# Forcing (mathematics)

For the use of forcing in recursion theory, see Forcing (recursion theory).

In the mathematical discipline of set theory, forcing is a technique discovered by Paul Cohen for proving consistency and independence results. It was first used, in 1963, to prove the independence of the Axiom of Choice and the Continuum Hypothesis from Zermelo–Fraenkel set theory. Forcing was considerably reworked and simplified in the following years, and has since served as a powerful technique, both in set theory and in areas of mathematical logic such as recursion theory.

Descriptive set theory uses the notion of forcing from both recursion theory and set theory. Forcing has also been used in model theory, but it is common in model theory to define genericity directly without mention of forcing.

## Intuition

Forcing is equivalent to the method of Boolean-valued models, which some feel is conceptually more natural and intuitive, but usually much more difficult to apply.

Intuitively, forcing consists of expanding the set theoretical universe to a larger universe . In this bigger universe, for example, one might have lots of new subsets of that were not there in the old universe, and thereby violate the continuum hypothesis. While impossible on the face of it, this is just another version of Cantor's paradox about infinity. In principle, one could consider

,

identify with , and then introduce an expanded membership relation involving “new” sets of the form . Forcing is a more elaborate version of this idea, reducing the expansion to the existence of one new set, and allowing for fine control over the properties of the expanded universe.

Cohen’s original technique, now called ramified forcing, is slightly different from the unramified forcing expounded here.

## Forcing Posets

A forcing poset is an ordered triple, , where is a preorder on that satisfies following splitting condition:

• For each , there are such that , with no such that . The largest element of is , that is, for all . Members of are called forcing conditions or just conditions. One reads as is stronger than . Intuitively, the “smaller” condition provides “more” information, just as the smaller interval provides more information about the number than the interval does.

There are various conventions in use. Some authors require to also be antisymmetric, so that the relation is a partial order. Some use the term partial order anyway, conflicting with standard terminology, while some use the term preorder. The largest element can be dispensed with. The reverse ordering is also used, most notably by Saharon Shelah and his co-authors.

### -Names

Associated with a forcing poset is the class of -names. A -name is a set of the form

This is actually a definition by transfinite recursion. More precisely, one first uses transfinite recursion to define the following hierarchy:

Then the class of -names is defined as

The -names are, in fact, an expansion of the universe. Given , one defines to be the -name

Again, this is really a definition by transfinite recursion.

### Interpretation

Given any subset of , one next defines the interpretation or valuation map from -names by

This is again a definition by transfinite recursion. Note that if , then . One then defines

so that .

### Example

A good example of a forcing poset is , where and is the collection of Borel subsets of having non-zero Lebesgue measure. In this case, one can talk about the conditions as being probabilities, and a -name assigns membership in a probabilistic sense. Due to the ready intuition this example can provide, probabilistic language is sometimes used with other forcing posets.

## Countable Transitive Models and Generic Filters

The key step in forcing is, given a universe , to find an appropriate object not in . The resulting class of all interpretations of -names will turn out to be a model of that properly extending the original (since ).

Instead of working with , one considers a countable transitive model with . By “model”, we mean a model of set theory, either of all of , or a model of a large but finite subset of , or some variant thereof. “Transitivity” means that if , then . The Mostowski Collapsing Theorem says that this can be assumed if the membership relation is well-founded. The effect of transitivity is that membership and other elementary notions can be handled intuitively. Countability of the model relies on the Löwenheim-Skolem Theorem.

As is a set, there are sets not in – this follows from Russell’s Paradox. The appropriate set to pick and adjoin to is a generic filter on . The “filter” condition means that

• ;
• ;
• if , then ;
• if , then there exists an such that .

For to be “generic” means:

• If is a “dense” subset of (that is, for each , there exists a such that ), then .

The existence of a generic filter follows from the Rasiowa-Sikorski Lemma. In fact, slightly more is true: Given a condition , one can find a generic filter such that . Due to the splitting condition, if is a filter, then is dense. If , then because is a model of . For this reason, a generic filter is never in .

## Forcing

Given a generic filter , one proceeds as follows. The subclass of -names in is denoted . Let . To reduce the study of the set theory of to that of , one works with the “forcing language”, which is built up like ordinary first-order logic, with membership as the binary relation and all the -names as constants.

Define (to be read as “ forces in the model with poset ”), where is a condition, is a formula in the forcing language, and the ’s are -names, to mean that if is a generic filter containing , then . The special case is often written as “” or simply “”. Such statements are true in , no matter what is.

What is important is that this external definition of the forcing relation is equivalent to an internal definition within , defined by transfinite induction over the -names on instances of and , and then by ordinary induction over the complexity of formulas. This has the effect that all the properties of are really properties of , and the verification of in becomes straightforward. This is usually summarized as the following three key properties:

• Truth: if and only if it is forced by , that is, for some condition , we have .
• Definability: The statement “” is definable in .
• Coherence: If and , then .

