Quantum Research Opportunities

High precision measurements in quantum optics and atomic physics rely on the fine control of the experimental parameters and require the locking stabilisation of the frequency of the transmitted signal. This project entails the design, development and characterization of a loop-back control system and digital controller for laser frequency stabilization. The hardware will be based on a RedPitaya STEMlab platform and will be used to lock the laser emission frequency to the cavity resonance of reference and spectral peak maximum for Doppler-free absorption spectroscopy experiments with Rubidium. The student will employ machine learning methods for analysis and optimisation of the interfacing and acquisition of the emission spectra for atomic vapor saturated absorption spectroscopy experiments.

This project is part of our exciting new ARC-funded research grant, where we aim to enhance high-tech quantum simulators to meet the demands of computer-modelling intensive industries such as drug and vaccine design. By developing innovative digitisation and control techniques for simulating the behaviour of complex quantum systems, a task that is generally impossible to solve with classical computing technology, this project aims to help shape the design of future quantum computers and maximise the modelling power of current industry-scale processors built by companies like Google, IBM and Australian start-up, Silicon Quantum Computing.

Quantum simulators aim to describe the properties of quantum systems that would otherwise be too difficult to simulate on ordinary computers. In particular, analog quantum simulators—which do not require universal, programmable quantum computers—are likely to be the first practical quantum computing devices.

Our goal is to simulate the outcomes of chemical reactions that are beyond the capabilities of conventional computers, which would have transformative impacts from materials and energy science to drug discovery.

Graphene, a single layer of carbon atoms with honeycomb lattice structure, shows many exotic physics and promising properties for device applications. Stacking different layers together provides a degree of freedom to change electronic properties of graphene, such as electronic band structures. In this project, the successful applicant will work with a team from QED group from School of Phyiscs at UNSW to explore effect of different stacking order on electronic properties of ABA- and ABC- stacked trilayer graphene. The successful applicant will participate in fabrication of van der Waals heterostructure and measuring their electronic properties in an environment of ultracold temperatures and high magnetic fields.

Complex light fields used in optical tweezers require advanced optical manipulation and control of the laser beam. The project focusses on the design, experimental setup and characterization of a beam auto-aligner system on a Raspberry Pi controlled stepper motor. The system will be used for maintaining and manipulating the intensity distribution of the laser beam and precise optical beamshaping by a spatial light modulator patterned optical trap for cold atoms. The work involves developing a machine learning algorithm for optimization of the “walking the beam” technique, used in most quantum optics experiments and control of structured light for advanced optical manipulation. The algorithm can be used to optimize the laser power into optical fibers, better modulation of the amplitude and phase of light and for controlling of the overlapping beams in a pump-probe experimental setup. The precise control of the laser beam intensity distribution enables the fine tuning of configurable potential wells for future optimized optical trapping experiments.