The next big breakthrough in quantum computing could come from Australia

There may be ongoing debate in some circles about when quantum computing will become a viable enterprise solution, but this matters little to the growing number of providers who are offering early commercial and pilot quantum solutions in a market that is already demonstrating strong demand.

Successes from laboratories around the world in areas such as materials simulation, optimization, early-stage quantum-enhanced machine learning and quantum twins are beginning to offer a tease at opportunities for competitive advantage and operational efficiency.

For leaders, it is time to move beyond a wait-and-see approach and evaluate how quantum computing could play a role in their operations.

A quantum computer leader is taking shape

By 2026, no single economy yet has a monopoly on quantum computing technology, but the global race to dominate and lead is clearly underway. While the US and China are leading the way with massive investment and progress, others including the UK, Germany and Canada are emerging as leaders.

Notably, after more than 25 years of steady focus and investment, Australia emerging as quantum computing star among this specific group of economies. Apart from setting quantum research and development as a national strategy, the country has built a healthy startup ecosystem and generated a pipeline of impressive quantum physicists and engineers.

Australia’s efforts are a model ARC Center for Quantum Computation and Communication TechnologyA multi-university network headquartered at the University of New South Wales (UNSW) in Sydney, Australia and established in 2011.

The organization’s focus is primarily on transforming quantum physics into usable computing, with a particular interest in silicon-based approaches rather than other methods, including photonics and trapped ions.

In 2017, after several technological breakthroughs and with seed funding of $82.4M, the center spun off a unit, silicon quantum computing (SQC), to commercialize their research into real, enterprise-ready solutions.

Australia’s quantum bet is starting to bear fruit

At the helm of both the ARC Center and SQC is Professor Michelle Simmons, who was named Australian of the Year in 2018, one of the country’s premier awards. His technical background and achievements are notable. He is a pioneer in the creation of atomic-scale electronic devices, including the world’s smallest transistor and the first two qubit gates using atom-based qubits in silicon.

While continuing her work as a professor and researcher, she now finds herself as the CEO and founder of a rapidly growing quantum computing provider.

As a result of their primary research focus and that of the ARC Center, SQC’s solutions are based on qubits – the basic units of quantum information – derived from phosphorus atoms embedded in pure silicon. Simmons believes that many of the technical results of this silicon-based approach, such as coherence, neutral atoms, superconducting metals, and photons, are superior to other alternatives.

According to Simons, SQC is growing faster than other quantum providers because they decided from the beginning to become a quantum processor unit (QPU) manufacturer rather than outsourcing the manufacturing of their hardware needs. If they go the third-party route, it could take up to 40 weeks to manufacture their semiconductors. It may take a week to do it yourself.

Mastering the manufacturing process means SQC can meet their high precision and accuracy needs and move forward much faster. In fact, they are consistently able to exceed their own delivery targets. They were targeting 2028 for their first commercial product, but they were ready and shipping in 2025.

The race for fault-tolerant quantum computing

Simons’ bigger goal is to build a completely error-corrected quantum computer. It is a system that uses incomplete qubits to create stable logical qubits that can process long, reliable calculations. This is no mean goal. Today, the difficulty in managing errors is a central problem that continues to hinder quantum computing progress.

Improved error correction increases the number of reliable logical qubits that can be deployed resulting in faster calculations. Today, Canada’s D-Wave has deployed approximately 5,000 qubits using quantum annealing approaches optimized for specific problems, while IBM’s 1121-qubit Condor processor represents a general-purpose gate-based system.

SQC has identified 2033 as the year they will support one million qubits. If they reach that goal, the computational capabilities will be staggering and will enable quantum computing to provide enterprise solutions ranging from materials discovery to large-scale industrial optimization. Simmons doesn’t believe it’s a pipe dream; Furthermore, his current rate of recurrence tells him that this is achievable.

Today, SQC distributes a commercially available QPU called Watermelon. It uses quantum reservoir computing, a Japanese innovation, which can be considered a shortcut to useful quantum machine learning. Watermelon’s quantum processing capabilities are available through a physical unit that customers can house in their datacenter or alternatively, quantum services can be accessed via the cloud.

As a related example of Watermelon’s features, instead of increasing the number of GPUs in a datacenter to accelerate AI training, some processing can be offloaded to Watermelon’s CPUs which can provide speed and efficiency benefits. For a recent telecommunications customer, Watermelon was able to reduce the time to process a typical AI training set from several weeks to a few days.

From digital twins to quantum twins

SQC’s next product, which is currently being tested with a small group of potential customers, is their quantum twins. Simons says his work is inspired by Richard Feynman Lectures from 1959 Where he said that you cannot understand the world unless you can create it on a similar scale.

Quantum twins address one main limitation: classical systems struggle to simulate complex quantum interactions as the size of the system increases, especially for complex molecular systems. There exists no limit to how complex structures can be simulated at the atomic scale using quantum computing. The quantum twin will be able to discover fundamental states of matter and help answer questions about a wide range of unknowns in the world of physics and chemistry.

One promising area for quantum twins is drug discovery. While there have been advances in simulation, pharmaceuticals still rely heavily on a trial-and-error process. A new drug must be tested and the results measured and not only does this take a long time, but how the molecules behave and interact with each other and within the human body is often not well understood. Using a quantum twin, researchers can model, simulate, observe, and measure the precise behavior that occurs when molecules interact. It has the potential to change the world of medicine.

A quantum computing roadmap

Simons and his team are rapidly learning what is needed to commercialize quantum computing products. He has found that allowing potential buyers to experience and implement his solutions is the best teacher. This helps the customer understand what is possible and provides real-time feedback to SQC to develop their solutions.

They also discovered that teaching potential customers the intricacies of quantum computing could be a showstopper. They are increasingly learning that better adoption occurs when complexity is hidden behind the scenes and the user is provided with a simpler, more intuitive interface. It is a prediction of a future where many people will use quantum computing capabilities without actually realizing it.

Simmons shares that he has a motto at SQC keep it real. They avoid hyperbole and focus on providing actual, real-world use. This is serving to increase customers’ interest in Watermelon CPUs and cloud services. To meet demand, they are currently building a new, expanded manufacturing facility and hiring several new employees.

Simmons and SQC are today delivering what many thought would take years to achieve. This may be the clearest evidence yet for leaders to start accelerating their quantum computing efforts.