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arxiv: 2603.21852 · v2 · submitted 2026-03-23 · 💻 cs.SC · cs.LG

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All elementary functions from a single binary operator

Andrzej Odrzywo{\l}ek

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classification 💻 cs.SC cs.LG
keywords elementaryfunctionsbinaryoperationsoperatorsingledataexact
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A single two-input gate suffices for all of Boolean logic in digital hardware. No comparable primitive has been known for continuous mathematics: computing elementary functions such as sin, cos, sqrt, and log has always required multiple distinct operations. Here I show that a single binary operator, eml(x,y)=exp(x)-ln(y), together with the constant 1, generates the standard repertoire of a scientific calculator. This includes constants such as e, pi, and i; arithmetic operations including addition, subtraction, multiplication, division, and exponentiation as well as the usual transcendental and algebraic functions. For example, exp(x)=eml(x,1), ln(x)=eml(1,eml(eml(1,x),1)), and likewise for all other operations. That such an operator exists was not anticipated; I found it by systematic exhaustive search and established constructively that it suffices for the concrete scientific-calculator basis. In EML (Exp-Minus-Log) form, every such expression becomes a binary tree of identical nodes, yielding a grammar as simple as S -> 1 | eml(S,S). This uniform structure also enables gradient-based symbolic regression: using EML trees as trainable circuits with standard optimizers (Adam), I demonstrate the feasibility of exact recovery of closed-form elementary functions from numerical data at shallow tree depths up to 4. The same architecture can fit arbitrary data, but when the generating law is elementary, it may recover the exact formula.

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Cited by 5 Pith papers

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  1. Additive Atomic Forests for Symbolic Function and Antiderivative Discovery

    cs.LG 2026-05 unverdicted novelty 7.0

    A derivative algebra with EML and SOL primitives plus additive atomic forests enables simultaneous symbolic recovery of functions and antiderivatives from data, matching or exceeding XGBoost on 13 of 17 benchmarks wit...

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    EML operator serves as a grammar to generate single-block activation-suppression modules that produce non-monotone dynamics in reduced biological ODEs, matching data on PKA-R and Rho-GTPase systems.

  3. Inexpressibility in Exp-Minus-Log

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    In the Exp-Minus-Log system every expressible number is computable and Chaitin's Ω_U is inexpressible.

  4. Algebraic structure behind Odrzywo{\l}ek's EML operator

    math-ph 2026-04 unverdicted novelty 6.0

    The EML operator forms an abelian group with functional inverses, giving a constructive algebraic route to many distinct families of transcendental elementary functions via binary trees.

  5. Why Architecture Choice Matters in Symbolic Regression

    cs.NE 2026-04 unverdicted novelty 6.0

    Different fixed tree architectures in gradient-based symbolic regression produce dramatically different recovery rates, with more expressive structures sometimes failing where restricted ones succeed reliably.