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data/README promised that re-running with an unchanged config reproduces exactly. That is no longer true for three of the eight runs: adding failure domains put n_regions and region_locality into the topology seed, which changes the graph drawn for every config, including those leaving both at their defaults. default, percolation and redundancy predate that change. A spot-checked cell moves by 0.3%, about 1.5 standard errors -- ordinary variation between independent realisations, not a change in behaviour, and within the error bars the report already states. Closed-form quantities are identical either way. The README now says which runs are current, which are not, and why. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
59 lines
4.0 KiB
Markdown
59 lines
4.0 KiB
Markdown
# Evidence of record
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The sweep outputs behind every number in [the report](../README.md). The simulator does not commit
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its own `runs/` directory — these are the copies of record, kept so that any figure or table can be
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re-derived, or challenged, without re-running hours of compute.
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Each run directory holds the three tables the simulator writes: `propagation.parquet`,
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`adversary.parquet` and `deanon.parquet`.
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| directory | config | sampling | backs |
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|---|---|---|---|
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| `default/` | `configs/default.yaml` | 1 000 rounds × 8 seeds = **8 000/cell** | §3.1–§3.5 — delay, observation, eclipse, deanonymization, delivery, coverage |
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| `redundancy/` | `configs/redundancy.yaml` | 1 200 × 8 = **9 600/cell** | §3.8 — messaging redundancy R = 1…4 |
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| `percolation/` | `configs/percolation.yaml` | 800 × 8 = **6 400/cell** | §3.5 — the churn threshold `u_c = 1 − 1/(degree − 1)` |
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| `correlated-churn/` | `configs/correlated-churn.yaml` | 800 × 8 = **6 400/cell** | §3.9 — correlated AS/region outages vs uniform churn |
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| `fullscale/` | `configs/fullscale.yaml` | 64 × 3 = **192/cell** | §5 — the 10⁶ scaling check (deliberately lighter; not a source of headline numbers) |
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| `cover-traffic/` | `configs/cover-traffic.yaml` | 900 s timeline × 4 seeds | §3.10 — blending, mixing, and the emission-quota stake ceiling. Carries a fourth table, `traffic.parquet` |
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| `attribution/` | `configs/attribution.yaml` | closed-form + 4 seeds | §3.4 — the attribution bracket at the report's scale: local confidence, attributable fractions, upstream hops, neighbourhood confidence |
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| `timing/` | `configs/timing.yaml` | 120 s timeline × 3 seeds | §3.11 — the two release designs under a timing attack, and the minimum-interval control |
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The linkability results (§3.6–§3.7) and both deanonymization rates are closed forms over these
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tables rather than separate measurements, so they have no run of their own — `blend.linkability`
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derives them and `make verify` checks them against Monte-Carlo.
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## Regenerating the report's numbers
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```
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python report_numbers.py
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```
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prints every quoted value straight from the parquets here -- the §3.1–§3.5 and §3.8 tables with
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their across-topology standard errors, and the §3.9–§3.11 tables and the §3.4 attribution bracket
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from their own runs.
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That is the fastest way to check a table in the report against its evidence. It takes optional
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paths (`report_numbers.py <default> <redundancy> <percolation>`) if you want to point it at fresh
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runs instead.
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## Regenerating the data itself
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From [`tools/simulators/blend`](../../../tools/simulators/blend): `make sweep`,
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`make redundancy`, `make percolation`, `make correlated-churn`, `make sweep-fullscale`. Results
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land in that simulator's `runs/<timestamp>_<label>/`.
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**On exact reproduction.** Seed streams are derived from the configuration, so re-running a study
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reproduces its *statistics* rather than bit-identical numbers whenever that derivation has moved.
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It has moved once since these runs: adding failure domains (§3.9) put `n_regions` and
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`region_locality` into the topology seed, which changes the graph drawn for every config, including
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those leaving both at their defaults. `default/`, `percolation/` and `redundancy/` were produced
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before that change and so no longer reproduce bit-exactly — a spot-checked cell moved by 0.3 %,
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about 1.5 standard errors, which is ordinary variation between independent realisations rather than
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a change in behaviour. `correlated-churn/`, `cover-traffic/`, `fullscale/`, `timing/` and
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`attribution/` were produced by the current derivation. Quantities that are closed-form
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(`deanon_rate`, the quota ceiling, the confidence formulae) depend only on counts and are identical
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either way; the Monte-Carlo ones scatter within their stated error bars.
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Two runs from the same session are deliberately **not** kept: the smoke runs (throwaway, far too
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noisy to interpret) and an earlier 144-rounds/cell redundancy grid that was superseded because its
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sampling error produced a non-monotonic delivery curve — the reason `redundancy/` samples 9 600.
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