Everyone agrees that the first working quantum computer will be a quantum leap into a higher-tech future, and the race to build it has begun. Now researchers at an Australian company, Silicon Quantum Computing (SQC), think they’ve brought us one step closer.
Like regular (classical) computers, quantum computers use transistors to encode information. But, unlike classical computers, the transistor of a quantum computer is on the quantum scale – down to the size of a single atom. While classical computers use bits – zeros and ones – quantum transistors encode quantum information containing zeros, ones, or a combination of zero and one.
Engineers can use the quantum effects of a single-atom transistor to perform calculations. But in the quantum world, things get weird.
Particles are said to exist in a “superposition” of states – their position, momentum and other physical properties are not determined by single values, but are expressed as probabilities. With superpositions, a quantum bit (or “qubit”) can store multidimensional computer data with a much greater complexity than a regular bit.
Therefore, quantum computers are expected to be thousands, even millions of times faster than classical computers, and to perform calculations much more efficiently than even the most powerful classical computers.
They also have other magic tricks up their sleeve.
When superpositions are extended across multiple systems — or atoms — you can have an “entangled state” where one qubit is correlated with another. Changes in one qubit can affect another when they are entangled. This has the potential for unhackable encryption technologies.
That all sounds really cool, but the same quantum effects that make quantum computers such an attractive prospect for physicists and computer scientists make it extremely difficult to produce and turn them into usable machines.
More about quantum computers: First demonstration of universal operations on an error-free quantum computer
Above all, the probabilistic nature of quantum systems means that they are highly prone to error. So a big challenge in making quantum machines is to make them “coherent” to reduce the noise in the signals.
It is this problem that the SQC team believes they have cracked.
Principal investigator and senior author of a Nature paper published today Michelle Simmons spoke to Cosmos about the team’s research.
Building on classical computing architecture, SQC is at the forefront of quantum computing using legacy silicon. Simmons, a physics professor at the University of New South Wales (UNSW), says this allows her team to “map” their place in the context of the history of computer science. The first transistor was invented in 1947, followed by the integrated circuit chip in 1958. Calculators were built on silicon technology in the 1960s, before engineers created the first industrial computers.
“We now want to make a quantum computer,” Simmons says. “The main difference is that we have to make things on an atomic scale. It needs to be much smaller so that we can access the quantum states and have them coherently and quickly.”
Simmons’ team built the world’s first single-atom transistor in 2012, and the first integrated circuit to be built earlier at the atomic scale in 2021. “What we’re looking at is the next device — some sort of commercially relevant algorithm to be solved before we make a computer that people can use. When we started out, we didn’t know what we were going to demonstrate in that circuit.”
The team chose to tackle polyacetylene – a carbon-based molecular chain with chemical formula (C2huh2†n where the n represents a repeating pattern of two hydrogen and two carbon atoms.
Atoms in polyacetylene are bonded by covalent bonds – strong molecular bonds where atoms share electrons in the outer shell. A single bond means that one outer shell electron is shared between the two bonded atoms. A double bond indicates two shared electrons. The alternating single and double bonds between the carbon atoms in the polyacetylene chain make the molecule an interesting study in physical chemistry.
The Su-Schrieffer-Heeger (SSH) model is a well-known theoretical representation of the molecule that records the interactions between the atoms and their electrons and explains the physical and chemical properties of the compound. “It’s a known problem that you can solve with a classic computer,” Simmons says. “There are very few atoms that a classical computer can look at all interactions. But now we’re doing it in a quantum system.”
How did the SQC team model polyacetylene on their quantum device?
“What we do is make sure that the actual processor itself mimics the carbon-carbon single bonds and the carbon-carbon double bonds,” explains Simmons. “We literally designed, with sub-nanometer precision, to try and mimic those bonds in the silicon system. That’s why it’s called a quantum analog simulator.”
Using the atomic transistors in their machine, the researchers simulated the covalent bonds in polyacetylene.
According to the SSH theory, there are two different scenarios in polyacetylene, called “topological states” – “topological” because of their different geometries.
In one state, you can cut the chain at the carbon-carbon single bonds, so you have double bonds at the ends of the chain. In the other, you cut the double bonds, leaving single carbon-carbon bonds at the ends of the chain and isolating the two atoms at both ends because of the greater distance in the single bonds. The two topological states show completely different behavior when an electric current is passed through the molecular chain.
