Rational hitting lists: rectangular #
Adapted from OpenAI's formalization at revision adc7f1241b42e322a6451854ab7e4b4c146bf78a.
Source: https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/lean/OAI/Computability/RationalHitting/Rectangular.lean
Imports, namespaces, module visibility, documentation, and formatting are adapted for complexitylib. The source theorem statements and mathematical arguments are retained.
The ordinary Kronecker evaluation, with the two vector indices curried in reverse order. This is only a coordinate convention.
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Full-rank blocks preserve the dimension of a common input subspace; this form avoids any unwarranted specialization of Laurent-series coefficients.
The subspace spanned by the components of a vector.
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A component regarded as a vector in the component span.
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Coordinates of each component in a basis of their span.
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The output map of the wk possible component images.
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- Complexity.RationalHitting.Rectangular.imageCombination T u = Fintype.linearCombination F fun (ij : Fin w × Fin k) => (T ij.1) (u ij.2)
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The concatenated coefficient matrix.
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- Complexity.RationalHitting.Rectangular.concatMatrix A P α ij = (A ij.1 * P) α ij.2
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A kernel vector with sufficiently expansive component span contradicts any invertible block evaluation of the same coefficient matrices.
The block matrix obtained as a sum of Kronecker products.
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- Complexity.RationalHitting.Rectangular.blockMatrix A X = ∑ i : Fin w, Matrix.kroneckerMap (fun (x1 x2 : F) => x1 * x2) (A i) (X i)
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The rectangular Taylor tests have no nonzero kernel component family when the same coefficients have an invertible matrix witness.