We define the forcing relation in by induction on the complexity of formulas, in which we first define the relation for atomic formulas by -induction and then define it for arbitrary formulas by induction on their complexity.

1. if and only if .

2. if and only if .

3. if and only if .

4. if and only if .

5. if and only if .

## Consistency

The discussion above can be summarized by the fundamental consistency result that, given a forcing poset , we may assume the existence of a generic filter , not belonging to the universe , such that is again a set-theoretic universe that models . Furthermore, all truths in may be reduced to truths in involving the forcing relation.

Both styles, adjoining to either a countable transitive model or the whole universe , are commonly used. Less commonly seen is the approach using the “internal” definition of forcing, in which no mention of set or class models is made. This was Cohen’s original method, and in one elaboration, it becomes the method of Boolean-valued analysis.

## Cohen Forcing

The simplest nontrivial forcing poset is , the finite partial functions from to under reverse inclusion. That is, a condition is essentially two disjoint finite subsets and of , to be thought of as the “yes” and “no” parts of , with no information provided on values outside the domain of . “ is stronger than ” means that , in other words, the “yes” and “no” parts of are supersets of the “yes” and “no” parts of , and in that sense, provide more information.

Let be a generic filter for this poset. If and are both in , then is a condition because is a filter. This means that is a well-defined partial function from to because any two conditions in agree on their common domain.

In fact, is a total function. Given , let . Then is dense. (Given any , if is not in ’s domain, adjoin a value for — the result is in .) A condition has in its domain, and since , we find that is defined.

Let , the set of all “yes” members of the generic conditions. It is possible to give a name for directly. Let . Then . Now suppose that in . We claim that . Let . Then is dense. (Given any , if is not in ’s domain, adjoin a value for contrary to the status of “”.) Then any witnesses . To summarize, is a “new” subset of , necessarily infinite.

Replacing with , that is, consider instead finite partial functions whose inputs are of the form , with and , and whose outputs are or , one gets new subsets of . They are all distinct, by a density argument: Given , let , then each is dense, and a generic condition in it proves that the αth new set disagrees somewhere with the -th new set.

This is not yet the falsification of the continuum hypothesis. One must prove that no new maps have been introduced which map onto , or onto . For example, if one considers instead , finite partial functions from to , the first uncountable ordinal, one gets in a bijection from to . In other words, has collapsed, and in the forcing extension, is a countable ordinal.

The last step in showing the independence of the continuum hypothesis, then, is to show that Cohen forcing does not collapse cardinals. For this, a sufficient combinatorial property is that all of the antichains of this poset are countable.

## The Countable Chain Condition

An antichain of is a subset such that if , then and are incompatible (written ), meaning there is no in such that and . In the example on Borel sets, incompatibility means that has zero measure. In the example on finite partial functions, incompatibility means that is not a function, in other words, and assign different values to some domain input.

satisfies the countable chain condition (c.c.c.) if and only if every antichain in is countable. (The name, which is obviously inappropriate, is a holdover from older terminology. Some mathematicians write “c.a.c.” for “countable antichain condition”.)

It is easy to see that satisfies the c.c.c. because the measures add up to at most . Also, is c.c.c., but the proof is more difficult.

Given an uncountable subfamily , shrink to an uncountable subfamily of sets of size , for some . If for uncountably many , shrink this to an uncountable subfamily and repeat, getting a finite set and an uncountable family of incompatible conditions of size such that every is in for at most countable many . Now, pick an arbitrary , and pick from any that is not one of the countably many members that have a domain member in common with . Then and are compatible, so is not an antichain. In other words, -antichains are countable.

The importance of antichains in forcing is that for most purposes, dense sets and maximal antichains are equivalent. A maximal antichain is one that cannot be extended to a larger antichain. This means that every element is compatible with some member of . The existence of a maximal antichain follows from Zorn’s Lemma. Given a maximal antichain , let . Then is dense, and if and only if . Conversely, given a dense set , Zorn’s Lemma shows that there exists a maximal antichain , and then if and only if .

Assume that is c.c.c. Given , with a function in , one can approximate inside as follows. Let be a name for (by the definition of ) and let be a condition that forces to be a function from to . Define a function , whose domain is , by . By the definability of forcing, this definition makes sense within . By the coherence of forcing, different ’s come from incompatible ’s. By c.c.c., is countable.

In summary, is unknown in as it depends on , but it is not wildly unknown for a c.c.c.-forcing. One can identify a countable set of guesses for what the value of is at any input, independent of .

This has the following very important consequence. If in , is a surjection from one infinite ordinal onto another, then there is a surjection in , and consequently, a surjection in . In particular, cardinals cannot collapse. The conclusion is that in .

## Easton Forcing

The exact value of the continuum in the above Cohen model, and variants like for cardinals in general, was worked out by Robert M. Solovay, who also worked out how to violate (the Generalized Continuum Hypothesis), for regular cardinals only, a finite number of times. For example, in the above Cohen model, if holds in , then holds in .

