Quantum Computing Explained: How Qubits Work and Why It Matters Now

A classical computer stores information in bits that are either 0 or 1, like a switch that is on or off. A quantum computer instead uses qubits, which can represent 0, 1, or a weighted combination of both at the same time, according to IBM's official explainer on quantum computing. That property, called superposition, is one of the reasons quantum machines can explore many possible answers to certain problems simultaneously rather than one at a time.

The Physics Behind the Machine

IBM identifies four quantum-mechanical effects that make quantum computing possible: superposition, entanglement, interference and decoherence. Entanglement links qubits so that measuring one reveals information about another, even when the two are physically separated. Interference lets a quantum circuit amplify correct answers and cancel out wrong ones, in the same way overlapping waves can reinforce or cancel each other. Decoherence is the opposite effect — quantum states collapsing into ordinary classical values — and it is the main obstacle engineers must suppress to keep a quantum processor useful, per IBM.

Qubits can be built from several physical systems, including superconducting circuits cooled to near absolute zero, trapped ions, quantum dots and photons. IBM's own quantum processors rely on superconducting circuits because they can be manufactured and controlled with existing chip-fabrication techniques, IBM states.

A Verifiable Advantage: Google's Willow Chip

On October 22, 2025, Google announced that its 105-qubit Willow processor had produced what the company called the first verifiable quantum advantage, using an algorithm it named Quantum Echoes, according to Google's official blog post. The algorithm sends a signal into a set of qubits, perturbs one of them, then reverses the signal's evolution to listen for an amplified 'echo' created by constructive interference.

Google reported that Quantum Echoes ran 13,000 times faster on Willow than the best known classical algorithm running on one of the world's fastest supercomputers. The company emphasized that, unlike its 2019 quantum-supremacy claim, this result is 'verifiable' — it can be repeated on comparable quantum hardware and cross-checked, rather than relying on a sampling task with no independent way to confirm the output.

Working with researchers at the University of California, Berkeley, Google used the algorithm to study nuclear magnetic resonance (NMR) signals from molecules containing 15 and 28 atoms, pointing to possible future uses in drug discovery, battery materials and the design of new qubits, per the same Google announcement.

IBM's Path From 'Utility' to Fault Tolerance

IBM distinguishes between several stages of progress. The company says it reached 'quantum utility' in 2023, meaning its quantum processors could outperform classical approximation methods on specific tasks. IBM has said it expects to reach 'quantum advantage' — outperforming all known classical methods on a practical problem — by late 2026, according to the company's own quantum-computing overview.

Beyond that, IBM has published a roadmap toward fault-tolerant quantum computing, where errors are detected and corrected before they corrupt a calculation. The roadmap describes a chip called Quantum Loon released in 2025 with added qubit connectivity for proof-of-concept experiments toward high-rate qLDPC codes, a module named Quantum Kookaburra planned for 2026 that stores information using quantum low-density parity-check (qLDPC) memory, and a system called Starling targeted for 2029 that IBM says should run 100 million quantum gates on 200 logical qubits. IBM's error-correction approach uses what it calls 'bivariate bicycle codes,' including a '[[144,12,12]] gross code' that the company says needs roughly ten times fewer physical qubits than earlier surface-code methods to achieve the same error protection.

Why Encryption Is Already Being Rewritten

Quantum computers matter beyond the lab because of Shor's algorithm, a mathematical method published by Peter Shor in 1994 showing that a sufficiently powerful quantum computer could factor large numbers — and therefore break widely used RSA-style encryption — far faster than any classical computer, as IBM's overview notes.

That risk is not hypothetical to standards bodies. On August 13, 2024, the U.S. National Institute of Standards and Technology (NIST) finalized its first three post-quantum encryption standards: FIPS 203 (ML-KEM) for general encryption, and FIPS 204 (ML-DSA) and FIPS 205 (SLH-DSA) for digital signatures, according to NIST's official announcement. NIST mathematician Dustin Moody said organizations should 'start integrating them into their systems immediately, because full integration will take time.'

What Quantum Computers Are Not

IBM's materials stress that quantum computers are not simply faster versions of ordinary computers; they are suited to specific classes of problems — such as simulating molecules, chemical reactions and certain optimization or machine-learning tasks — where the number of interacting variables grows too large for classical computers to track efficiently. For everyday tasks like word processing or web browsing, classical computers remain far more practical.