# What Math Really Is

There is an almost ubiquitous misconception about what mathematics really is, and it’s a misconception that genuinely beckons a correction.  I would take a guess that if the average person was asked “What is mathematics?”, they would respond with something along the lines of “well, it’s a bunch of rules that help you find certain numbers”.  While this may have been a correct answer long ago, it is far from correct today.

Fortunately, what it actually is can be summarized very succinctly.  Mathematics is simply the process of making assumptions and proving what follows.  Hence, we all do math on a daily basis—either when talking to one another, or when thinking to oneself:  “given what I know, I think that…”.  This is math.

This is also why math courses through calculus are terrible—as they are absurdly misleading.  Current curriculum is libelous to the discipline of mathematics and its participants, and action needs to be taken to address this.

At this point, high school language arts and composition courses may teach more math than actual math courses.  Fundamental to mathematics is logic and its application in the context of sets.  Logic was essentially nonexistent when I was in high school.  Yet math and language arts classes implicitly assume that students have a solid understanding of it when they are asked to make arguments.  Granted, as we are logical entities cognitively, we are trivially masters of logic.  But in terms of conveying it communicably, improved training is necessary.  I feel the overlooking of this necessity is a grave miscalculation that has hindered scientific thinking (an ability from which every citizen of the world can drastically benefit) for far longer than it should have.  This needs to change.

# Fuzzy Logic

Recall the definition of an $n$-ary logic system as a homomorphism $\varphi:F[X]\to V$ with $X$ a theory, $F$ a structure, and $V$ a structure of cardinality $n$ such that $F$ and $V$ have the same signature.  Fuzzy logic is hereby defined as the study of $c$-ary logic systems where $c$ is the cardinality of the continuum.  In this sense propositions can be thought of as having valence values in some interval, like $[0,1].$  So classical binary boolean logic is a type of fuzzy logic, where $\mbox{ran}\,\varphi=\{0,1\}.$

Example 1.  Recall in our construction of a utilitarian set we had a set $X$ together with a utility function $u:X\to [-1,1).$  Now suppose $T$ is a set of terms which is also a utilitarian set.  Suppose we define a structure $F$ on $T/\sim_u$ by

$\displaystyle [x]\vee [y]=u'^{-1}\left(\min\{u'[x],u'[y]\}\right)=u'^{-1}\left(\min\{u(x),u(y)\}\right)$

$\displaystyle [x]\wedge [y]=u'^{-1}\left(\max\{u'[x],u'[y]\}\right)=u'^{-1}\left(\max\{u(x),u(y)\}\right).$

This structure has signature $(0,0,2,0,...).$  Then $T/\sim_u$ is also a set of terms, with certain terms in $T$ identified, and if $X$ is a theory/subset in $T/\sim_u,$ then $u':F[X]\to [-1,1)$ is a $c$-ary logic system where $[-1,1)$ has the min and max operations.

In the case of Example 1, if we think of the set $T$ of terms as a set of behaviors, which could be construed as terms of persons (acting as words), then the structure $F[X]$ can be interpreted as equivalence classes of compound behaviors that yield the same utility where logical valence of compound behaviors is simply based on their utility.

Since the valence set in a fuzzy logic system is an interval, let us look at some common structures on $[0,1]$ to discuss some intuitive structures on terms.  We already mentioned min and max functions and a corresponding structure on class utilitarian sets.  $[0,1]$ is closed under binary multiplication.  The corresponding binary connective would thus send two propositions to a proposition whose valence is a product of the original two.  Treating binary boolean logic as a fuzzy logic, propositional conjunction satisfies this condition.

Example 2.  Let $(X,\Sigma,P)$ be a probability space.  Let $[0,1]$ be closed under addition where any sum exceeding $1$ is defined as $1$ and define a unary operation by $r^{-1}=1-r.$ Now note that $\Sigma$ is closed under union and complementation; denote this structure on $\Sigma$ by $F.$  If measurable sets are construed as formulas, select a theory $X$ of disjoint sets.  Then $P:F[X]\to [0,1]$ is a fuzzy logic system.

# Some Mathematical Misconceptions

1.  Math isn’t useful.
Quite the contrary.  As math is fundamental to all knowledge, developments in it trickle down to economics, physics, and computer science.  From there they make their way into business and political decision making, chemistry, biology, engineering, and then onto the social sciences.  Thus it may not be immediately useful; rather, it is a long-term investment whose payoff is slowest in return, but greatest in magnitude.

