What is Quantum Computing and Why Scientists Say It Will Change Everything

Start with the bit

Every classical computer — the one in your pocket, the server farms under the Atacama desert, the machine running the global financial system — processes information as bits. A bit is a switch. It is either 0 or it is 1. Everything a classical computer does, no matter how sophisticated, ultimately reduces to enormous sequences of 0s and 1s being flipped and combined according to logical rules.

This has been the basis of computing for eight decades, and it has served us extraordinarily well. But there is a class of problems — important ones, in cryptography, drug discovery, materials science, and logistics — where classical computers run into a wall. Not because they are slow, but because the nature of the problem makes it mathematically intractable regardless of speed.

Quantum computing is an attempt to build machines that work by entirely different rules.

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What a qubit actually is

A qubit is the quantum analogue of a bit. But where a classical bit must be either 0 or 1, a qubit can exist in a superposition of both states simultaneously — at least until you measure it.

This is where Schrödinger's cat becomes useful. Erwin Schrödinger proposed a thought experiment: a cat is placed in a sealed box with a vial of poison triggered by a quantum event. Until the box is opened, the cat is, under strict quantum mechanical rules, neither alive nor dead — it exists in a superposition of both states. The act of observation collapses it into one definite outcome.

A qubit is the vial's radioactive atom. Before you measure it, it genuinely holds both states at once. Quantum mechanics is not saying we simply don't know which state it is in — it is saying it is in both, described by a probability wave that only resolves when observed.

Why superposition is powerful

One qubit can represent 0 and 1 simultaneously. Two qubits can represent all four combinations (00, 01, 10, 11) simultaneously. Ten qubits can represent 1,024 states simultaneously. Fifty qubits can represent over a quadrillion states at once.

When a quantum computer processes information, it processes all possible states in parallel. For the right kind of problem, this is transformative. It is not that the computer gets the answer faster — it is that it explores the entire problem space simultaneously, rather than checking solutions one at a time.

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Entanglement: the other strangeness

Entanglement is quantum mechanics' second great trick, and perhaps its most philosophically disturbing.

When two qubits become entangled, their states become correlated in a way that has no classical analogue. Measure one and you instantly know something about the other — regardless of the distance between them. Einstein famously called this "spooky action at a distance" and spent years trying to prove it was impossible. He was wrong. Entanglement is real, has been experimentally verified thousands of times, and is one of the key resources that gives quantum computers their power.

In a quantum algorithm, entanglement allows qubits to cooperate in a fundamentally deeper way than classical bits can. Information encoded across entangled qubits can be manipulated as a whole, enabling operations that would require exponentially more resources on a classical machine.

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What quantum computers are actually good at

This is where a lot of popular writing goes wrong. Quantum computers are not universal upgrades to classical computers. They are not faster at email, spreadsheets, video streaming, or most of what ordinary computers do. They excel at a specific category of problems.

Cryptography and code-breaking. The most alarming near-term application. Most modern encryption — including RSA, which secures internet banking, government communications, and much of global commerce — relies on a simple mathematical fact: it is easy to multiply two large prime numbers together, but practically impossible to work backwards from the product and find the originals. A classical computer trying to factor a 2,048-bit RSA key would take longer than the current age of the universe.

A sufficiently powerful quantum computer running Shor's algorithm — a quantum algorithm specifically designed for factoring — could do it in hours or days. This is not a distant theoretical concern. Security agencies around the world are already transitioning to post-quantum cryptography standards, and the US National Institute of Standards and Technology (NIST) finalised its first post-quantum encryption standards in 2024.

Molecular simulation. Classical computers are terrible at simulating quantum systems, for an obvious reason: quantum systems follow quantum rules, not classical ones. Simulating even a relatively simple molecule accurately requires computational resources that grow exponentially with molecular complexity.

