How Does Quantum Computing Work?

In October 2019, Google announced that its quantum processor had performed a calculation in 200 seconds that would take the world’s fastest classical supercomputer approximately 10,000 years. IBM disputed the specific number, but the underlying claim was clear: something fundamentally different was happening inside that machine. The machine was a quantum computer, and it was doing math that no ordinary computer could realistically replicate.

Classical computers, from your phone to the largest data center, process information using bits. A bit is a switch that is either off (0) or on (1). Everything these machines do, from displaying this text to running a video call, comes down to manipulating millions of these tiny switches in sequence. Quantum computers work differently. They use quantum bits, or qubits, which can be 0, 1, or something genuinely impossible in the ordinary world: a combination of both at the same time.

The short answer

Quantum computing is a type of computation that harnesses quantum mechanical phenomena, specifically superposition and entanglement, to process information in ways that classical computers cannot efficiently replicate. A qubit can exist as 0 and 1 simultaneously through superposition, and multiple qubits can become entangled so that measuring one instantly influences the state of another, even across distance. These properties allow quantum computers to explore many possible solutions at the same time, rather than checking them one by one.

The full picture

Superposition: being in two places at once

The most confusing thing about qubits is that they can be in two states simultaneously. A classical bit is definitively either 0 or 1. A qubit can be in a state that is partly 0 and partly 1, a condition called superposition. This is not a metaphor or a limitation of measurement: the qubit genuinely exists in both states at the quantum level, until a measurement collapses it into one or the other.

When you have multiple qubits, superposition scales quickly. Two qubits in superposition give you four possible states at once (00, 01, 10, 11). Three qubits give you eight. By the time you reach 50 qubits, you have over a quadrillion simultaneous states. This exponential growth is where quantum computing gets its power: a quantum computer with enough stable qubits can represent and process an astronomical number of possibilities in parallel.

Entanglement: spooky action at a distance

Albert Einstein famously called entanglement “spooky action at a distance,” and he was uncomfortable with it for good reason. When two qubits become entangled, they form a correlated pair: measuring one qubit instantly tells you the state of the other, regardless of how far apart they are. Change one, and the other responds immediately.

For quantum computing, entanglement means you cannot treat qubits as independent units. They form a collective system, and their correlations can be exploited to perform computations that would require exponentially more classical bits to represent. Entanglement is what allows a quantum computer to do more than just run many classical calculations in parallel; it creates genuinely quantum correlations that have no classical analog.

Quantum gates and circuits

Classical computers perform operations using logic gates (AND, OR, NOT, and their variants). Quantum computers have analogous quantum gates that rotate qubit states and create or resolve entanglement. A quantum circuit is a sequence of these quantum gates applied to a set of qubits, designed to steer the system toward a useful answer.

The design of quantum circuits is a specialized discipline. You cannot simply write a quantum program the same way you write a classical program. The challenge is that the answer lives in the quantum state of the system, and extracting it requires careful measurement strategies that account for the probabilistic nature of quantum mechanics.

Why quantum computers need extreme cold

Qubits are fragile. The quantum states they exploit are easily disrupted by environmental interference: vibrations, electromagnetic fields, even cosmic rays. This disruption is called decoherence, and it is the primary enemy of quantum computing.

Most superconducting qubits, the type used by IBM and Google, operate at temperatures close to absolute zero, roughly 15 millikelvin, which is colder than outer space by a factor of about 250. At these temperatures, the thermal vibrations that would scramble qubit states nearly disappear. The machines that house these qubits look like elaborate chandeliers of concentric shielding layers, with the processor itself suspended at the center, isolated from everything.

What quantum computers are actually good at

Quantum computers are not universal upgrades to classical machines. They excel at specific problem types, particularly those involving optimization, sampling, and simulating quantum systems.

Drug discovery is frequently cited as a flagship application. Simulating how a new molecule behaves at the quantum level is extraordinarily difficult for classical computers because quantum mechanics governs molecular behavior. A quantum computer, being quantum itself, can simulate those interactions more naturally. A 2023 Nature Chemistry study demonstrated quantum simulation of a FeMoco enzyme cluster relevant to nitrogen fixation, a problem considered intractable for classical methods at that scale.

