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lambda_rec_is_root

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The theorem confirms that the curvature functional K vanishes at the recognition length. Researchers deriving constants non-circularly in Recognition Science cite it to anchor the balance condition before uniqueness arguments. The proof is a direct term-mode reduction that unfolds K, lambda_rec and ell0 then applies simp and ring.

claimThe curvature functional satisfies $K(lambda_rec) = 0$, where $K(lambda) = lambda^2 / lambda_rec^2 - 1$.

background

In the LambdaRecDerivation module the recognition length lambda_rec is set to ell0, which equals 1 in RS-native units. The curvature functional is defined by K(lambda) := lambda^2 / lambda_rec^2 - 1. This construction uses only the normalized bit cost and the curvature cost 2 lambda^2 from the Q3 Gauss-Bonnet normalization, without presupposing G; G is instead recovered afterward as pi lambda_rec^2 c^3 / hbar.

proof idea

The proof is a term-mode reduction. It unfolds the definitions of K, lambda_rec and ell0, applies simp to clear the power and division, and finishes with ring to obtain the identity 1 - 1 = 0.

why it matters in Recognition Science

The result is invoked by lambda_rec_is_forced to establish existence and uniqueness of the positive root. It supplies the explicit verification step in the non-circular derivation of lambda_rec described in the module documentation, confirming that the balance condition holds at the recognition length before G is defined as a consequence. Within the Recognition Science framework this anchors the constants block inside the eight-tick cycle where lambda_rec coincides with ell0.

scope and limits

formal statement (Lean)

  95theorem lambda_rec_is_root : K lambda_rec = 0 := by

proof body

Term-mode proof.

  96  unfold K lambda_rec ell0
  97  simp only [one_pow, div_one]
  98  ring
  99

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