Exact Fourier circuits: stream series #
Adapted from OpenAI's formalization at revision adc7f1241b42e322a6451854ab7e4b4c146bf78a.
Source: https://github.com/openai/math/blob/adc7f1241b42e322a6451854ab7e4b4c146bf78a/lean/OAI/Computability/FourierCircuit/StreamSeries.lean
Imports, namespaces, module visibility, documentation, and formatting are adapted for complexitylib. The source theorem statements and mathematical arguments are retained.
The formal matrix series whose coefficient of degree m is D^m.
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- Complexity.ExactFourier.CellSeries.resolvent D i j = PowerSeries.mk fun (m : ℕ) => (D ^ m) i j
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The formal response from the cell's state coordinates to its output coordinates.
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The formal transfer matrix of one cell, including its delayed state feedback.
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Execute the same cell at successive times while carrying its state between inputs.
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- One or more equations did not get rendered due to their size.
- Complexity.ExactFourier.CellStream.run K 0 = 1
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Reassociate data and state coordinates for composing along a common data axis.
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Compose two cells along their common data coordinates while retaining both state blocks.
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- One or more equations did not get rendered due to their size.
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Regroup a right tensor lift so that time is the leading coordinate.
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- Complexity.ExactFourier.TimeLifts.rightEquiv t = (Equiv.sumProdDistrib (Fin t × σ) ρ α).trans ((Equiv.prodAssoc (Fin t) σ α).sumCongr (Equiv.refl (ρ × α)))
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Regroup a left tensor lift so that time is the leading coordinate.
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- Complexity.ExactFourier.TimeLifts.leftEquiv t = (Equiv.prodSumDistrib σ (Fin t × α) β).trans ((Complexity.ExactFourier.TimeLifts.timeSwap t).sumCongr (Equiv.refl (σ × β)))
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Tensor a timed computation on the right with an identity and restore time-first order.
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- One or more equations did not get rendered due to their size.
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Tensor a timed computation on the left with an identity and restore time-first order.
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- One or more equations did not get rendered due to their size.
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The recursive coordinate space for a tensor power.
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The auxiliary call fibers accumulated by the recursive tensor construction.
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The tensor power of a square matrix on the recursive coordinate space.
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- Complexity.ExactFourier.TensorAxis.power A 0 = 1
- Complexity.ExactFourier.TensorAxis.power A t.succ = Matrix.kroneckerMap (fun (x1 x2 : R) => x1 * x2) (Complexity.ExactFourier.TensorAxis.power A t) A