How quantum computers work

Quantum computer basics

Every computer, no matter how advanced, begins with the same building block: the bit [↧]. It’s almost unbelievable that everything your laptop does – from streaming films to crunching spreadsheets – can be broken down into strings of 0s and 1s. And those numbers aren’t abstract. In hardware, they’re stored as physical states: tiny charges on capacitors, magnetic spots on a disk, or patterns etched into silicon.

Quantum computers start from the same basic principle: information must be stored in physical systems. But, here, the behaviour of those systems is governed by the laws of quantum mechanics rather than classical physics. The basic unit is the quantum bit, or qubit. Like a classical bit, a qubit produces either 0 or 1 when it is measured. But unlike its classical cousin, it can occupy a far richer set of states, mathematically represented as a vector in a two-dimensional space combining the basis states |0⟩ and |1⟩.

You’ll notice we’ve introduced mathematical notation here. In quantum computing, the equations aren’t just a way of describing what happens – they are the thing itself. Linear algebra tells us exactly how qubits behave, evolve and interact. Without it, we’d have no way to explain what makes quantum computation so different from the digital machines we know.

Superposition: beyond 0 and 1

At first glance, qubits may seem no different from classical bits: they have two basic states, |0⟩ and |1⟩, which play the same roles as 0 and 1 in ordinary computing. But here’s the crucial difference: qubits aren’t limited to those states. They can also exist in superpositions [↧] – combinations of |0⟩ and |1⟩. For instance, a qubit might be partly in |0⟩ and partly in |1⟩, described mathematically as something like 0.6 |0⟩ + 0.8 |1⟩. The numbers in front – here 0.6 and 0.8 – are called amplitudes: they capture the “weights” of each state, and when squared, they give the probabilities of measuring the qubit as 0 or 1.

In practice, the basis states |0⟩ and |1⟩ often correspond to very concrete physical configurations, such as different charge levels or a photon being in one of two locations. These are easy to picture, much like the physical ways classical bits are stored – a magnetic mark on a disk, or a hole in a punch card.

Superpositions, however, are harder to imagine. They’re not simply “in both states at once”, although that’s a common shorthand. Instead, a qubit can exist in a continuous range of states. This ability to carry and process combinations is one of the core reasons quantum computers can do things that classical machines cannot.

Quantum circuits in action

A single quantum gate [↧] can do remarkable things, but real computation arises only when they’re combined. Linked together, these gates form quantum circuits [↧], each one nudging qubits further along a path toward a reliable answer. On paper, this may look straightforward. In practice, though, it’s one of the hardest things to achieve. Quantum states are extremely fragile, and the slightest disturbance – a flicker of heat, a stray photon – can destroy them. These random disturbances are known as quantum noise [↧].

To preserve their state, qubits must be as isolated as possible. Some particles interact so weakly with their surroundings that they are almost impossible to disturb. Neutrinos, for instance – ghost-like particles that barely interact with matter – can pass through thick walls of lead untouched. Yet that very “aloofness” makes them useless as qubits: if we can’t reliably interact with them, we can’t prepare, manipulate or measure their states.

This highlights the central dilemma of quantum hardware: qubits must be isolated enough to preserve their state, but accessible enough that we can control them. Building a functional quantum computer is ultimately about striking that balance.

Quantum gates: how we program qubits

Once you have qubits, the next question is: How do you do something with them? Superposition is powerful, but on its own it’s just potential. To actually compute, we need ways to nudge, flip or blend qubits into new states. That’s what quantum logic gates are for.

Think of them as the moves in the game of quantum computing. A quantum gate is a precise operation that transforms a qubit, or sometimes several qubits at once. They’re the building blocks of every quantum algorithm [↧], just as classical gates like AND, OR and NOT sit at the heart of everything your laptop does.

Some gates are simple. The quantum version of NOT, for instance, flips |0⟩ into |1⟩ and vice versa. But qubits can also exist in combinations of those states. If a qubit is in a superposition, say α |0⟩ + β |1⟩, the NOT gate swaps the amplitudes: it becomes α |1⟩ + β |0⟩. In other words, the weights attached to |0⟩ and |1⟩ simply trade places.

Other gates are more surprising. The Hadamard gate [↧], for example, doesn’t just flip a qubit – it blends its states into a superposition. With it, you can move from the ordinary “either/or” world of bits into the far stranger “both at once” world of qubits. That’s powerful because it opens new computational pathways. Where a classical NOT gate is like walking back and forth along a road, the Hadamard gate is like taking a boat straight across the water. Suddenly, new routes appear, and with them, new ways of solving problems that classical machines can’t match.

Making qubits talk

Designing circuits is one thing, but it’s meaningless unless we can extract a result. That’s where measurement [↧] comes in. Imagine someone hands you a qubit in some unknown state. Can you simply “peek inside” to see how it was set up? Surprisingly, no. It’s not that the qubit is “being secretive”, it’s that quantum mechanics doesn’t allow us to access the full state directly. When you measure, you only ever get one clear outcome.