2.  Math is just arithmetic:  numbers and computation.
It’s no surprise that this conception exists given high school and lower division curriculum that strictly emphasize this.  While computation is an integral component to math, it is merely the mechanism by which genuine math is done.  Math is the epitome of science:  it simply consists of making assumptions and proving what follows (computation is the process generating the proof).  Of course one hopes the assumptions made do not contradict eachother–otherwise anything is provable (at least in traditional binary logic).  In this sense, any experiment is math, with assumptions being hypotheses and results being true if they are consistent with the hypotheses.  Even the practice of law is math, with assumptions being “people follow laws for all laws”, and true/false therefore coinciding with legal and illegal behaviors.  Everyday decision making of individuals (and hence social science) is math:  the assumptions being “biological predispositions and existence of a well-ordering of a set of possible decisions under given circumstances” and true decisions coinciding with those that are optimal (in the sense of the ordering).

3.  Humans don’t have to be mathematical.
This is actually a contradiction.  The human body in fact can be thought of as nothing more than a computer whose hardware is biology (even though our biology is soft/flimsy material–hopefully due for a big upgrade in the upcoming centuries) and whose software is a bundle of cognitive schemas.  Mathematically, we simply have that the assumptions are the hardware and arbitrary software installed at a later point, and the true consequences are just the perceptions that are consistent relative to the hardware and software (versus the false ones which are not).  For what we conventionally call a computer, the software is installed by humans.  For humans, the software is installed by the environment.  Sometimes the software itself may contradict the hardware–or other software for that matter.  Statements (computations) that follow which are in contradiction to the assumptions (hardware/other software) can lead to run on and halting problems (or in the case of humans, perceptions/schemas contradicting other schemas or hardware, possibly leading to psychological disorders).

4.  Any statement is either true or false.
This statement is (naively)false and undecidable.  The (meta)assumptions we have made so far are that true statements are simply those that follow from (direct)assumptions, and false statements are those whose negation follows from the (direct)assumptions.  Given those (meta)assumptions, the statement is (naively)false since the lack of (direct)assumptions (naively)contradicts the (meta)assumptions.  If a statement or its negation do not follow from a set of assumptions, we say it is undecidable/independent with respect to that set of assumptions.  Since we made no (direct)assumptions regarding statement 4, it is undecidable.

# Fundamental Knowledge-Part 2: Models

The next task is to absorb the traditional area of mathematical logic.  One key missing ingredient is a model.  Let us recall the traditional setup (taken from [1]).

Definition 2.1.  Let $S$ be a set (of symbols).  An $S$-structure is a pair $\mathfrak{A}=(A,\mathfrak{a})$ where $A$ is a nonempty set, called a universe, and $\mathfrak{a}$ is a map sending symbols to elements, functions, and relations of $A$.  An assignment of an $S$-structure $(A,\mathfrak{a})$ is a map $\beta:S\to A$.  An $S$-interpretation is a pair $\mathfrak{I}=(\mathfrak{A},\beta)$ where $\mathfrak{A}$ is an $S$-structure and $\beta$ is an assignment in $\mathfrak{A}$.

For shorthand notation, the convention (with some of my modifications) is to write:  $c^\mathfrak{A}=\beta(c)$, $(f(t_1,...,t_n))^\mathfrak{A}=\mathfrak{a}(f)(\beta(t_1),...,\beta(t_n))$, and $(xRy)^\mathfrak{A}=\beta(x)\mathfrak{a}(R)\beta(y)$.  These are the terms.  Formulas are then built from the terms using traditional (although this can be generalized) logical connectives.

The notion of a model is then defined via induction on formulas.

Definition 2.2.  Let $\mathfrak{I}=(\mathfrak{A},\beta)$ be an $S$-interpretation.  We say that $\mathfrak{I}$ satisfies a formula $\phi$ (or is a model of $\phi$), denoted $\mathfrak{I}\vDash\phi$, if $\phi^\mathfrak{A}$ holds, where $\phi^\mathfrak{A}$ is defined via its components and $\beta$ and $\mathfrak{a}$ where necessary.

Formal languages in convention are built up from the formulas mentioned above, which are nothing more than special cases of Alt Definition 1.3.  A model for a language is hence nothing more than an $A$-interpretation into a structure, where $A$ is an alphabet (provided it is equipped with a logic system).  This is precisely what I have constructed in Part 1;  the symbols of $W\subset A^*$ are mapped to the universe $\mathcal{L}_{F,T,W}$.  The next thing to establish is that every model is a language model.  This is trivial since a model by definition satisfies a set of formulas as well as compounds of them (i.e. it must satisfy a language).  Hence we have no need to trouble ourselves with interpretations and may simply stick to the algebra of Part 1.

