The weakness of the pigeonhole principle under hyperarithmetical reductions
Benoit Monin
Ludovic Patey
Abstract
The infinite pigeonhole principle for 2-partitions (RT21) asserts the existence, for every set A, of an infinite subset of A or of its complement. In this paper, we study the infinite pigeonhole principle from a computability-theoretic viewpoint. We prove in particular that RT21 admits strong cone avoidance for arithmetical and hyperarithmetical reductions. We also prove the existence, for every Δn0 set, of an infinite lown subset of it or its complement. This answers a question of Wang. For this, we design a new notion of forcing which generalizes the first and second-jump control of Cholak, Jockusch and Slaman.
1 Introduction
In this paper, we study the infinite pigeonhole principle (RTk1) from a computability-theoretic viewpoint. The infinite pigeonhole principle asserts that every finite partition of ω admits an infinite part. More formally, RTk1 is the problem whose instances are colorings f:ω→k. An RTk1-solution to f is an infinite set H⊆ω such that ∣f[H]∣=1. The general question we aim to address is the following:
Question 1.1*.*
Does every instance of RTk1 admit a “weak” solution?
We consider various notions of weakness, among which the inability to bound a fixed non-zero degree for the Δn0, arithmetical and hyperarithmetical reduction. This property is known as strong cone avoidance. With respect to Δn0 and arithmetical reductions, our main theorems are:
Theorem 1.2** **(Main theorem 1)
Fix n≥0. Let B be non ∅(n)-computable. Every set A has an infinite subset H⊆A or H⊆A such that B is not H(n)-computable.
Theorem 1.3** **(Main theorem 2)
Let B be non arithmetical. Every set A has an infinite subset H⊆A or H⊆A such that B is not arithmetical in H.
We also study restrictions of the infinite pigeonhole principle to Δn0 instances. With that respect, our main theorem is:
Theorem 1.4** **(Main theorem 3)
Fix n≥0. Every \cmsy;(n+1)-computable set A has an infinite subset H⊆A or H⊆A of lown+2 degree.
Finally our main theorem with respect to hyperarithmetic reductions is:
Theorem 1.5** **(Main theorem 4)
Let B be non hyperarithmetical. Every set A has an infinite subset H⊆A or H⊆A such that B is not hyperarithmetical in H, in particular with ω1H=ω1ck.
Our motivation comes from reverse mathematics.
Reverse mathematics is a foundational program which aims to find the weakest axioms needed to prove ordinary theorems. The early reverse mathematics showed the existence of an empirical structural phenomenon, in that most theorems are provably equivalent to one among five main systems of axioms, linearly ordered by the logical implication. See Simpson’s book [25] for a reference on reverse mathematics. However, some natural statements escape this structural phenomenon, the most famous one being Ramsey’s theorem for pairs (RT22). Given a set X, let [X]n denote the set of unordered n-tuples over X. Ramsey’s theorem for n-tuples and k-colors (RTkn) asserts the existence, for every coloring f:[ω]n→k, of an infinite set H⊆ω such that ∣f[ω]n∣=1. In particular, RTk1 is the infinite pigeonhole principle.
Ramsey’s theorem for pairs and two colors received a lot of attention from the computability community as it was historically the first example of statement escaping the structural phenomenon of reverse mathematics. The study of RTk2 revealed a deep connection between the computability-theoretic features of RTk2 and the combinatorial features of RTk1. More precisely, almost every proof of a statement of the form “Every computable instance of RTk2 admits a weak solution” can be obtained by a proof of the statement “every (arbitrary) instance of RTk1 admits a weak solution”, with the help of very weak computability-theoretic notion called cohesiveness. This is in particular the case for cone avoidance [24, 6], PA avoidance [12], constant-bound trace avoidance [13], preservation of hyperimmunity [20], and preservation of non-c.e. definitions [31, 19], among others.
In many cases, the combinatorial features of RTk1 and the computability-theoretic features of RTk2 can be proven to be equivalent. See Cholak and Patey [3, Theorem 1.5] for an equivalence in the case of cone avoidance. It therefore seems essential to obtain a good understanding of the infinite pigeonhole principle in order to better understand why Ramsey’s theorem for pairs escapes the structural phenomenon of reverse mathematics.
1.1 Strong cone avoidance
Given a partial order ≤r on 2ω and a set X, we let degr(X)={Y:X≡rY} be the degree of X, where X≡rY if X≤rY and Y≤rX. We are in particular interested in the case where ≤r is among the Δn0 reduction ≤n, the arithmetical reduction ≤arith and the hyperarithmetical reduction ≤hyp.
Given a mathematical problem P formulated in terms of instances and solutions, it is natural to ask which sets are P-encodable. Here, we say that a set X is P-encodable if there is an instance I of P such that for every P-solution Y to I, X≤rY. Some problems are very weak with respect to the order ≤r, and satisfy the following property:
Definition 1.6** (Strong cone avoidance).**
A problem P admits strong cone avoidance for ≤r if for every pair of sets Z and C such that C≤rZ, every instance X of P admits a solution Y such that C≤rZ⊕Y.
