NCI Presents: TechTake is an exciting opportunity for international computational and data science leaders to discuss and demonstrate how technology supports research.
Taking place on the last Tuesday of each month, this event will run online in order to reach diverse audiences across the globe and from all fields.
TechTake is designed to prompt engaging and in-depth conversations about both the current state and potential futures of technology to broaden and deepen understanding.
Dr Benjamin Joecker, UNSW
As a researcher in Professor Andrea Morello's group, Benjamin and his UNSW peers are setting out to design and build a large-scale quantum computer, a device that uses quantum mechanics to solve otherwise intractable computational problems. The group was the first to demonstrate a qubit, the smallest building block of a quantum computer, in silicon, which paved the way for CMOS foundry compatible approaches pursued today.
Efficient models for the design of a donor-based quantum computer in silicon
Last year, the tech giant Google has made headlines by showing that a quantum computer can solve a problem intractable for even the fastest supercomputers. Research in Australia today is focused on qubits, the smallest building block of a quantum computer, in silicon to pave the way for a foundry compatible approach. While silicon is the preferred material for scaling, its crystal structure plays a crucial role for the processor layout. A successful design requires a good understanding of the system and accurate models.
Simulating quantum systems is a formidable task, one of the reasons Richard Feynmann originally saw the need to build a quantum computer. Many approaches are computationally heavy and are unfit to produce the large data sets needed to find optimal qubit configurations, while others have relied on unjustified approximations. In this talk, I will show that our multi-valley effective mass theory can efficiently model donor-based qubits in silicon with high accuracy. Full configuration interaction simulations on a compact but precise basis set allowed us to show the scalability of this qubit implementation and provide invaluable data for future chip designs.