Quantum computers, operating on quantum rules natively, could simulate molecular interactions with precision that classical machines cannot approach. The implications for drug discovery are significant: instead of testing millions of candidate molecules in slow wet-lab experiments, pharmaceutical companies could simulate how a potential drug binds to a protein target at the quantum level, dramatically accelerating the search for treatments for cancer, Alzheimer's, and antibiotic-resistant bacteria.

Optimisation problems. The travelling salesman problem — finding the shortest route through a set of cities — is trivially easy for two cities and computationally nightmarish for two hundred. Real-world logistics, financial portfolio optimisation, and supply chain management all involve variants of this class of problem. Quantum approaches like the Quantum Approximate Optimisation Algorithm (QAOA) may offer advantages here, though this remains an active research question.

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The current state of the hardware

Building a quantum computer is one of the hardest engineering challenges in history. Qubits are extraordinarily fragile. Any interaction with the environment — a stray magnetic field, a vibration, even thermal noise — causes decoherence: the quantum state collapses, and the computation is ruined. Most quantum computers must operate near absolute zero, colder than outer space, and even then qubits remain reliable for only fractions of a second.

IBM is currently the most aggressive public chronicler of quantum progress. Its roadmap envisions systems with tens of thousands of physical qubits by the late 2020s, with error correction schemes turning noisy physical qubits into reliable logical qubits. Its current flagship system, the Heron processor, has demonstrated significant improvements in error rates over its predecessors.

Google made headlines in 2019 by claiming quantum supremacy — demonstrating a quantum computation that would have taken a classical supercomputer 10,000 years. IBM disputed the 10,000-year figure (it later revised it down to a matter of days with the right classical algorithm). The underlying point — that quantum systems can, for specific tasks, outperform classical ones — stood.

IonQ takes a different hardware approach, using individual trapped ions as qubits rather than superconducting circuits. Trapped-ion qubits are inherently more stable and have better fidelity, though they are harder to scale.

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The timeline question

Honest researchers resist precise predictions. The challenges remaining — primarily error correction and scaling to thousands of logical qubits — are enormous and cannot be scheduled.

The current era is often called NISQ (Noisy Intermediate-Scale Quantum). NISQ machines have tens to hundreds of qubits but too much noise to run the most powerful quantum algorithms at scale. They are useful for research and for demonstrating principles, but they are not yet breaking RSA encryption or designing breakthrough drugs.

Fault-tolerant quantum computing — machines with enough logical qubits and low enough error rates to run Shor's algorithm on meaningful key sizes — is likely at least a decade away, and possibly two. The cryptographic threat, while real, is not imminent. The drug discovery and materials science applications may arrive earlier, through hybrid classical-quantum approaches that use quantum processors for the hardest sub-problems.

A useful framing: quantum computing is roughly where classical computing was in the 1950s. The fundamental physics works. The hardware is being built. The killer applications are being identified. The engineering challenges between here and practical widespread use are formidable but not insurmountable.

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Why you shouldn't panic, but should pay attention

If you run a business that depends on encrypted communications — which is to say, any modern business — you should be tracking the post-quantum cryptography transition. The threat is not tomorrow, but cryptographic upgrades take years to implement across complex systems, and adversaries are already harvesting encrypted data today with the intention of decrypting it once quantum capability arrives. The time to start migrating is before the urgency is acute.

For everyone else, quantum computing represents one of the genuinely transformative technologies of the coming decades. Its applications in chemistry and materials science could accelerate progress on climate technology, battery design, and medicine in ways that are difficult to fully anticipate. The physics is extraordinary. The engineering is grinding. The implications are real.

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The bottom line

Quantum computers exploit superposition and entanglement to process information in ways classical machines fundamentally cannot. They are not general-purpose speed upgrades; they excel at specific problems in cryptography, molecular simulation, and optimisation. The hardware is real and advancing, but fault-tolerant quantum computing at scale is still roughly a decade away. The encryption implications are serious enough that standards bodies are already acting. For most people, the most important thing is not to panic, not to dismiss it, and to watch the engineering progress with genuine interest — because when the threshold is crossed, it will matter enormously.