Differential Logic • 16

Propositions and Tacit Extensions

Now that we’ve introduced the field picture as an aid to visualizing propositions and their analytic series, a pleasing way to picture the relationship of a proposition f : X \to \mathbb{B} to its enlargement or shift map \mathrm{E}f : \mathrm{E}X \to \mathbb{B} and its difference map \mathrm{D}f : \mathrm{E}X \to \mathbb{B} can now be drawn.

To illustrate the possibilities, let’s return to the differential analysis of the conjunctive proposition f(p, q) = pq and give its development a slightly different twist at the appropriate point.

The proposition pq : X \to \mathbb{B} is shown again in the venn diagram below.  In the field picture it may be seen as a scalar field — analogous to a potential hill in physics but in logic amounting to a potential plateau — where the shaded region indicates an elevation of 1 and the unshaded region indicates an elevation of 0.

Proposition pq : X → B
\text{Proposition}~ pq : X \to \mathbb{B}

Given a proposition f : X \to \mathbb{B}, the tacit extension of f to \mathrm{E}X is denoted \boldsymbol\varepsilon f : \mathrm{E}X \to \mathbb{B} and defined by the equation \boldsymbol\varepsilon f = f, so it’s really just the same proposition residing in a bigger universe.  Tacit extensions formalize the intuitive idea that a function on a given set of variables can be extended to a function on a superset of those variables in such a way that the new function obeys the same constraints on the old variables, with a “don’t care” condition on the new variables.

The tacit extension of the scalar field pq : X \to \mathbb{B} to the differential field \boldsymbol\varepsilon (pq) : \mathrm{E}X \to \mathbb{B} is shown in the following venn diagram.

Tacit Extension ε(pq) : EX → B
\text{Tacit Extension}~ \boldsymbol\varepsilon (pq) : \mathrm{E}X \to \mathbb{B}

\begin{array}{rcccccc}  \boldsymbol\varepsilon (pq)  & = &  p & \cdot & q & \cdot &  \texttt{(} \mathrm{d}p \texttt{)}  \texttt{(} \mathrm{d}q \texttt{)}  \\[4pt]  & + &  p & \cdot & q & \cdot &  \texttt{(} \mathrm{d}p \texttt{)}  \texttt{~} \mathrm{d}q \texttt{~}  \\[4pt]  & + &  p & \cdot & q & \cdot &  \texttt{~} \mathrm{d}p \texttt{~}  \texttt{(} \mathrm{d}q \texttt{)}  \\[4pt]  & + &  p & \cdot & q & \cdot &  \texttt{~} \mathrm{d}p \texttt{~}  \texttt{~} \mathrm{d}q \texttt{~}  \end{array}

Resources

cc: Academia.eduCyberneticsLaws of Form • Mathstodon (1) (2)
cc: Research GateStructural ModelingSystems ScienceSyscoi

#amphecks, #animata, #boolean-algebra, #boolean-functions, #c-s-peirce, #cactus-graphs, #change, #cybernetics, #differential-calculus, #differential-logic, #discrete-dynamics, #equational-inference, #functional-logic, #gradient-descent, #graph-theory, #inquiry-driven-systems, #logic, #logical-graphs, #mathematics, #minimal-negation-operators, #propositional-calculus, #time, #visualization