Dzhafarov and Jockusch [6] proved that RT21 admits strong cone avoidance of the Turing reduction. Their theorem has practical applications, and yield a simpler proof of Seetapun’s theorem [24]. We prove a similar result for Δn0 and arithmetical reductions.
Theorem** **(Reformulation of Main theorem 1 (Theorem 1.2))
RT21 admits strong cone avoidance for Δn0 reductions.
Theorem** **(Reformulation of Main theorem 2 (Theorem 1.3))
RT21 admits strong cone avoidance for arithmetical reductions.
We finally prove in the last section strong cone avoidance for hyperarithmetical reductions, the main difficulty being to show that a non-computable ordinal is never RT21-encodable. This gives us the following theorem:
Theorem** **(Reformulation of Main theorem 4 (Theorem 1.5))
RT21 admits strong cone avoidance for hyperarithmetical reductions.
These theorems show the combinatorial weakness of the pigeonhole principle with respect RT21-encodability. To prove this, we designed a new notion of forcing with an iterated jump control generalizing the first and second jump control of Cholak, Jockusch and Slaman [2].
1.2 Lowness and hierarchies
The computability-theoretic study of the pigeonhole principle is also motivated by questions on the strictness of hierarchies in reverse mathematics. Some consequences of Ramsey’s theorem form hierarchies of statements, parameterized by the size of the colored tuples. A first example is Ramsey’s theorem itself. Indeed, RTkn+1 implies RTkn for every n,k≥1. By the work of Jockusch [9], this hierarchy collapses starting from the triples, and by Seetapun [24], Ramsey’s theorem for pairs is strictly weaker than Ramsey’s theorem for triples. We therefore have
[TABLE]
Some other hierarchies have been considered in reverse mathematics.
Friedman [7] introduced the free set (FSn) and thin set theorems (TSn), while Csima and Mileti [4] introduced and studied the rainbow Ramsey theorem (RRTkn). These statements are all of the form Pn: “For every coloring f:[ω]n→ω, there is an infinite set H⊆ω such that f↾[H]n avoids some set of forbidden patterns”.
The reverse mathematics of these statements were extensively studied in the literature [1, 4, 11, 16, 17, 19, 21, 28, 29, 30, 31, 32]. In particular, these theorems form hierarchies which are not known to be strictly increasing.
Question 1.7*.*
Are the hierarchies of the free set, thin set, and rainbow Ramsey theorem strictly increasing?
Partial results were however obtained. All these statements admit lower bounds of the form “For every n≥2, there is a computable instance of Pn with no Σn0 solution”, where Pn denotes any of RTkn (Jockusch [9]), RRTkn (Csima and Mileti [4]), FSn, or TSn (Cholak, Giusto, Hirst and Jockusch [1]). From the upper bound viewpoint, all these statements follow from Ramsey’s theorem. Therefore, by Cholak, Jockusch and Slaman [2], every computable instance of P1 admits a computable solution, and every computable instance of P2 admits a low2 solution. These results are sufficient to show that P1<P2<P3 in reverse mathematics. This upper bound becomes too coarse for triples. Wang [30] proved that every computable instance of RRTk3 admits a low3 solution. The following question is still open. A positive answer would also answer positively Question 1.7.
Question 1.8*.*
Does every computable instance of FSn, TSn, and RRTkn admit a lown solution?
Indeed, suppose 1.8 is answered positively for some P∈{RRT2,FS,TS}. For every n, one can iterate a relativization of 1.8 to build a model M of Pn containing only sets of lown degree. In particular, any set in M is Σn+10 , while by the lower bounds mentioned above, there is a computable instance of Pn+1 with no Σn+10 solution. Thus, Pn+1 fails in M, hence Pn does not imply Pn+1 over RCA0.
Upper bounds to FSn, TSn, and RRTkn,
are usually proven inductively over n [32, 16, 20], starting with the infinite pigeonhole principle for n=1. In this paper, we therefore prove the following theorem, which introduces the machinery that hopefully will serve to answer positively Question 1.8.
Theorem** **(Main theorem 3 (Theorem 1.4))
Fix n≥0. Every \cmsy;(n+1)-computable set A has an infinite subset H⊆A or H⊆A of lown+2 degree.
In particular, we fully answer two questions of Wang [30, Questions 6.1 and 6.2], also asked by the second author [18, Question 5.4]. The cases n=2 and n=3 were proven by Cholak, Jockusch and Slaman [2] and by the authors [15], respectively.
1.3 Definitions and notation
A binary string is an ordered tuple of bits a0,…,an−1∈{0,1}.
The empty string is written ϵ. A binary sequence (or a real) is an infinite listing of bits a0,a1,….
Given s∈ω,
2s is the set of binary strings of length s and
2<s is the set of binary strings of length <s. As well,
2<ω is the set of binary strings
and 2ω is the set of binary sequences.
Given a string σ∈2<ω, we use ∣σ∣ to denote its length.
