(draft)
We take the view that logic deals with "propositions", that is, things that can be true
or false
. [1]
Take Venn diagrams: Given a "domain" of objects a proposition is a subset of . In a Venn diagram one identifies a proposition with the subset of objects for which the proposition is true
. (Think eg of as the set of all animals and "cat" as a proposition that is true of some animals and not of others.)
More precisely, given a fixed set (domain, universe), we take a proposition to be a subset . From given propositions one can build new propositions as follows. If are propositions then
(I should proably insert some pictures of Venn diagrams here.)
This definition of what a proposition is blurs the distinction of a proposition as a linguistic construct (the letter ) and its meaning ( as a subset of ). Typically, logicians are more careful than this, but for these notes this sloppiness should not lead to major confusions (I hope). In fact, it can be quite convenient. For example, to express that satsifies the proposition (sometimes written as ) we can simply write
because, under our identification of propositions and sets, satisifes the proposition iff[2] is an element of the set .
(For example: When I say that "Leon is a cat" I equally say that "Leon is an element of the set of cats".)
I said that these notes will be written in the spirit of category theory (but no category theory is needed to do the exercises). We can see this right from the start. Instead of starting to build a theory of propositional logic for a fixed set , we rather consider how propositions transform under functions . This may seem as a major detour, or even complication. But it is the modern view in many areas of mathematics: Instead of focussing on a given stucture (such as the set together with its subsets), study these structures together with their structure-preserving maps.
And this is our starting point. The first proposition/exercise below asks you to show that every function on objects induces a function on propositions that preserves the structure of .
But before we go there, it will be useful to have a notation for the set of all propositions on a given set . We write
for the set of subsets of .[3]
In the following, the propositions are exercises. Write out a proof for each the following propositions.
Proposition: Given a function the inverse image function preserves unions, intersections and complements. [4]
The next aim is to show that the converse also holds, that is, if a function preserves unions and intersections, then it is the the inverse image of some .
In the notation introduced below, will be the restriction of to .
This requires some work and there are different ways to do this. I will guide you through the way I do this, which has been chosen with future generalizations in mind.
As an aside, adjoints (or adjunctions) play a major role in category theory and many areas of mathematics. In the next proposition/exercise, we encounter a special case for the first time.
Proposition: If preserves unions and intersections then has a left adjoint and a right-adjoint .[5]
Remark: Category theoretic generalisations of this are known as adjoint functor theorems.
Recall that given preserving intersections and unions, we want to find so that is the inverse image . We want to show that we can obtain from restricting to via . For this we need that maps singletons to singletons. [6]
With an eye on later generalisations, we will use an abstract characterisation of singletons, not in terms of elements, but in terms of subsets.
Definition: is an atom if for all we have that implies that there is such that .
If you see this definition for the first time it will probably look strange. So let me give three reasons for setting things up like this.
Proposition: is an atom iff there is such that .
For the proof of the lemma, recall that has a left adjoint since preserves intersections and use the definition of atom and adjoint.
Lemma: Let preserve intersections and unions. Then the left adjoint maps atoms to atoms.
The next proposition now is obtained from putting everything together. You may have to go back to the beginning and retrace your steps to see the whole picture.
Proposition: Every function preserving intersections and unions is the inverse image map for a (unique) function .
We have done now the hard work. But we can "milk our cow" and deduce some stronger results.
Theorem: There is a bijection between functions preserving intersections and unions and functions .
This theorem is the beginning of duality theory. It has ramifications in many areas of mathematics.
To understand this better, we need to describe the collections of subsets using abstract algebra … (to be continued)
Logic is sometimes divided into model theory and proof theory. Proof theory studies mathematical proofs and views a proposition as true if it has a proof. Model theory studies mathematical models that assign to each proposition a truth value (typically true
or false
). A proposition is valid if it evaluates to true
in all models. These notes are written from the model-theoretic rather than the proof-theoretic point of view. Venn diagrams are pictures of mathematical models for what is known as "classical propositional logic". ↩︎
if and only if ↩︎
(I apologise for the length of this explanation, but this notation is ubiquitous in math and quite slick once one got used to it.)
true
with and false
with . So, in fact, refers to the set of truth values.To summarize, we write for the collection of subsets of , which, equivalently, is the set of functions .
The last bullet point, under which we identify a proposition with a subset with a function into truth-values is very important, both from a conceptual point of view and from a technical point of view. So if you are not sure about this, maybe try to prove the propositions/exercises below and then come back to contemplate this point. ↩︎
Given , we define . Thus the task is to show that , and similarly for and . As a variation, we will also need that preserves infinite intersections and unions. ↩︎
By definition, is left-adjoint to (and is right-adjoint to ), written as , if for all
The following statements may help with proving the propositions.
implies and .
implies that and are monotone.
(Footnote: A function is monotone if .)
Conversely, if and for all and if are monotone, then .
Given , the condition determines uniquely and, vice versa, determines uniquely given .
(You may take these statements for granted or as further exercises.) ↩︎
A singleton is a set that contains exactly one element. ↩︎
The definition that is an atom can be rewritten as
iff