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READ THE EVIDENCE

Check the claim before sharing.

Choose one claim. Find its primary source. Keep the conditions and the limitation beside the result.

Your source-check worksheet

No account or programming is needed. Use this for a short reading discussion or your own notes.

  1. Record the headline, article link and original publication date.
  2. Find the primary paper, technical report or standard. Record its title, link and date.
  3. Write one narrow claim in your own words. Is it a measurement, simulation, announcement or future target?
  4. Find the supporting section, table or figure. Note the workload, comparison and experimental conditions.
  5. Write one limitation that changes how a reader should interpret the claim. Mark missing details as unknown.
  6. Finish: “The source reports ___ under ___. It supports ___. It does not establish ___.” Date your check.

Download the worksheet (TXT) · Facilitator notes (TXT)

Worked example: a protected quantum memory

Start with QubitWire’s error-correction field guide and the Google Quantum AI and collaborators surface-code paper. The paper was published online on 9 December 2024. An author correction dated 28 April 2026 amends labels and legend keys in Figure 3a.

Question: Does a lower logical memory error rate demonstrate an arbitrary useful application running fault-tolerantly?

Open the worked answer

Claim: Under the reported Willow experimental conditions, logical memory errors decreased as the surface-code distance increased.

Locate the evidence: Read “A surface code memory below threshold,” especially the paragraph beginning “We characterize the logical performance,” and Figure 1c–d. The reported distance-7 result uses a neural-network decoder, with memory runs up to 250 error-correction cycles averaged across logical X and Z bases. Lower-distance results include multiple subgrids.

Keep the boundary: This experiment protects stored quantum information. It does not demonstrate arbitrary fault-tolerant applications. The distance-5 real-time decoder and the repetition-code study are distinct results in the same paper.

Reading note: The source supports a below-threshold surface-code memory result under its measured conditions. Logical computation, application workload and resource requirements need their own evidence. Sources checked .

Download the worked answer and source locations (TXT)

Five source-linked records

Quantum source-provenance pilot · Version 1.0. These original annotations show how to keep a claim, source, check date and limitation together. A research result, a cryptographic standard and a software resource are different kinds of evidence. This English-language convenience selection supports reading exercises; it is not newly measured data, a comprehensive survey or a ranking.

Below-threshold surface-code memory

Google Quantum AI and collaborators reported Willow memory experiments with a logical-error suppression factor of 2.14 plus or minus 0.02 for each increase of two in surface-code distance.

Limit: This is a logical-memory result. It does not demonstrate arbitrary fault-tolerant applications or application-level advantage. The paper also discusses correlated errors, scale-up and decoding challenges.

Primary source: Quantum error correction below the surface code threshold. Published .

Where to read: Abstract; A surface code memory below threshold; Figure 1c–d; Outlook

Author correction (PDF) · Published

Review note: The 28 April 2026 author correction fixes the repetition-code x-axis label and legend keys in Figure 3a. The publisher states that the HTML and PDF figure were amended.

Source checked · Read the QubitWire context →

ML-KEM key encapsulation

NIST published FIPS 203 as a final standard on 13 August 2024, specifying ML-KEM for key encapsulation with three parameter sets.

Limit: A KEM establishes a shared key under stated conditions. A standard does not certify an implementation or prove migration. NIST’s 17 November 2025 Planning Note flags an issue for a future revision.

Primary source: FIPS 203: Module-Lattice-Based Key-Encapsulation Mechanism Standard. Published .

Where to read: Date Published; Abstract; Planning Note (11/17/2025); Document History

Publisher’s potential-updates spreadsheet (XLSX) · Linked details were not reviewed.

Review note: The linked potential-updates spreadsheet was inaccessible in this run; its detailed changes were not reviewed.

Source checked · Read the QubitWire context →

ML-DSA digital signatures

NIST published FIPS 204 as a final standard on 13 August 2024, specifying ML-DSA algorithms for generating and verifying digital signatures.

Limit: Digital signatures and key encapsulation serve different purposes. Publication does not certify deployment or implementation security. NIST’s 31 July 2026 Planning Note lists minor issues for correction in a future revision.

Primary source: FIPS 204: Module-Lattice-Based Digital Signature Standard. Published .

Where to read: Date Published; Abstract; Planning Note (07/31/2026); Document History

Publisher’s potential-updates spreadsheet (XLSX) · Linked details were not reviewed.

Review note: The linked potential-updates spreadsheet was inaccessible in this run; its detailed changes were not reviewed.

Source checked · Read the QubitWire context →

SLH-DSA hash-based signatures

NIST published FIPS 205 as a final standard on 13 August 2024, specifying the stateless hash-based digital-signature algorithm SLH-DSA, based on SPHINCS+.

Limit: This is a digital-signature specification. It does not establish an organization’s migration, certify an implementation or provide a key-encapsulation algorithm.

Primary source: FIPS 205: Stateless Hash-Based Digital Signature Standard. Published .

Where to read: Date Published; Abstract; Document History

Review note: No Planning Note or errata link was displayed on the checked final record. This is a page-and-date observation, not a guarantee against future corrections.

Source checked · Read the QubitWire context →

Shared optimization benchmarks

IBM’s 12 August 2026 QOBLIB update describes ten shared optimization problem classes with metrics and classical baselines for comparing quantum and classical methods.

Limit: A benchmark library is not a solver result or proof of quantum advantage. A comparison must solve the same workload and required quality against strong classical methods.

Primary source: QOBLIB: tracking progress in quantum optimization. Published .

Where to read: What is QOBLIB?; Why the search for advantage runs through benchmarking

Related benchmark library

Review note: This annotation covers benchmark infrastructure only. Changing submission counts and unrelated promotional advantage claims were excluded.

Source checked · Read the QubitWire context →

Download the records (JSON) · Read the collection method and limits

Comparing two results? Use the fair-comparison worksheet to keep workload, baseline and conditions beside each claim.

Check the record format offline

The Python toolkit checks required fields, dates, links, duplicate IDs and review markers without network access or added dependencies. Passing the check verifies the format. It does not verify science, source accuracy or permission to reuse a source.

Download the evidence toolkit (ZIP). The README includes one command to check the authentic records and a separate failing test fixture.

Reuse a small reference card

The text-only memory card keeps the takeaway, qualification, source links and check date together. It works without an embedded image, tracking code or a required link back to QubitWire.

Open the card · Download the original card files (ZIP) · Plain-text version

The new worksheet, notes, card and original annotations use CC BY 4.0. The toolkit code uses the MIT License. These permissions apply only to this kit. Linked papers, standards, other QubitWire material and third-party media retain their own rights. Full reuse notes.

Version 1.0 · Primary-source review · Corrections: gotqubits@gmail.com