While we have absorbed model theory, there are a few more critical topics to absorb from mathematical logic. We return to the language of Part 1 (no pun).  Let $X$ be a theory of $\mathcal{L}_{F,T,W}$ and $\varphi:F[X]\to V$ be a binary logic system.  A formula $\phi\in\mathcal{L}_{F,T,W}$ is derivable in $X$ if it is a proposition (i.e. is in $F[X]$).  We may write $X\vdash\phi$.  This definition is in complete agreement with the traditional definition (namely, there being a derivation, or finite number of steps, that begin with axioms and use inference rules);  it is nothing more than saying it is in $F[X]$.  Similarly $\phi\in\mathcal{L}_{F,T,W}$ is valid if $\varnothing\vdash\phi$, or equivalently, it is derivable in any theory.  In our setup this would imply $\phi\in F[\varnothing]=\varnothing$.  Hence no formula is valid.

Let $F$ have a unary operation $\lnot$ and $\varphi:F[X]\to V$ be a logic system on a theory $X$.

If we assume $\lnot$ to be idempotent ($\lnot\lnot\phi=\phi$), then since $\varphi$ is a homomorphism, we have $\varphi(\phi)=\varphi(\lnot\lnot\phi)=\lnot\lnot\varphi(\phi)$.  That is, the corresponding unary operation in $V$ must also be idempotent on $ran(\varphi)$.

Definition 2.3.  A unary operation $\lnot$ (not necessarily idempotent) is consistent in $\varphi$ if for all $\phi\in F[X]$, $\varphi(\phi)\neq\varphi(\lnot\phi)$.

If we assume $\lnot$ is consistent in $\varphi$ and that $\varphi$ is a binary logic system, then the corresponding $\lnot$ in $V$ is idempotent since

$\varphi(\phi)=0\Rightarrow\varphi(\lnot\phi)=1\Rightarrow\varphi(\lnot\lnot\phi)=\lnot\lnot\varphi(\phi)=0$.

Again, proofs in a binary system are independent of the choice of valence.   If we assume consistency and idempotency, then we have a nonidentity negation which is idempotent on the range.  The case for assuming binary system and idempotency yields either a trivial mapping of propositions (all to $0$ or all to $1$), or that $\lnot$ is consistent and idempotent on $V$.  And lastly if we assume all three (idempotency and consistency of $\lnot$ together on a binary system), we obtain a surjective assignment with idempotent negation in $V$.

Let $\varphi:F[X]\to V$ be a binary logic system where $V$ is a boolean algebra.  Then the completeness and compactness theorems are trivial.  Recall these statements:

Completeness Theorem.  For all formulas $\phi$ and models $\mathfrak{I}$,

$\mathfrak{I}\vDash\phi\Rightarrow X\vdash\phi$

where $\mathfrak{I}\vDash X$.

Compactness Theorem.  For all formulas $\phi$ and models $\mathfrak{I}$,

$X\vdash\phi\Rightarrow\mathfrak{I}\vDash\phi$

where $\mathfrak{I}\vDash X$.

Traditionally these apply to, what we would call, a binary logic system $\varphi:F[X]\to V$ where $V$ is a boolean algebra (hence $F$ has a consistent, idempotent negation) under traditional operations, and in particular this fixes the operational/relational structures of $F, T$, and $W$ , but $X$ is arbitrary.  In this setup, all “formulas” (or what we would hence call propositions since they are generated by a theory) are trivially satisfiable since they have a language model.  Hence Compactness is true.  Moreover since they are propositions in a binary logic system, they are in some $F[X]$ for a theory $X$ and are hence derivable; so we have Completeness.

Lastly we wish to address Godel’s Second Incompleteness Theorem;  recall its statement:

Godel’s Second Incompleteness Theorem.  A theory contains a statement of its own consistency if and only if it is inconsistent.

We have only defined what it means for a unary operation in a logical system to be consistent.  Hence we can say that a binary logic system with a unary operation is consistent if its unary operation is consistent.  But all of these traditional theorems of mathematical logic are assuming a binary logic system where $V$ is a boolean algebra , $\lnot$ is idempotent, and the map $\varphi:F[X]\to V$ is surjective.  Hence $\lnot$ is consistent (from above discussion), and the consequence in the theorem is false.

The weakest possible violation of the antecedent of Godel’s theorem is to use a structure to create itself (i.e. that it is self-swallowing), which makes no sense, let alone using it to create a larger structure within which is a statement about the initial structure.  That a binary logic system with unary operation could contain a statement of its own consistency is itself a contradiction, since the theory itself, together with the statement $\phi$, are in a metalanguage.  It is like saying that one need only the English language to describe the algebraic structure of the English language.  As we previously said at the end of Part 1, one can get arbitrarily close to doing this–using English to construct some degenerate form of English, but you can never have multiple instances of a single language in a language loop.  Another example would be having the class of all sets, then attempting to prove, using only the sets and operations of them, that there is a class containing them.

