How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Finite-bit Box–Muller with certified elementary-function evaluators
Definition
Input an integer bit budget , two disjoint ideal fair-bit subsequences as in
Disjoint streams of independent fair bits produce independent uniform variables, and a fixed deterministic
configuration consisting of finite dyadic format parameters, positive integer
series truncation indices and nonnegative integer total split budgets
for the log/root interval evaluators, positive dyadic log/root width
targets, and phase parameters with exact rational , integer exponent limits
, integer precisions ,
and a positive integer elementary-series cap . Every call uses
these fixed parameters; a failed call returns inconclusive with its supplier
status. No success at a requested width is promised for arbitrary fixed budgets.
The midpoint convention is Midpoint bit discretization has bounded coupling and CDF error, and
the exact reference transform is Box–Muller has a product Gaussian density and Rayleigh second moment.
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Take the first bits from each subsequence and form the exact dyadics . Enclose by directed dyadic endpoints in the selected format. If this is non-finite or its lower endpoint is not positive, return
inconclusive; underflow may not turn a log argument into an accepted interval containing zero. -
Apply Finite-budget validated range evaluation to the logarithm DAG on that interval with the configured finite parameters and log width target. On
certified(L,X), write and set , . The natural logarithm equals the integral logarithm by The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t, so . Compute the exact dyadic . -
Enclose by directed endpoints in the configured format; reject non-finite endpoints or a negative lower endpoint. Apply the same budgeted procedure to its square-root DAG with the root width target. On a certified interval , set and . The range guarantee of Budgeted range evaluation terminates and certifies only sound enclosures gives and . Width differences and the products in these instructions are exact dyadic arithmetic.
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Call Certified dyadic enclosures for unit-circle phases on the exact rational and configured phase parameters. On its certified return , set and . By Certified phase output encloses the exact unit-circle value, , including pi, angle, truncation and directed-endpoint errors. This is the existing phase routine, with its existing canonical-pi bridge.
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Return the exact dyadic vector and the dyadic certificates . If any preceding supplier call has a non-finite status, propagate it as
inconclusive. Final vector multiplication is exact dyadic multiplication; rounding it further requires a separate added error certificate.
The output is the dyadic vector together with the reported evaluator certificates. Its arithmetic suppliers provide neither an IID source nor exact normal output.
Depends on
- Disjoint streams of independent fair bits produce independent uniform variables
- Midpoint bit discretization has bounded coupling and CDF error
- Box–Muller has a product Gaussian density and Rayleigh second moment
- Finite-budget validated range evaluation
- Budgeted range evaluation terminates and certifies only sound enclosures
- Certified dyadic enclosures for unit-circle phases
- Certified phase output encloses the exact unit-circle value
- The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t
Used by
Dependency tree · two levels
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Sources
- Luc Devroye, Non-Uniform Random Variate Generation, Chapter V §4.4, generating normal random variates (standard reference, not scraped)
- E. M. Raz, Lecture Notes in Probability, Chapter 5, Exercise 5.2 (standard reference, not scraped)