William B. Easton worked out the proper class version of violating the for regular cardinals, basically showing that the known restrictions, (monotonicity, Cantor’s Theorem and König’s Theorem), were the only -provable restrictions (see Easton’s Theorem).

Easton’s work was notable in that it involved forcing with a proper class of conditions. In general, the method of forcing with a proper class of conditions fails to give a model of . For example, forcing with , where is the proper class of all ordinals, makes the continuum a proper class. On the other hand, forcing with introduces a countable enumeration of the ordinals. In both cases, the resulting is visibly not a model of .

At one time, it was thought that more sophisticated forcing would also allow an arbitrary variation in the powers of singular cardinals. However, this has turned out to be a difficult, subtle and even surprising problem, with several more restrictions provable in and with the forcing models depending on the consistency of various large-cardinal properties. Many open problems remain.

## Random Reals

Main article: random algebra

In the Borel sets example, the generic filter converges to a real number , called a random real. A name for the decimal expansion of (in the sense of the canonical set of decimal intervals that converge to ) can be given by letting . This is, in some sense, just a subname of .

To recover from , one takes those Borel subsets of that “contain” . Since the forcing poset is in , but is not in , this containment is actually impossible. However, there is a natural sense in which the interval in “contains” a random real whose decimal expansion begins with . This is formalized by the notion of “Borel code”.

Every Borel set can, non-uniquely, be built up, starting from intervals with rational endpoints and applying the operations of complement and countable unions, a countable number of times. The record of such a construction is called a Borel code. Given a Borel set in , one recovers a Borel code, and then applies the same construction sequence in , getting a Borel set . One can prove that one gets the same set independent of the construction of , and that basic properties are preserved. For example, if , then . If has measure zero, then has measure zero.

So given , a random real, one can show that . Because of the mutual inter-definability between and , one generally writes for .

A different interpretation of reals in was provided by Dana Scott. Rational numbers in have names that correspond to countably many distinct rational values assigned to a maximal antichain of Borel sets, in other words, a certain rational-valued function on . Real numbers in then correspond to Dedekind cuts of such functions, that is, measurable functions.

## Boolean-Valued Models

Main article: Boolean-valued model

Perhaps more clearly, the method can be explained in terms of Boolean-valued models. In these, any statement is assigned a truth value from some complete atomless Boolean algebra, rather than just a true/false value. Then an ultrafilter is picked in this Boolean algebra, which assigns values true/false to statements of our theory. The point is that the resulting theory has a model which contains this ultrafilter, which can be understood as a new model obtained by extending the old one with this ultrafilter. By picking a Boolean-valued model in an appropriate way, we can get a model that has the desired property. In it, only statements which must be true (are "forced" to be true) will be true, in a sense (since it has this extension/minimality property).

## Meta-Mathematical Explanation

In forcing, we usually seek to show that some sentence is consistent with (or optionally some extension of ). One way to interpret the argument is to assume that is consistent and then prove that combined with the new sentence is also consistent.

Each “condition” is a finite piece of information – the idea is that only finite pieces are relevant for consistency, since, by the Compactness Theorem, a theory is satisfiable if and only if every finite subset of its axioms is satisfiable. Then we can pick an infinite set of consistent conditions to extend our model. Therefore, assuming the consistency of , we prove the consistency of extended by this infinite set.

## Logical Explanation

By Gödel’s Second Incompleteness Theorem, one cannot prove the consistency of any sufficiently strong formal theory, such as , using only the axioms of the theory itself, unless the theory is inconsistent. Consequently, mathematicians do not attempt to prove the consistency of using only the axioms of , or to prove that is consistent for any hypothesis using only . For this reason, the aim of a consistency proof is to prove the consistency of relative to the consistency of . Such problems are known as problems of relative consistency. In fact one proves

(*)

We will now give the general schema of relative consistency proofs. As any proof is finite, it uses only a finite number of axioms:

For any given proof, can verify the validity of this proof. This is provable by induction on the length of the proof.

Now, we obtain

If we prove the following,

(**) ,

we can conclude that

,

which is equivalent to

,

which gives (*). The core of the relative consistency proof is proving (**). One has to construct a proof of for any given finite subset of the axioms (by instruments of course). (No universal proof of of course.)

In , it is provable that for any condition , the set of formulas (evaluated by names) forced by is deductively closed. Furthermore, for any axiom, proves that this axiom is forced by . Then it suffices to prove that there is at least one condition that forces .

In the case of Boolean-valued forcing, the procedure is similar – one has to prove that the Boolean value of is not .

Another approach uses the Reflection Theorem. For any given finite set of axioms, there is a proof that this set of axioms has a countable transitive model. For any given finite set of axioms, there is a finite set of axioms such that proves that if a countable transitive model satisfies , then satisfies . One has to prove that there is finite set of axioms such that if a countable transitive model satisfies , then satisfies the hypothesis . Then, for any given finite set of axioms, proves .

Sometimes in (**), a stronger theory than is used for proving . Then we have proof of the consistency of relative to the consistency of . Note that , where is (the Axiom of Constructibility).