Hence the antecedent is also false.  So both implications are true.

[1]  Ebbinghaus, H.-D., J. Flum, and W. Thomas.  Mathematical Logic.  Second Edition.  Undergraduate Texts in Mathematics.  New York: Springer-Verlag.  1994.

# Fundamental Knowledge-Part 1: The Language Loop

We must start with a language.  A language can be defined in two ways.  First let us begin with the axioms of pairing, union, and powerset and schema of separation.  This gives us a cartesian product of sets, and hence functions.

Definition 1.1.  An $n$ary operation on a set $X$ is a map $O:X^n\to X$.  A structure is a set $X$ together with an $n$-ary operation.  The signature of a structure $X$ is the sequence $(n_1,...,n_k,...)$ where $n_k$ is the number of $k$-ary operations.

Definition 1.2.  Let $X$ and $Y$ be structures with the same signature such that each $k$-ary operation of $X$ is assigned to a $k$-ary operation of $Y$ (i.e. $f(O_i)=O^i$ where $O_i$ is the $i$th $k$-ary operation of $X$).  A homomorphism between structures $X$ and $Y$ is a map $\varphi:X\to Y$ such that

$\displaystyle \varphi(O_i(x_1,...,x_n))=O^i(\varphi(x_1),...,\varphi(x_n))$.

Note that a nullary operation on $X$ is a map $O:\varnothing\to X$.  That is, it is simply an element of $X$.  Now let $A$ be a set which we will call an alphabet, and its elements will be called letters.  A monoid $X$ has a nullary operation, $1\in X$ called a space, and a binary operation, which will simply be denoted by concatenation.  We define the free monoid on $A$ as the monoid $A^*$ consisting of all strings of elements in $A$.  We now have two definitions of a language, of which the first is traditional and the second is mine:

Definition 1.3.  A language is a subset of $A^*$.

Alt Definition 1.3.  Let $W\subset A^*$, $T$ be a relational structure (a set together with an $n$-ary relation), and $F$ be a structure.  The language $\mathcal{L}_{F,T,W}$ is defined as $F[T[W]]$ where $X[Y]$ is the free $X$-structure on $Y$.  In particular elements of $W$ are called words, elements of $T[W]$ are called terms, and elements of $\mathcal{L}_{F,T,W}$ are called formulas.

Definition 1.4.  A theory of $\mathcal{L}_{F,T,W}$ is a subset $X\subset\mathcal{L}_{F,T,W}$.  Elements of a theory are called axioms.  Elements of $F[X]$ are called propositions.  A theory $X$ of $\mathcal{L}_{F,T,W}$ is called a reduced theory if for all $\phi,\psi\in X$, $\psi\neq O(\phi,x_1,...,x_{n-1})$ for all $n$-ary operations of $F$ and all placements of $\phi$ in evaluation of the operation.  (That is, the theory is reduced if no axiom is in the orbit of another).

For example, the theory $\mathcal{L}_{F,T,W}$ is called the trivial theory.  The theory $\varnothing$ is called the empty (or agnostic) theory.

Definition 1.5.  An $n$ary logic system on a theory $X$ is a homomorphism $\varphi:F[X]\to V$ where $F$ and $V$ have the same signature and $V$ has cardinality $n.$  We may also say the logic system is normal if $\varphi(\phi)=\varphi(\psi)$ for all $\phi,\psi\in X.$

In traditional logic $V$ is a two element boolean algebra.  Traditional logic also has a special kind of function on its language.

Definition 1.6.  A quantifier on $\mathcal{L}_{F,T,W}$ is a function $\exists:T[W]\times\mathcal{L}_{F,T,W}\to\mathcal{L}_{F,T,W}$.  We may write:

$\exists(x\in X,\phi)=(\exists x\in X)\phi$.

In particular it is a pseudo operation, and gives the language a pseudo structure.  This is similar to modules, where in this case a product of a term and a formula are sent to a formula.

Hence our initial assumption of four axioms (as well as the ability to understand the English language), have in turn given us the ability to create a notion of a language of which a degenerate English can be construed as a special case.  This is certainly circular in some sense, but in foundations we must appeal to some cyclic process.  One subtlety worth noting is that the secondary language created will always be “strictly bounded above” by the initial language;  they aren’t truly equivalent.  (In fact this last statement is similar to the antecedent of Godel’s Second Incompleteness theorem).