Research Projects – To Be Delete

This project is part of the CSIRO Next Generation Quantum Graduates Scholarship Program (NGQGP). Diraq is a Sydney-based quantum computing company, delivering revolutionary quantum computing to the world, based on existing silicon chip technology. This immersive PhD project at Diraq provides students with hands-on experience in silicon MOS based quantum computing. Under expert guidance, participants contribute to cutting-edge projects, receive tailored mentorship, and engage in specialised training, enriching both their academic journey and industry prospects. 

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.

Hybrid Quantum Systems attempt to harness the complementary strengths of several distinct quantum technologies, including light, sound, excitonic and electronic systems, to perform different tasks in a complex architecture of a quantum computer. For example, the computations would be implemented using atomic systems or superconducting circuits, and their results carried between distant computational modes using light. Acoustic resonators would serve to interface, or transduce the quantum information between the computational and communication systems. Such systems are likely to offer a shortcut towards practical large-scale quantum computing.