Ivan Tsitsilin

Offered Bachelor’s or Master’s Theses Topics

Design and Operation of a Multi-Input Quantum Perceptron

Quantum machine learning is a new area of research at the interface of classical machine learning and quantum computing. Advantages arising from the quantum implementation of a neural network are still unclear but an implementation and training of a small scale quantum network could shed some light on its usefulness. You will start by understanding the principle of adiabatic ramp neurons as implemented with superconducting qubits. You will then investigate possible implementation of a network using 2-3 multi-input neurons and design a training experiment to perform on such a device. This will involve the design and characterization of a multi-qubit chip device including numerical simulations that is optimized for multi-input version of the neuron. Ideally, you will measure the non-linear activation function of a quantum perceptron depending on the weights set by the ZZ coupling to the input neurons and train the network to classify quantum or classical input data.

suitable as

• Master’s Thesis Condensed Matter Physics

Supervisor: Stefan Filipp

Investigation of many-body couplers for superconducting qubits

High connectivity between qubits can lead to significant advantages when compiling quantum algorithm on real hardware. For example, in trapped ion quantum computing architectures multi-qubit entanglement is mediated by shared oscillator modes, allowing for all-to-all connectivity and long range interactions. In this project we aim to explore the coupling of multiple superconducting quantum circuits (qubits or resonators) via a shared coupling element. We investigate simultaneous couplings between multiple superconducting circuit elements by controlling the interaction strength and interaction time. The ideal outcome of this project is the demonstration of useful quantum operations, such as joint measurements, qubit reset or quantum operations on multiple qubits.

suitable as

• Master’s Thesis Condensed Matter Physics

Supervisor: Stefan Filipp