All elementary functions from a single binary operator
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 9 of its 56 references that are in the map. First posted on arXiv 23 Mar 2026.
Builds on
9 of 56 references.
References · 9
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Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026EML Trees Are Universal Approximatorscited by 1
- 2026Auto-Relational Reasoningcited by 0
- 2026Additive Atomic Forests for Symbolic Function and Antiderivative Discoverycited by 0
- 2026EML-CD: Causal Mechanism Recovery via EML Symbolic Trees in Structure Learningcited by 0
- 2026Diversity of EML-type operatorscited by 0
- 2026Diversity of EML-type operators10 Sep 2026
- 2026EML Trees Are Universal Approximators22 Jun 2026
- 2026EML-CD: Causal Mechanism Recovery via EML Symbolic Trees in Structure Learning4 Jun 2026
- 2026Additive Atomic Forests for Symbolic Function and Antiderivative Discovery1 May 2026
- 2026Auto-Relational Reasoning29 Apr 2026