Investigating the Relationship between Entanglement and Fourier Coefficients in Quantum Machine Learning

• Type: Bachelor-/Master thesis
• State: open
• Supervisor: Maja Franz
• Student: No Name

The field of quantum machine learning produced numerous theoretical and empirical insights in recent years. As shown in recent work such a "quantum machine learning model" can be represented by a truncated Fourier series, opening up new possibilities for analysis. This thesis aims to investigate the relationship between the correlation of the Fourier coefficients and the fundamental quantum property of entanglement.

Activities

• Familiarisation with quantum computing, focusing on quantum Fourier (machine learning) models and entanglement.
• Implementation of (existing) entanglement measures using Python.
• Experimental setup of numerical simulations of quantum computing.
• Contributions to our open-source QML-essentials framework.

Requirements

• Interest and basic knowledge in the field of quantum computing.
• Enrolment in a computer science or related discipline
• Easy and regular availability.
• Long-term collaboration is desired.
• Optional: Basic knowledge of Python frameworks for quantum computing (Pennylane, Qiskit, ...).

We Offer

• Flexibility regarding the scope and focus of the thesis.
• Personal familiarisation with quantum information science.
• Insight into the processes and workflows of quantum computing.
• Work in an open and supportive team.

If you are interested or have further questions just write an email to maja.franz (at) oth-regensburg.de