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Reproduction: Who Said Neural Networks Aren't Linear?

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Executive summary
Claim 1: Linearizer definition and induced linearity
Claim 2: Composition of Linearizers (Prop 2.5)
Claim 3: Idempotence iff A^2 = A (Lemma 4.2)
Claim 4: One-step flow matching via operator collapse
Claim 5: Modular style transfer via swappable core
Conclusion