To get that outcome, the qubit has to be pushed into contact with the classical world. In practice, that means letting it interact with a detector, a laser setup or an electronic circuit. The exact setup varies depending on the technology: lasers reveal the state of trapped ions [↧], microwave circuits pick up signals from superconducting qubits, and photon detectors register which path a photon has taken.

Whatever the platform, the effect is the same: the quantum state is converted into a classical signal that we can record.

How quantum computers work

We’ve looked at the basic building blocks of quantum computing: qubits, quantum gates, circuits and measurement. But the real magic takes place when you put them together and watch how groups of qubits interact. This is where the working principles of quantum computers come alive.

• Entanglement [↧]: Link two qubits and they no longer behave like isolated objects. Their states become intertwined, so measuring one instantly determines the correlated outcome of the other, even if they’re separated by vast distances. This strange bond isn’t just a physics curiosity; it’s a powerful resource that allows quantum computers to tackle certain problems far more efficiently than classical machines.
• Interference [↧]: As qubits evolve through a quantum circuit, their hidden waves of probability overlap, cancel or reinforce one another. Well-designed algorithms exploit this effect to suppress wrong answers while amplifying the right ones. Grover’s algorithm [↧] is a striking example, using interference to search through enormous datasets much more effectively than classical computers.
• Decoherence [↧]: But there’s a catch: qubits are fragile. Heat, stray particles, or even the faintest vibration, can collapse their delicate state, a problem known as decoherence. Error correction [↧] methods help, but keeping qubits stable long enough to run meaningful algorithms is one of the biggest challenges in quantum computing.

Put together, the cycle looks like this: prepare qubits in a chosen state (usually |0⟩); apply quantum gates that manipulate and entangle them; design the circuit so interference amplifies the correct answers while suppressing the wrong ones; and finally measure the qubits to convert the result into classical information. It’s not just a faster way of computing, it’s a fundamentally new way of thinking about what computers can do.

Different paths to quantum computing

The hard part isn’t the theory, it’s making it work in physical machines. Around the world, researchers are testing different types of quantum computers, each based on a distinct physical system with its own strengths and limitations.

• Superconducting qubit quantum computer: Used by IBM and Google, this is today’s most established platform. Superconducting circuits cooled to near absolute zero switch states incredibly fast, but scaling is difficult – the more qubits you add, the harder it is to keep them stable. Thanks to mature software like Qiskit and Cirq, developers can build, test and refine quantum programs more easily, giving these systems a natural head start.
• Trapped-ion quantum computer [↧]: Companies like IonQ use lasers to trap and manipulate individual atoms. These qubits have exceptionally long coherence [↧] times, making them very stable. The trade-off is slower gate operations and greater difficulty scaling to large systems.
• Photonic quantum computer: Light itself can carry quantum information, as in the models of PsiQuantum and Xanadu. Photons (light particles) resist noise naturally, but coaxing them to interact strongly enough for computation is a major challenge.
• Neutral atoms quantum computer: Using optical tweezers, atoms can be arranged in grids of potentially thousands of qubits. This is a highly scalable model, though still young compared to other platforms.
• Quantum dot quantum computer: This model uses nanoscale semiconductors to trap and manipulate single electrons. Built from the same materials as classical chips, they fit naturally into existing semiconductor technology. The difficulty, however, is keeping those delicate quantum states coherent at such tiny scales.
• Topological quantum computer: This approach, championed by Microsoft, aims to harness anyons – exotic quasiparticles thought to form the basis of topological qubits [↧]. In theory, these qubits could be far more resistant to quantum noise than other designs, but for now the concept remains unproven.

Each of these approaches comes with trade-offs – speed versus stability, scalability versus control – and none has emerged as the definitive path forward. Together, though, they provide some of the most striking quantum computer examples, showing how diverse physical systems can be engineered to harness the underlying principles of quantum mechanics.

Standards powering the quantum era

Quantum computing is no longer a distant vision, it’s already here in its earliest forms. Through cloud platforms, researchers and businesses can run experiments on real machines, usually only a few dozen qubits strong. Modest as they are, these prototypes prove that the strange rules of quantum mechanics can be turned into working computation.

The challenge now is coherence, not just in qubits, but across the field itself. As designs multiply, the risk is fragmentation: competing platforms, each speaking its own language. To counter this, quantum computing has its own dedicated technical committee: ISO/IEC JTC 3. Created in 2024, it brings together global experts to set common rules for how quantum systems are described, built and connected.

Standards don’t hold quantum computing back – they give it direction. They provide the invisible scaffolding for interoperability and trust, turning isolated breakthroughs into a shared ecosystem. With standards, the field can move beyond dazzling experiments to become an industry with the power to transform finance, healthcare, logistics, and beyond.

