Introduction

Prasanna Pakkiam says...‘There are varying degrees of what defines a quantum computing device

 

An interview with PhD student Prasanna Pakkiam, the lead author of a recent report on research conducted at the CQC2T in Australia.

  • Client

    Prasanna Pakkiam

  • Services

    To develop a compact qubit sensor using single-gate RF readout.

  • Technologies

    Quantum Computing

  • Dates

    04/01/2019

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Description

What exactly is the quantum computing and how does it differ from conventional computing?

 

The difference is in the representation of information and the subsequent operations one may perform. In a classical computer, whether it is in binary arithmetic or just branching logic, the representation is ultimately the 'bit' which is a Boolean value (e.g., true/false, 0/1, 0V/5V etc.). In quantum computing the information is represented by a 'qubit' which is a two-state quantum system. The foundations of quantum mechanics dictate that when moving between these states, one can enter 'superpositions' where for example it can be effectively in both states at once. The real power comes when taking multiple qubits and 'entangling' them together. Operations on a particular qubit entangled to many other qubits will also affect the state of the other qubits. The idea is the algorithms are setup such that the algorithm forces the entangled qubits into the state that contains the answer (to an algorithm) we wish to measure in a way that's similar to the constructive/destructive interference used in classical wave mechanics (like in noise cancelling headphones). In other words, a quantum computer exploits the fundamental wave-like quantum nature of our universe – effects that scramble when observed from the macroscopic viewpoint of humans and subsequently not exploited by classical computers.

 

 

How complex is this task and what is the kind of research and resources deployed?

The qubit in our research is mapped onto two electrons held across two quantum dots made of phosphorus atoms. The challenge is that if this electron interacts with anything from the outside world, it will entangle with that particle and subsequently 'quantum information' (or coherence) is lost. We ensure that the electron does not have a chance to interact with anything other than the phosphorus atoms by precisely placing the phosphorus atoms in a silicon crystal using STM (scanning-tunnelling-microscope) lithography. In addition, to ensure that thermal fluctuations (or phonons) don't affect our electron qubit, we cool our samples down to ~20-100mK temperatures via a dilution refrigerator. Finally, with the electrons sufficiently isolated, we control and read the qubit states via well-timed voltage and microwave pulses created by state of the art off the shelf and custom hardware stacks.

 

This latest breakthrough that uses a compact sensor for accessing information stored in electrons of individual atoms – how significant it is?

It is an important milestone for electron qubits hosted on solid-state quantum dots. It has been known for years that such a compact single-gate sensor could be useful, but it was generally dismissed in architectures as it was thought that the sensitivity was not enough for a large scalable quantum computer. The results of this research now place this sensor on the table as a viable candidate in a quantum computing architecture built with quantum dots.

 

How far is the world from the first ever quantum computing device?

There are varying degrees of what defines a 'quantum computing device'. Many systems have already shown individual qubits and many qubit gates. There are few-qubit systems that have been shown to solve some simple quantum simulation problems (albeit answers that can be found using a large enough classical computing cluster). However, for a general purpose quantum computer that can solve certain classes of problems inaccessible to current classical computers (such as those in chemical and materials engineering), requires many qubits. We want high quality qubits that have low errors. Similar to classical computing, one employs error correction algorithms that make use of redundant physical qubits to create effective low-error 'logical qubits'. Current state-of-the-art error correction algorithms are still in their infancy and there is a lot of research still needed before we get there.  

 

What is your role in this project? How do you feel being associated with such an important mission?

I am a researcher who contributes to a certain research stream. As with any R&D, the duty at hand is to evaluate the feasibility of the approach proposed by the node and develop it a point where it can be readily integrated into the overall system. In this case, the node was tasked to develop a compact qubit sensor using single-gate RF readout. How I feel is not important as objectivity must be retained when making the evaluations, for future nodes will spawn from the results and conclusions of the current nodes. Nonetheless, I do feel satisfaction that the results presented here are applicable to not only our particular qubit system, but to all solid-state quantum dot implementations.

 

We understand this will be a game changer. Can you give us some idea of the impact with some examples?

The results here simply validate the single-gate RF readout sensor as a viable qubit sensor. The direct impact will be that scalability constraints can be possibly alleviated when moving to many qubit systems in solid state quantum dots. Conventional qubit sensors in solid-state quantum dots typically require three wires per qubit. These wires must be routed to qubits which must be typically separated by 10-100nm. It becomes a challenge when one realises that there must be mandatory control lines also routed to the individual qubits. Being able to make single gates serve dual roles in both control and readout can help reduce the wire density in a system where there is very little space real estate. The real impact will be seen by the adoption of this sensor enabling the creation more complex many-qubit systems using solid state quantum dots in the coming years.

Born in Madurai in 1990, Prasanna Pakkiam moved to Auckland during late Primary school, and later to Melbourne for undergraduate studies – BE (Hons) in ECSE (electrical and computer systems engineering) and BSc (Hons) in Physics and Pure Mathematics. He is presently in Sydney for his PhD.

 

Quantum Computing: Crossing Another Hurdle

A group led by Australian of the Year, Professor Michelle Simmons, has overcome another critical technical hurdle for building a silicon-based quantum computer. Professor Michelle Simmons’ team at UNSW Sydney has demonstrated a compact sensor for accessing information stored in the electrons of individual atoms – a breakthrough that brings us one step closer to scalable quantum computing in silicon.

 

The research, conducted within the Simmons group at the Centre of Excellence for Quantum Computation and Communication Technology (CQC2T) with PhD student Prasanna Pakkiam as lead author, was published recently in the prestigious journal Physical Review X (PRX).

 

“Not only is our system more compact, but by integrating a superconducting circuit attached to the gate we now have the sensitivity to determine the quantum state of the qubit by measuring whether an electron moves between two neighbouring atoms,” says lead author Pakkiam.

 

Caption:

The authors of the paper (L-R): PhD student Mark R Hogg; Prof Michelle Simmons; Post Doc Matthew G House; PhD student Prasanna Pakkiam; and Post Doc Andrey Timofeev.

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