Toward P vs NP: An Observer-Theoretic Separation via SPDP Rank and a ZFC-Equivalent Foundation within the N-Frame Model
Darren J. Edwards

TL;DR
This paper introduces a novel ZFC-based framework that uses SPDP rank and a new complexity measure called CEW to theoretically separate P from NP, providing a rigorous foundation for the P vs NP problem.
Contribution
It develops a self-contained, formal separation framework within ZFC that connects SPDP rank, CEW, and computational complexity, offering a new approach to P vs NP.
Findings
Bounded CEW observers correspond to P, unbounded CEW to NP.
Exponential SPDP rank for #3SAT implies P != NP.
Constructive lower bounds on SPDP rank using Ramanujan-Tseitin expanders.
Abstract
We present a self-contained separation framework for P vs NP developed entirely within ZFC. The approach consists of: (i) a deterministic, radius-1 compilation from uniform polynomial-time Turing computation to local sum-of-squares (SoS) polynomials with polylogarithmic contextual entanglement width (CEW); (ii) a formal Width-to-Rank upper bound for the resulting SPDP matrices at matching parameters; (iii) an NP-side identity-minor lower bound in the same encoding; and (iv) a rank-monotone, instance-uniform extraction map from the compiled P-side polynomials to the NP family. Together these yield a contradiction under the assumption P = NP, establishing a separation. We develop a correspondence between CEW, viewed as a quantitative measure of computational contextuality, and SPDP rank, yielding a unified criterion for complexity separation. We prove that bounded-CEW observers…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Polynomial and algebraic computation