That’s the theory. “When we make the device,” Simmons says, “we see exactly that behavior. So that’s super exciting.”
dr. Charles Hill, senior lecturer in quantum computing at the University of Melbourne, agrees.
“One of the most promising potential applications of quantum technology is to use one quantum system to simulate other quantum systems,” Hill says. “In this work, the authors considered a chain of ten quantum dots and used them to mimic the so-called SSH model.
“This is a remarkable piece of engineering. The quantum devices used for this demonstration are manufactured to nanometer accuracy. This experiment paves the way for emulating larger and more complex quantum systems in the future.”
The advantage of the complex manufacturing process, Simmons says, is that the team “doesn’t make new materials that you have to invent and figure out how to make.”
“We literally have atomic sub-nanometer precision,” she adds. “The atoms themselves are contained in a silicon matrix, so you build a system in a material that has been used in the semiconductor industry.
“There are only two atoms – phosphorus and silicon – in our entire device. So we remove everything else, all the interfaces, the dielectrics, all the things that cause problems in other architectures, and we have just those two atoms. It’s conceptually simple, but obviously challenging to make. It’s a nice, clean, physical, scalable system.
“The challenges were how do you put an atom in its place, and how do you know it’s there? It literally took us ten years to understand the chemistry to get phosphorus atoms into a silicon matrix so that it is protected. (One of) the technologies we used was a scanning tunneling microscope (STM), a lithography tool.”
After the team placed a silicon plate in a vacuum, the team first heats the substrate to 1,100°C, before gradually cooling it to about 350°C, creating a flat two-dimensional silicon surface. The silicon is then covered with hydrogen atoms, which can be selectively removed individually using the STM tip. Phosphorus atoms are placed in the newly formed holes in the hydrogen layer, before being covered with a new layer of silicon.
“It means we’re making one device at a time,” admits Simmons. “But my analogy is that it’s like a Swiss watch. It is very precise and handmade. My view is that you need that precision to create a scalable system. It’s very hard to build a qubit state if you don’t have precision because you don’t know what you have. So our view is, yes, it’s slower, but you know what you’ve got.”
Once the device is manufactured, Simmons says their choice of algorithm to test it is historically significant.
“The simulation algorithm is Richard Feynman’s dream from the 1950s,” explains Simmons. “If you want to understand how nature works, you have to build it on that length scale. Can we mimic the single and double bonds of the carbon molecule with this kind of precision down to the nanometer?
“Instead of using a single atom to mimic the carbon atom, we found that we use 25 phosphorus atoms.”
The team found that they could control the flow of electrons along the chain.
“So you have individual and local control and comprehensive control,” Simmons says. “We have shown that we can do this with just six electrodes for a 10-point chain. So much less electrodes than the actual number of dots. And that’s great for scaling. Because in a quantum computer you basically want to have that lower number of ports compared to the active elements, otherwise it scales badly.”
Not only does their device match SSH theory, Simmons believes that quantum computers will soon begin to simulate problems beyond even our best theories.
“It opens a door to the kinds of things we could never have imagined before. It’s terrifying and exciting at the same time,” she says.
The device has similar drawbacks to other quantum computers – most notably the expensive and energy-intensive need for huge refrigerators to keep operating temperatures exceedingly low, approaching absolute zero.
For commercial confidentiality, Simmons keeps quiet about the projects the SQC is tackling after this initial demonstration. But she does say, “We want to apply it to as many different things as possible and see what we can discover.”
“The fact that we can get the electrons coherent throughout the chain tells us that this is a very quantum coherent system,” she says. “It gives me confidence that the physical system we use is really stable.
“It’s a demonstration of the purity of the system. There are many different ways we can go now. Creating larger physical systems is certainly one. Looking at the spin state rather than the charge states is another.”
Simmons describes this kind of research as ‘a journey’. She especially appreciates its interdisciplinary nature, with all the quantum physicists, chemists, engineers and software engineers involved.
“For young people, this is such an exciting field to be in,” she says. “It’s the evolution of a basic research project into something practically useful.”
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