Technical Credibility — FAQ
Layer 3 — technical credibility questions: TauLib, Lean, custom axioms, build reproduction.
Layer 3 · Technical Credibility
TauLib, Lean, Release Manifest, sorry, custom axioms, TCB, Mathlib, build reproduction.
20 entries · last reviewed 2026-05-09 · version v0.1-pilot
What does “machine-checked in Lean” mean here?
It means encoded formal statements compile under the pinned Lean environment, relative to Lean’s trusted kernel, disclosed assumptions, and current TauLib snapshot.
Machine-checked does not mean every prose claim is verified. It means the Lean-encoded theorem or obligation is accepted by the proof checker under the disclosed environment and trust budget.
Does TauLib prove the physical claims?
No. TauLib verifies formal obligations where encoded; it does not by itself prove empirical truth, bridge adequacy, semantic correspondence, or external scientific acceptance.
Lean can check encoded derivations. It cannot by compilation alone prove that a τ-internal object corresponds to a physical observable, that a measurement bridge is adequate, or that a numerical match validates the framework.
What is the current formalization snapshot?
The current Release Manifest reports 512 Lean modules, 142,406 lines, 4,863 theorem/lemma declarations, 0 sorry assignments, and 3 custom axiom declarations.
The Release Manifest is the authoritative current snapshot for release metrics and pins source revision, Lean version, Mathlib version, counts, custom axioms, and sorry status. Other pages should render those facts from the manifest.
What is a `sorry`, and why does 0 `sorry` matter?
In Lean, `sorry` is a placeholder for an unfinished proof. A 0-sorry release means no explicit unfinished-proof placeholders remain in the pinned TauLib source.
A `sorry` can temporarily accept a theorem without proof. A 0-sorry release is meaningful formalization hygiene, while still not proving bridge adequacy or empirical truth.
Does 0 `sorry` mean the theory is true?
No. It means the formalized Lean proofs have no explicit unfinished-proof placeholders; it does not settle bridge, semantic, empirical, or external-review questions.
A 0-sorry Lean development is stronger than one with placeholder proofs, but it is not a truth certificate for the whole research program. The encoded statements, correspondence to prose, bridge claims, and domain claims remain separate burdens.
What are the custom axioms?
They are three explicit TauLib axiom declarations beyond Mathlib’s trusted base, all located in Book III spectral / number-theoretic bridge territory.
A custom axiom is accepted without being proved inside Lean. The site treats the three custom axioms as visible debts, with inventory pages explaining rationale, scope, and review burden.
Are the custom axioms hidden?
No. They are exposed through the Release Manifest, Custom Axiom Inventory, TauLib source, and `#print axioms` audit route.
Reviewers should inspect axiom declarations, run `#print axioms` on downstream declarations, and check whether theorem status labels reflect custom-axiom dependence.
What does “compute-then-axiomatize” mean?
It means a universal claim is finite-checked over an explicit computable envelope, but the unbounded universal step is still declared as an axiom rather than proved.
This pattern is explicit debt, not proof. It is acceptable only if named, bounded, reproducible, load-bearing, and reflected in downstream scope labels.
What is `#print axioms`, and why does it matter?
`#print axioms` is a Lean audit command that shows which axioms a declaration depends on, including custom axioms or `sorryAx` where present.
It helps distinguish theorem statements that are fully proven under the disclosed base from statements that depend on classical axioms, custom axioms, native computation trust, or placeholder proof artifacts.
What is the trusted computing base?
The trusted computing base is the underlying machinery a Lean proof depends on: Lean’s kernel, standard axioms, and any disclosed extensions such as `native_decide`.
No proof assistant verifies itself from nothing. The question is whether the trust base is disclosed, bounded, and auditable. TauLib’s TCB page names the Lean baseline and native computation costs.
What is `native_decide`, and why is it a trust issue?
`native_decide` proves decidable propositions by native computation; it is powerful, but it extends the trusted base beyond purely kernel-reduced proof terms.
`native_decide` is useful for finite computations, but it depends on native compilation/evaluation. The site should treat it as a named trust-budget extension, not hidden magic.
Does TauLib import Mathlib mathematics as its object-level foundation?
The Release Manifest states that Mathlib is used for tactics only and that TauLib does not import Mathlib mathematical content as the object-level foundation.
The precise claim is code-level and should be audited through imports and dependencies. Lean/Mathlib tooling is used, but τ object-level content is intended to be constructed internally rather than imported as mathematical semantics.
What is the Release Manifest?
The Release Manifest is the authoritative snapshot of the current public release: pinned source revision, Lean/Mathlib versions, counts, axioms, sorry status, and boundaries.
If public numbers differ, the Release Manifest determines which count is load-bearing and which filter rule is being used. It is the source of truth for release-state facts.
Why do counts sometimes differ between Registry, dashboards, and TauLib?
They count different units with different filter rules: registry objects, dashboard-display objects, formalized dashboard objects, Lean modules, and direct `sorry` counts.
Registry objects are not Lean modules. Dashboard totals are filtered views. Formalized counts apply status filters. `sorry` count is a source scan. The first question is always which filter rule each page uses.
What is the difference between the Registry and TauLib?
The Registry is the object/dependency map of the Corpus; TauLib is the Lean formalization projection of selected formal content.
A registry object is a stable public ID for a Corpus item. A TauLib module is a Lean source file. The meaningful audit question is whether claimed mappings between Registry, Corpus, and TauLib are explicit and inspectable.
How can I reproduce the TauLib build?
Use the pinned TauLib commit and Lean/Mathlib versions from the Release Manifest, then run `lake build` and verify that `rg "sorry" TauLib` returns no matches.
Treat the pinned commit as authoritative, not a moving branch. A failed build or unexpected `sorry` is a serious reproducibility issue.
Does every Result page have a Lean proof?
No. Results are consequence surfaces with status labels; some have formal support, some are bridge claims, some are empirical, and some remain interpretive or domain-level.
A Result page is not automatically a Lean theorem. The right question is status, Corpus support, formalized component, bridge burden, and external validation route.
What remains bridge-pending?
Any claim that transfers from τ-internal formal structure to standard mathematics, physics, biology, metaphysics, measurement, or public impact needs a separate bridge check.
Bridge adequacy asks whether a τ-internal construction legitimately transfers to the external target. The site should keep internal proof, bridge claim, and domain validation visibly separate.
What is the fastest technical audit path?
Start with the Release Manifest, reproduce the pinned build, scan for `sorry` and `axiom`, then run `#print axioms` on selected hinge theorems.
A fast audit should confirm commit, build, Lean/Mathlib pins, source scans, custom axioms, TCB disclosure, and theorem dependency traces before inspecting prose correspondence.
What would count as a serious formalization failure?
A failed pinned build, unexpected `sorry`, undisclosed custom axiom, broken dependency trace, or mismatch between formal theorem and public prose would all be serious failures.
Such failures may require correction, retraction, relabeling, or narrowing. They do not all necessarily destroy the entire program, but they must update status labels and public artifacts.
Read next
- Expert Handoff — Layer 4: which expert to call, what packet to send
- Verify — verification framework, formalization stack, release manifest
- TauLib — formalization status surface
- Release Manifest — current quantitative facts
- How to Verify — by reviewer role