Hamilton Institute Seminar

Wednesday, May 4, 2022 - 13:00 to 14:00
Zoom & In-person

https://us02web.zoom.us/j/88018185733?pwd=OEcxb2ZSYUwzV2hWTE9wcE1yTWRUQT09
Passcode: 279596

In-person: Hamilton Institute Seminar room (317), 3rd Floor Eolas Building, North Campus, Maynooth University

Speaker: Dr Niall Murphy, Equal1 Labs

Title: "Noisy, Broad & Short: quantum computing at 3.5K"

Abstract: First suggested in the 1980s, quantum computers have finally arrived.  They promise to extend our computing power beyond what is possible with classical silicon computers.  However, they are notoriously difficult to build and scale.  To minimize errors most must be kept at close to 0K with classical control systems at some distance at warmer temperatures.

Equal1 is an Irish/US quantum computing company that uses commercial CMOS processes to make a new type of quantum computer.  The qubits are on the same silicon chip as the classical components for qubit control.  Current prototypes run at 3.5K (very hot), which means our qubits have a short coherence time.  However, having the control logic beside the qubits allows for extremely fast feedback loops between classical and quantum chip components, allowing for quantum operations to occur within coherence time.

Another advantage of using standard CMOS technology is that it is very easy to scale up to millions of qubits. What can we do with wide but shallow quantum circuits?  We will have a look at how Equal1's unique quantum dot structure can be used to implement a quantum machine learning algorithm known as VQE (Variational Quantum Eigensolver), with applications in quantum chemistry.

Bio: Niall Murphy is a computer scientist at Equal1 Labs, an Irish/US start-up that is building scalable silicon quantum computers. His BSc and PhD in Computer Science are from Maynooth University, where he focused on computational complexity theory. Niall has been a researcher in UPM Spain, Microsoft Research Cambridge and the Sainsbury Lab at the University of Cambridge where he worked with amazing colleagues to explore the role of stochastic gene expression in both bacterial pattern formation, synthetic biology, and its applications in cellular computation.  Recently Niall has focused on developing practical applications for near term quantum computers.