flaukowski/kannaka-scientist-v1

No trained model yet. Every Kannaka Scientist model so far has failed its pre-registered go/no-go gate; see gates/gate_history.json.

What Kannaka Scientist is

A swappable Brain interface driving an ECDSA.fail knob-search harness: the loop repeats brain.propose(), scorer.score(), ledger.append() and brain.learn() against a fixed knob Space (space/ecdsa_knobs.json) until its budget is spent. random and tpe ship in this snapshot's code/scientist/brains/. ensemble -- the from-scratch model under test -- is not shipped here: it failed every gate it was run against (see Gate history below) and its code is parked, unpublished, on wip/* branches. See spec/design.md for the full architecture.

Gate history

Every go/no-go gate run for Kannaka Scientist v1, including failures; attempts are pre-registered unless marked diagnostic. Bar: beat random in >=8/10 seeds at a 40-config budget (V2 also requires >= TPE's count). Lower final score is better; 1.0 = the record.

ID	Date	Model	Scorer	Seeds	Result	Win counts	Cause / finding	Code commit
t5-mlp	2026-09-28	7 numpy MLPs (1x32 tanh, score+failure heads)	FakeScorer v1	100-109	FAIL	ensemble wins vs random=4; guard history blind wins=6	160 features vs 20-30 samples; members overfit (ensemble-mean corr ~0.035)	876a585 (branch wip/t5-gate-fail)
t5b-bayes-linear	2026-09-28	7 Bayesian linear regressors (empirical-Bayes alpha/beta) + L2 logistic failure head	FakeScorer v1	200-209	FAIL	ensemble wins vs random=4; guard history blind wins=1; old seeds 100 109 wins=4	beta hits its cap (noise-free fake, n < p); predictions track the true score only weakly	d48e932 (branch wip/t5b-gate-fail)
tpe-reference-v1	2026-09-28	Optuna TPE (reference, not our model)	FakeScorer v1	200-209	diagnostic	tpe wins vs random=5	FakeScorer v1 is unsearchable at 40 configs: every arm ends 0.97-0.99 while planted optima are 0.91-0.93	-
t5c-bayes-linear-v2	2026-09-28	7 Bayesian linear regressors + L2 logistic failure head (unchanged)	FakeScorerV2 (8 relevant knobs, smooth int bowls, noise 0.002)	300-309	FAIL	ensemble wins vs random=5; tpe wins vs random=7; guard history blind wins=6	does not learn from history within 40 configs (blind copy does as well); linear int features cannot represent bowls	d8314ed (branch wip/t5c-gate-fail; FakeScorerV2 lives there)

Every attempt above is FAIL except the Optuna TPE reference run, which is diagnostic (TPE is not our model). The full per-attempt detail, including per-seed final scores where recorded, is in gates/gate_history.json. The code_commit values above (the wip/* branches) are not public -- they are not part of this snapshot or this repo's public history; only the code under code/ here, at the commit named in MANIFEST.json, is published.

What is in this repo

• README.md -- this card.
• LICENSE and NOTICE -- the Space Child License, byte-identical to the source repo's.
• space/ecdsa_knobs.json -- the knob Space these attempts searched over.
• priors/ecdsa_history.jsonl and priors/ecdsa_history.counts.json -- the mined public-submission history prior (facts about public submissions only).
• gates/gate_history.json -- every gate attempt, including one non-pre-registered TPE diagnostic, compiled from the recorded counts; the failures are included.
• threat_ledger/ -- the BQR threat ledger's first artifact: the ECDSA.fail record curve (CSV, chart, methods note); see Threat ledger below.
• spec/design.md -- the design spec these attempts were run against.
• code/ -- a snapshot of scientist/, tools/, pod/, tests/ and pyproject.toml at the published commit (git archive HEAD; only committed code, never the working tree).
• MANIFEST.json -- the git commit, build time, sha256 of every file above, and "model": null.

History-prior caveat

The history miner examined 1,307 submissions; 21 rows mined; 6 usable within k=3. Public submissions also changed code, not just knobs, so a history row's score reflects code and knobs -- the prior is a head start, not ground truth (history rows are down-weighted 0.3 against 1.0 for our own scored runs). Mapping each mined row onto this Space and dropping any that change more than k=3 knobs leaves the 6 usable rows.

Threat ledger

The BQR threat ledger tracks progress on the ECDSA.fail benchmark, under its rules (approximate circuits allowed; average executed Toffoli x peak qubits), measured from the benchmark's first record. The benchmark's task is one secp256k1 elliptic-curve point addition as a reversible quantum circuit. As of 2026-09-28T16:15Z, it covers 533 promoted records:

• First record (2026-05-30): score 10,753,444,395 (3,960,753 Toffoli x 2,715 qubits)
• Latest record (2026-09-28): score 1,111,307,500 (889,046 Toffoli x 1,250 qubits)
• Factor: the latest record's score is 9.7x below the first record's.

Progress on this benchmark, under its rules (approximate circuits allowed; average executed Toffoli x peak qubits, over 9024 Fiat-Shamir shots), measured from the benchmark's first record. Each record is the best publicly verified cost of this one sub-circuit (one secp256k1 point addition) under the benchmark's rules; a full attack costs more, and better unpublished circuits may exist. This is not a full attack, and it gives no break date.

See threat_ledger/ for the CSV, the chart and the methods note.

What's next

• e001 (Track A, registered, not yet run): arms tpe, random x seeds 1, 2 at a budget of 30 configs per arm and seed (120 configs total). The Brain slot runs tpe, a standard tuner, while Kannaka Scientist has no model that passes its gate; the purpose is to find ECDSA.fail knob configs that beat the record, not to demonstrate our own model.
• Track B (laptop only, never on the Lab): a further from-scratch model attempt, gated on fresh FakeScorerV2 seeds 400-409 against the same bar (>=8/10 vs random, and >= TPE's count), openly labelled as shaped by knowing V2's structure.
• e001's results (and Track B's, if it passes its gate) are added to this repo after Nick's go. A model, if one ever passes its gate, goes to a Hugging Face model repo of the same name.

Licence

Space Child License v1.0 -- free for peaceful use, war pays. See LICENSE and NOTICE.

The Space Child License covers our own code, docs and results. The ECDSA.fail-derived data (submission knob tables, official metrics, upstream context in the patch) belongs to the ECDSA.fail benchmark (Layr-Labs/ecdsafail) and its submitters, and is reproduced for research with credit.