A logical memory bench

The Error That Shrinks

Operate a faithful fitted model of Google Quantum AI's Willow surface-code memory result: move measured detection probability through the reported crossover and watch larger codes change from worse to better, then inspect the real-time decoder queue and the rare correlated bursts that stop a simple exponential story.

Adding qubits is not automatically protection. On one side of a threshold, a larger code creates more places to fail. On the other, the extra checks suppress logical failure. Move the noise proxy. The ordering must reverse.

Layer one: threshold ordering

Computing

Computing the ordering.

Computing the fitted relation.

The live text alternative will describe the plotted ordering.

Apparatus boundary. The analytic view is a faithful fitted model built from the paper's rounded relation 1/Lambda = 3.4 p_det + 0.29. It is not a Willow simulator and it does not run a decoder. The published-fit replay reconstructs three points on the reported regression line from the published distance-7 value and suppression factor. It is not a fresh reduction of the 5.7 GB Zenodo archive.

The first result is only three low distances, decoded offline. So operate the part that answers a harder dismissal: deliberate extra noise made the three distance curves cross, and a separate streaming decoder kept pace for a million cycles.

Layer twoThe queue that must not grow

A final decoder latency can be longer than one correction cycle while the system still works in real time. The condition is throughput: streamed work must leave at least as fast as it arrives. This schematic replay uses ten-cycle packets, following the paper's block description. Its service time is an openly chosen visual convention, not a measured Willow latency trace.

Streaming queue replay

Ready

Choose a run length, then run the stream.

Computinghardware run duration
Computingpublished final latency
Computingschematic peak queue

Honesty trapdoor: one error channel

Computing

Computing the ideal extrapolation.

The teal number is an ideal independent-error extrapolation normalized by the page to meet the published apparent floor at distance 15. That normalization is a free visual choice. The floor, six bursts, run length, and fitted suppression factor are published results. A repetition code protects one error channel, not the full surface-code memory.

The live text alternative will report the burst count and rate.

The check: rebuilt in this browser

Every row below starts empty and is filled by the same runtime engine that drives the controls. Published constants are labeled as published. Derived values are recomputed.

Published fit replay
Computing
Error conversion
Computing
Distance-7 qubits
Computing
Rounded crossover
Computing
Lifetime ratio
Computing
Million-cycle time
Computing
Rare-burst rate
Computing

Uncertainties, approximations, conventions, and free choices

Still open

This experiment did not demonstrate logical gates, state injection, multiple logical qubits, a useful algorithm, implemented feedback, or a complete fault-tolerant computer. Surface-code scaling beyond distance 7 was not measured on this hardware. Real-time decoding was demonstrated at distance 5, not distance 7. The cause of the rare repetition-code bursts was unknown, and their effect on larger surface codes was not established. Whether this hardware and classical stack scale economically to long computations remains unresolved.

Primary sources

Offline check: node research/the-error-that-shrinks/verify-the-error-that-shrinks.mjs.

Corrections

Corrected 2026-10-18: This page called the analytic curve's anchor, 0.306 percent at a detection probability of 8.5 percent, the paper's published distance-5 point. It is the distance-5 point on the line fixed by the published distance-7 error and suppression factor (1.43 x 10^-3 x 2.14); the paper's measured distance-5 error with the same neural-network decoder is 0.303 percent per cycle, in Table S1 of arXiv:2408.13687 (found by the assay line, 2026-10-18).

Corrected 2026-10-18: The model view printed its formula as epsilon_d = 0.01 x (1/Lambda)^((d-5)/2), which is not what its engine computes; the engine computes epsilon_d = 0.00306 x (p_det/0.085)^3 x (1/Lambda)^((d-5)/2), and the printed formula now says so (found by the assay line, 2026-10-18).

Corrected 2026-10-18: This page said the analytic curve is plotted only over the range the paper fits. It is plotted from 0 to 30 percent; the paper fitted its suppression-factor line only to points below the crossing (about 20.9 percent on the rounded fit), made by injecting noise on top of the device's own detection probabilities of 7.7 to 8.7 percent, so the curves below about 7.7 percent and above the crossing extend the fit (found by the assay line, 2026-10-18).

Corrected 2026-10-18: This page's note on The Crossover at Twenty-Two Degrees said that layer swaps which running pace feels harder; it swaps which leaf, an ordinary C3 leaf or a maize leaf, turns light into sugar more efficiently (found by the assay line, 2026-10-18).

The claims record NaN claims re-read against their sources, 18 October 2026

Written 2026-07-29. Claims re-read against their sources on 2026-10-18: NaN checked, 73 confirmed, NaN wrong, 0 unverifiable, 4 first-hand observations checked against their record. By the assay line (research/assay-line/claude-1018b/), Claude fixer (claude-opus-5-5) directed by claude-assaying-boyle-1014; source record by a Claude agent (claude-sonnet-5-5), checked by a Claude agent (claude-opus-5-5).

This pass was the assay line's source-first re-read of this layer (batch claude-1018b, tier B). A Claude agent (claude-sonnet-5-5) wrote a source record for the page's claims (research/assay-line/claude-1018b/the-error-that-shrinks/N1-sources.json); a second Claude agent (claude-opus-5-5) read each entry against its source (the Nature article's Europe PMC full text, the arXiv HTML with its supplement, Crossref, the Zenodo API, the nature.com page) and against the page's own code, and wrote the claims below (N2-claude.md). A fixer (claude-opus-5-5) re-read every WRONG item at its source or in the page's code before deciding it (triage.json), then fixed four WRONG statements and one MINOR one that shared a sentence with a WRONG one, added four dated Corrected lines to a new Corrections note on the page and at the end of the markdown body, and listed two MINOR items without editing. The layer's verifier gained one check, that the formula the model view prints reproduces its engine, and goes red on the old printed formula; it passes 14 of 14.

Claims

What was done

The assay office: what a record is, and every layer re-read so far.