Finite, repeatedly rounded binary sums #
Each internal node uses Model.add, with one nearest-even rounding at that node. A finite
execution certificate excludes exceptional inputs and overflow at every intermediate result.
The error budget then follows from FloatLib's half-ULP theorem, including subnormal values.
This API does not change Model.sum, which accumulates exactly and rounds only once.
All leaves and intermediate additions have real denotations.
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Finiteness of the root is part of a finite execution certificate.
The rounded real interpretation agrees with encoded execution at each finite node.
The sum of half-ULPs at the actual intermediate additions.
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No normal-range hypothesis is needed: each finite addition has an absolute half-ULP bound.
Two finite schedules over the same inputs can differ by at most their combined budgets.