Cryptography is another area of intense focus. Current widely-used encryption schemes, including RSA, rely on the mathematical difficulty of factoring large numbers. A sufficiently powerful quantum computer running Shor’s algorithm could break these schemes. The US National Institute of Standards and Technology (NIST) finalized its first post-quantum cryptography standards in 2024 specifically to address this threat.

Financial firms are exploring quantum optimization for portfolio management and risk analysis. These problems involve evaluating vast numbers of combinations and scenarios, exactly the class where quantum approaches may offer advantages over classical heuristics.

Why it matters

The implications play out along two divergent timelines. In the shorter term, quantum simulation of molecular systems could compress decades of drug discovery and materials science work. A pharmaceutical company that can accurately simulate how a candidate molecule will interact with a target protein, without months of laboratory trial and error, has a fundamentally different cost structure and speed of innovation. The same applies to fertilizer design, battery chemistry, and catalyst development.

The longer-term concern is the cryptographic one. Data encrypted today with standards that quantum computers can break is at risk if it is captured now and decrypted later by a future quantum machine. Health records, government communications, financial data, and authentication systems all have minimum security shelf lives measured in decades. Organizations that cannot guarantee their data is protected under post-quantum standards face a sliding window of vulnerability.

Neither timeline is imminent, but both are advancing. IBM’s roadmap targets a 100,000-qubit system by 2033. Google demonstrated quantum error correction below threshold in 2023, a milestone that means adding more qubits actually reduces errors rather than amplifying them. The field is moving from scientific curiosity to engineering challenge.

Common misconceptions

“Quantum computers will replace classical computers.”

This is wrong in the same way that specialized scientific instruments replaced neither calculators nor smartphones. Quantum computers are narrow accelerators for specific problem classes. For web browsing, databases, streaming video, or the vast majority of computing tasks, classical computers will remain faster, cheaper, and more practical indefinitely. A quantum computer needs to be kept at a fraction of a degree above absolute zero and costs millions of dollars to operate. A standard laptop handles email without either requirement.

“Quantum computers are just faster classical computers.”

Quantum speedup is not simply a matter of clock speed. The advantage comes from fundamentally different algorithms and a different computational model. For the problems where quantum computing offers advantage, the speedup can be dramatic. For most everyday computing tasks, a quantum computer running current algorithms would be slower than the device in your pocket. The speedup is specific, not universal.

“Quantum computers already exist and are in widespread use.”

The most capable quantum computers today have hundreds to low-thousands of noisy, error-prone qubits. IBM’s Heron processor, announced in 2024, has 133 qubits but still requires error correction protocols to be practically useful. Google’s Willow paper, published in 2024, demonstrated performance improvements on a targeted benchmark. The machines being discussed in press releases and the fault-tolerant quantum computers that could break RSA encryption are separated by many years of engineering and likely require millions of physical qubits to support the hundreds or thousands of logical qubits needed for meaningful cryptographic work.

Key terms

Qubit - The fundamental unit of quantum information. Unlike a classical bit, which is definitively 0 or 1, a qubit can exist in superposition of both states simultaneously.

Superposition - A quantum property where a qubit exists as a combination of 0 and 1 at the same time. When measured, the qubit collapses into one state or the other, with probabilities determined by its superposition coefficients.

Entanglement - A quantum correlation between two or more qubits where their states are linked regardless of physical distance. Measuring one entangled qubit instantly affects what you will measure on the others.

Decoherence - The loss of quantum information in a qubit due to interaction with its environment. It is the primary engineering challenge in building practical quantum computers.

Quantum gate - An operation analogous to a logic gate in classical computing, applied to qubits to manipulate their states and create entanglement. Quantum circuits are sequences of quantum gates.

Post-quantum cryptography - Encryption algorithms designed to be secure against attacks from quantum computers. NIST finalized its first post-quantum standards in 2024.