• ISO/IEC 4879:2024Information technology — Quantum computing — Vocabulary

Quantum horizons

With standards laying the groundwork, the scattered experiments of today are being shaped into a connected ecosystem. That foundation is crucial, because quantum computing is not just about faster machines, it’s about reimagining what’s possible. By bending the rules of physics into tools for computation, we stand at the edge of discoveries classical technology could never reach.

The road ahead will be long, full of noise, errors and technical hurdles. But history shows that every great leap in computing – from vacuum tubes to microchips to the cloud – began with fragile prototypes and bold imagination. Quantum is no different.

What makes this moment extraordinary is that we are present at the very beginning. The breakthroughs of tomorrow will be built on the questions we ask today. Quantum computing is not a distant future – it’s a revolution already unfolding.

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Glossary

• Algorithm (quantum): algorithm for use on a quantum processor
  Note: Quantum algorithms can be designed so that they need to be run multiple times to extract the required result; for example, to overcome noise or as a means to implement a target algorithm efficiently using approximate quantum circuits.
  [Adapted from ISO/IEC 4879:2024, 3.4.9]
• Bit, binary digit: either of the digits 0 or 1 when used in the binary system
  [ISO/IEC 2382:2015, 2121573]
• Classical computer: computer that processes information using classical bits
• Coherence (quantum): existence or extent of unambiguous phase relationships between possible states of a quantum system
  [Adapted from ISO/IEC 4879:2024, 3.2.18]
• Cryptography (quantum): cryptography that utilizes quantum communication in an essential way
  [ISO/IEC 4879:2024, 3.6.2]
• Decoherence: loss or degradation of quantum coherence
  [Adapted from ISO/IEC 4879:2024, 3.2.19]
• Entanglement: property of a quantum state within a joint quantum system, consisting of at least two subsystems, for which the quantum state cannot be described in terms of independent characteristics of its individual constituents
  [ISO/IEC 4879:2024, 3.2.10]
• Error correction (quantum): procedure to diagnose and correct errors in the constituent parts of a logical qubit without measuring any logically encoded quantum information, by exploiting the logical qubit’s symmetries
  [Adapted from ISO/IEC 4879:2024, 3.4.6]
• Grover’s algorithm: quantum algorithm for searching an unsorted database with quadratic speedup compared to classical algorithms
• Hadamard gate: quantum gate that places a qubit into a superposition of states
  Note: The Hadamard gate is often used at the beginning of quantum algorithms.
• Interference: coherent superposition of wave functions (quantum states) of a physical system
  [ISO/TS 80004-12:2016, 2.7]
• Ion trap: quantum processor architecture that uses ions confined by electromagnetic fields as qubits, manipulated with lasers
• Measurement (quantum): process that outputs a physical property of a quantum state
  Note: Quantum measurement usually involves interaction with a meter system which encodes the output of the physical property.
  [Adapted from ISO/IEC 4879:2024, 3.2.16]
• Quantum circuit: combination or sequence of quantum gates and other operations
  Note: Quantum circuits are usually designed to perform a more complex function than individual gates.
  [Adapted from ISO/IEC 4879:2024, 3.4.5]
• Quantum computer: fully programmable quantum processor that can implement or approximate any unitary dynamics defined within its full Hilbert space
  Notes:
  - In circuit-based quantum computing, a quantum computer has access to a universal set of quantum gates.
  - Quantum computers most commonly use quantum information encoded in qubits.
  [Adapted from ISO/IEC 4879:2024, 3.4.10]
• Quantum encryption: use of quantum-mechanical phenomena to ensure secure communication, typically through quantum key distribution
• Quantum gate: applied quantum operation that transforms input quantum states into output quantum states
  [Adapted from ISO/IEC 4879:2024, 3.4.2]
• Quantum key distribution (QKD): use of quantum phenomena for cryptographic purposes
  [ISO/TS 80004-12:2016, 6.6]
• Quantum noise: disturbance in a quantum system that affects its state and leads to errors or loss of coherence
• Quantum processor: tangible device that performs quantum information processing
  [ISO/IEC 4879:2024, 3.4.8]
• Quantum supremacy: point at which a quantum computer performs a computation that is unfeasible for classical computers within practical resource limits
• Qubit: quantum system with two basis states
  Note: Qubit stands for quantum bit; it is the smallest unit of quantum information.
  [Adapted from ISO/IEC 4879:2024, 3.3.3]
• RSA threat: risk to RSA cryptographic systems arising from the capability of quantum algorithms to factor large integers efficiently
• Shor’s algorithm: a quantum Fourier transform-based algorithm for factoring a (large) integer
  [ISO/IEC 9594-12:2025, 3.2.23]
• Superposition: complex linear combination of two or more different quantum states
  [ISO/IEC 4879:2024, 3.2.8]
• Topological qubits: qubits in which quantum information is encoded in topological properties of a system, providing inherent resistance to certain types of errors
  Note: Topological qubits are often linked to Majorana zero modes for fault-tolerant quantum computing.
• Trapped-ion quantum computer: quantum computer that uses charged atoms (ions) suspended in space and manipulated with lasers