Quantum computing is a type of computing that harnesses the principles of quantum mechanics to process information in fundamentally different ways from the laptops and servers we use today. While classical computers have driven extraordinary progress over the past seven decades, they are hitting physical limits. Quantum computers are being developed to tackle problems that would take a classical machine longer than the age of the universe to solve. Understanding what that means, and why it matters, starts with grasping a few key ideas from physics.
The basics: bits versus qubits
Every classical computer stores and processes information as bits. A bit is either a 0 or a 1, a switch that is either off or on. Everything your phone or laptop does, from streaming video to sending an email, is ultimately a vast sequence of those binary choices.
A quantum computer uses qubits instead. A qubit can exist in a state of 0, 1, or both at the same time. This property is called superposition. Think of a classical bit as a coin lying flat: it is either heads or tails. A qubit is like a coin spinning in the air: it is effectively heads and tails simultaneously until you look at it, at which point it lands on one side.
Superposition alone is powerful, but quantum computers also rely on a second property called entanglement. When two qubits become entangled, the state of one instantly influences the state of the other, regardless of the physical distance between them. A change in one is reflected in the other instantaneously. Einstein famously called this "spooky action at a distance," and it is a core ingredient in how quantum systems process information so rapidly.
A third property, interference, lets quantum computers amplify paths that lead to correct answers and cancel out paths that lead to wrong ones, a bit like noise-cancelling headphones for bad solutions.
Why it's so much faster for certain problems
With superposition, a quantum computer with just 300 qubits can represent more states simultaneously than there are atoms in the observable universe. This does not mean quantum computers are faster at everything. They are not. For straightforward tasks like word processing or browsing the web, a classical computer is perfectly adequate and will remain so.
Where quantum computers shine is in problems involving enormous numbers of possible combinations: breaking down large numbers into their prime factors (which underlies most modern encryption), simulating how molecules behave at an atomic level (critical for drug discovery), optimising complex logistics networks, and training certain types of machine learning models. For these specific categories, a sufficiently powerful quantum computer could accomplish in seconds what a classical supercomputer could not finish in a human lifetime.
This potential has significant implications for fields like medicine, materials science, finance, and cybersecurity. If you are curious about how cybersecurity already grapples with threats from emerging computing power, our explainer on what cybersecurity is and why it matters gives useful grounding on the defensive side of this equation.
How a quantum computer is actually built
Building a quantum computer is extraordinarily difficult because qubits are extremely fragile. Any interaction with the outside environment, a stray vibration, a fluctuation in temperature, even a passing photon, can disrupt the quantum state in a process called decoherence. When decoherence occurs, the qubit collapses to a classical 0 or 1 and loses its quantum advantage.
To prevent decoherence, most quantum computers operate at temperatures near absolute zero, colder than outer space. The hardware often looks more like a complex chandelier of gold-plated wiring and dilution refrigerators than anything resembling a conventional computer.
Several different approaches to building qubits exist. Superconducting qubits, used by companies like IBM and Google, run electrical currents without resistance at ultra-low temperatures. Trapped-ion qubits use individual charged atoms suspended in electromagnetic fields. Photonic systems use particles of light. Each approach has trade-offs in stability, error rates, and scalability.
One of the biggest engineering challenges is quantum error correction. Because qubits are so error-prone, many physical qubits must work together to produce a single reliable "logical" qubit. Current machines have hundreds to thousands of physical qubits, but the number of reliable logical qubits they can produce remains far smaller. Reaching fault-tolerant quantum computing at scale is the defining challenge of the field right now.
Where things stand in 2026
Quantum computing has moved rapidly from theoretical physics to working prototypes, but the technology remains in what researchers call the "noisy intermediate-scale quantum" (NISQ) era. Machines today are powerful enough to demonstrate quantum advantages on narrow, carefully chosen problems, but not yet capable of replacing classical computers for real-world commercial tasks at scale.
IBM, Google, Microsoft, and a growing field of startups are racing to reach the milestone of fault-tolerant quantum computing. Governments, including Australia's, have committed significant research funding to the sector, recognising that whichever nations and companies crack large-scale quantum computing first will hold an enormous strategic and economic advantage.
The timeline for truly practical quantum computing is genuinely uncertain. Optimistic forecasts put broadly useful, fault-tolerant machines within the next decade. More cautious assessments suggest it could take two to three decades. What is clear is that the research is accelerating, investment is growing, and the foundational science is sound.
The intersection of quantum computing with blockchain technology is one area drawing serious attention, since quantum processors capable of running Shor's algorithm could eventually break the cryptographic foundations that secure most blockchain networks. That is a long way off, but the security community is already working on quantum-resistant encryption standards in anticipation.
What it means for everyday Australians
For most people, the day-to-day impact of quantum computing will arrive quietly and indirectly. Faster drug discovery could mean better medicines reaching patients sooner. More efficient logistics algorithms could lower the cost of goods and reduce supply-chain waste. Improved climate modelling could sharpen the predictions that inform policy. Quantum machine learning could accelerate developments in artificial intelligence that are already reshaping industries.
The risks matter too. A sufficiently powerful quantum computer would render most of today's encryption obsolete, threatening the security of banking, communications, and government systems. This is why organisations like NIST have been working for years to develop post-quantum cryptography standards, publishing their first finalised algorithms in 2024. Preparing for a post-quantum world is now a serious priority for governments and large institutions worldwide.
Quantum computing is not a distant science-fiction concept. It is a technology in active development, with real consequences already beginning to ripple through security planning, pharmaceutical research, and national strategy. The more clearly we understand what it actually is, the better positioned we are to navigate those consequences as they arrive.