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Quantum Error Correction

Turning thousands of unreliable physical qubits into a handful of trustworthy logical ones — foundational theory, experimental milestones, courses and software, and the companies building fault-tolerant hardware.

33 topics•5 categories•Updated October 2026

Foundational Theory & Tutorials

8 entries

The papers and tutorials that established quantum error correction.

Experimental Milestones

7 entries

Experiments showing error correction working on real hardware.

Courses & Software

6 entries

Hands-on ways to learn and simulate error correction.

Hardware Roadmaps & Companies

7 entries

Organisations working toward fault-tolerant quantum computers.

Related Pages & Programmes

5 entries

More on this site and national programmes.

Frequently Asked Questions

Why do quantum computers need error correction?

Quantum gates err far more often than classical gates and qubits lose their state through decoherence, so long, useful algorithms cannot run reliably without correcting errors as they happen.

Why can't we just copy qubits as backup?

The no-cloning theorem forbids copying an unknown quantum state, and measuring a qubit to check it collapses its superposition. QEC instead spreads information across many qubits and measures parity checks, called syndromes.

What is a logical qubit?

A reliable qubit built from many noisy physical qubits using an error-correcting code. The physical-to-logical ratio depends on the code and hardware quality, and can range from tens to thousands.

What are the main code families?

Surface codes (local and hardware-friendly), stabilizer and topological codes (the theoretical framework), qLDPC codes (lower overhead but need longer-range connections) and concatenated codes (strong in theory but demanding on gate quality).

What does below threshold mean?

Below the threshold, adding more physical qubits to a code lowers the logical error rate. Google Quantum AI's 2024 experiment is cited as a convincing demonstration on a real chip.