Published April 28, 2026 | Version v1
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The 144-Lattice Partition Theorem: How the CTF Framework Found a New Result in Number Theory, and What It Means Inside the Framework

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Description: Investigation of the CTF base frequency f0=10373/72 f_0 = 10373/72 f0=10373/72 Hz under the mod-144 power sum framework led to the discovery of a partition theorem for prime power sums. The standalone mathematical result — proven without reference to the CTF Framework — is published separately (Gurwell, 2026b). This paper documents the discovery context and interprets the theorem’s structure within the CTF Framework.

The theorem states that S(p,k)=∑i=1p−1ikmod  144 S(p,k) = \sum_{i=1}^{p-1} i^k \mod 144 S(p,k)=i=1p1ikmod144 is independent of k k k for all odd k≥3 k \geq 3 k3 if and only if pmod  144 p \mod 144 pmod144 belongs to one of 32 residue classes, with lock values in {0, 1, 9, 64, 73, 81}. When the CTF prime set {11, 17, 19, 23, 41, 53} is used as the exponent family, the same 6-value partition emerges.

Within the CTF Framework the six lock values are not arbitrary: 0 corresponds to the static lattice (72 and 144 both lock here), 9 is the spatial generator (9×8=72 9 \times 8 = 72 9×8=72, 9×12=108 9 \times 12 = 108 9×12=108, 9×16=144 9 \times 16 = 144 9×16=144), 64 = 26 2^6 26 is the pure kinetic power, 81 = 34 3^4 34 is its spatial complement, and 73 = 72 + 1 is the CTF denominator plus unity. The sum 64+9=73 64 + 9 = 73 64+9=73 is exact.

The temporal numerator 10373 = 11 × 23 × 41, tested against its own constituent primes, produces residues 76, 76, 4 with difference 76 − 4 = 72. This self-referential structure is documented as a CTF-specific finding building on the partition theorem, including the 2² (Key of 4) and step difference in the temporal numerator self-residue profile.

The partition theorem provides a formal mathematical basis for the CTF Framework’s spatial/temporal distinction: universal lock classes map to static spatial constants while splitting classes correspond to dynamic temporal elements. All computations are reproducible with the appendix Python code using modular exponentiation.

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