Transcending the Forbidden through Executable Ternary Logic: A Formal Experimental Study
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Many mathematical expressions are deemed undefined or forbidden in conventional binary logic—division by zero, the square root of negative numbers, and indeterminate forms like 0⁰ or ∞–∞. These are not necessarily invalid operations, but rather cases that binary logic is not equipped to handle. This paper explores how a computable ternary logic model, previously formalized in [1][2], can reinterpret such expressions as valid, non-fatal logical states.
We analyze the limitations of existing logical systems, including three-valued and fuzzy models, and propose a structured ternary system capable of encoding forbidden expressions without contradiction. Using this system, undefined forms are mapped to explicit logical states (e.g., DIV, NROOT, ZEREX) associated with trits, a logic unit with three stable states.
A series of executable demonstrations are presented using Python and HTML code snippets, illustrating how each forbidden operation can be processed logically rather than rejected outright. This approach does not discard binary computation, but rather proposes a second-order logic layer that expands its expressive capacity.
The study offers a pathway toward error-resilient computation, more realistic AI decision-making, and a foundational reconsideration of the boundary between the computable and the impossible.
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Primary Research Articles (Authored by the Authors)
1. Fellouri, A., & Adjailia, M. (2025)."Beyond Binary: Logical DNA and Minimal Information Recovery through the K3L Paradigm. SSRN, ID: 5297799 Referenced in Sections: Abstract, 2.1, 3.4, 5.5, 6, Conclusion
2. Fellouri, A., & Adjailia, M. (2025) "Novel Trit-Based Logic Model for Signal Processing and Memory Systems."HAL, ID: hal-05104397v1Referenced in Sections: Introduction, 2.2, 3.1–3.3, 4, 5.1–5.4, 7
Contextual and Related Scientific Sources
3. Kaye, R., & Wilson, R. (1991) Mathematical Logic. Oxford University Press. Referenced in: Section 3.1 – Comparison to binary logic assumptions.
4. Knuth, D. E. (1997). The Art of Computer Programming, Vol. 1: Fundamental Algorithms. Addison-Wesley. Referenced in: Section 4.2 – Binary limitation and control flow examples.
5. Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379–423. Referenced in: Section 5.3 – Entropy, information theory, and K3L encoding impact.
6. Svozil, K. (1995).Quantum Logic. Springer. Referenced in: Section 5.7 – Ambiguity and forbidden operations.
7. Ternary Computing Project (TCI) – Tokyo Institute of Technology (Archived 2002). Referenced in: Section 2.3 – History of ternary systems and failure of adoption.
8. Young, T. (1801).Double-Slit Interference Experiment. Royal Society Archives. Referenced in: Section 5.6 – Physical analogs of ambiguity.
9. Schrödinger, E. (1935). The Present Situation in Quantum Mechanics. Proceedings of the American Philosophical Society. Referenced in: Section 5.6 – Conceptual superposition and ambiguity modeled by X.
10. IEEE Standard for Floating-Point Arithmetic (IEEE 754-2019).Referenced in: Section 5.2 – Division by zero, NaN, and undefined behavior.
Supplementary Demonstration Tools
11. HTML5 W3C Specification – Compression and Canvas API.Referenced in: Section 5.5 – HTML examples and visualization.
12. Python REPL environments – Logic gate simulation tools.Used for internal test cases (appendices, if included).
Copyright (c) 2025 Abdelkrim Fellouri, Adjailia Meriem

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