

[1] C. E. Bradley et al., A Ten-Qubit Solid-State Spin Register with Quantum Memory up to One Minute, Phys. Rev. X 9, 2019

[2] K. Jung et al., Deep learning enhanced individual nuclear-spin detection, npj Quantum Information 7, 2021

Requirements

• Physics background
• Coding and AI experience