Given two strings σ,τ∈2<ω, σ is a prefix
of τ (written σ⪯τ) if there exists a string ρ∈2<ω
such that σ⌢ρ=τ. Given a sequence X, we write σ≺X if
σ=X↾n for some n∈ω.
A binary string σ can be interpreted as a finite set Fσ={x<∣σ∣:σ(x)=1}. We write σ⊆τ for Fσ⊆Fτ.
We write #σ for the size of Fσ. Given two strings σ and τ, we let σ∪τ be the unique string ρ of length max(∣σ∣,∣τ∣) such that Fρ=Fσ∪Fτ.
A binary tree is a set of binary strings T⊆2<ω which is closed downward under the prefix relation. A path through T is a binary sequence P∈2ω such that every initial segment belongs to T.
A Turing ideal I is a collection of sets which is closed downward under the Turing reduction and closed under the effective join, that is, (∀X∈I)(∀Y≤TX)Y∈I and (∀X,Y∈I)X⊕Y∈I, where X⊕Y={2n:n∈X}∪{2n+1:n∈Y}. A Scott set is a Turing ideal I such that every infinite binary tree T∈I has a path in I. In other words, a Scott set is the second-order part of an ω-model of RCA0+WKL.
A Turing ideal M is countable coded by a set X
if M={Xn:n∈ω} with X=⨁nXn.
A formula is Σ10(M) (resp. Π10(M)) if it is Σ10(X) (resp. Π10(X)) for some X∈M.
Given two sets A and B, we denote by A<B the formula
(∀x∈A)(∀y∈B)[x<y].
We write A⊆∗B to mean that A−B is finite, that is,
(∃n)(∀a∈A)(a∈B→a<n).
A k-cover of a set X is a sequence of sets Y0,…,Yk−1 such that X⊆Y0∪⋯∪Yk−1.
2 Preliminary tools
We start by introduce the central tools used in the various forcings to come : the largeness and partition regular classes. They were introduced by the authors in [15] to design a notion of forcing controlling the second jump of solutions to the pigeonhole principle. In this paper we push their use further, with the introduction of M-cohesive and M-minimal largeness classes, which are necessary for the third jump control and beyond.
2.1 Largeness classes
Definition 2.1**.**
A largeness class is a non-empty collection of sets A⊆2ω such that
If X∈A and Y⊇X, then Y∈A
For every k-cover Y0,…,Yk−1 of ω, there is some j<k such that Yj∈A.
For example, the collection of all the infinite sets is a largeness class. Moreover, any superclass of a largeness class is again a largeness class.
Lemma 2.2
Suppose A0⊇A1⊇… is a decreasing sequence of largeness classes.
Then ⋂sAs is a largeness class.
Proof.
If X∈⋂sAs and Y⊇X, then for every s, since As is a largeness class, Y∈As, so Y∈⋂sAs.
Let Y0,…,Yk−1 be a k-cover of ω. For every s∈ω, there is some j<k
such that Yj∈As. By the infinite pigeonhole principle, there is some j<k such that Yj∈As for infinitely many s. Since A0⊇A1⊇ is a decreasing sequence, Yj∈⋂sAs.
∎
Lemma 2.3
Let A be a Σ10 class.
The sentence “A is a largeness class” is Π20.
Proof.
Say A={X:(∃σ⪯X)φ(σ)} where φ is a Σ10 formula.
By compactness, A is a largeness class iff for every σ and τ such that σ⊆τ and φ(σ) holds, φ(τ) holds, and for every k, there is some n∈ω such that for every σ0∪⋯∪σk−1={0,…,n}, there is some j<k such that φ(σj) holds.
∎
2.2 Partition regular classes
Definition 2.4**.**
A partition regular class is a collection of sets L⊆2ω such that
L is a largeness class
For every X∈L and Y0∪⋯∪Yk−1⊇X, there is some j<k such that Yj∈L.
In particular, the class of all infinite sets is partition regular.
Lemma 2.5
Suppose A0⊇A1⊇… is a decreasing sequence of partition regular classes.
Then ⋂sAs is a partition regular class.
Proof.
The proof is easy, similar to the one of Lemma 2.2 and left to the reader.
∎
Definition 2.6**.**
Let A be a largeness class. Define
[TABLE]
Note that a superset of a partition regular class need not to be partition regular, it is however always a largeness class. Note also that if U is a Σ10(X) class, then by compactness L(U) is a Π20(X) class.
Lemma 2.7
Let A be a largeness class. Then L(A) is the largest partition regular subclass of A.
Proof.
We first prove that L(A) is a partition regular subclass of A.
By definition of A being a largeness class, ω∈L(A).
Let X∈L(A) and X0∪⋯∪Xk−1⊇X. Suppose for the sake of absurd that Xi∈L(A) for every i<k. Then for every i<k, there is some ki∈ω and some Yi0∪⋯∪Yiki−1⊇Xi such that Yij∈A for every j<ki. Then {Yij:i<k,j<ki} is a cover of X contradicting X∈L(A). Therefore L(A) is a partition regular class.
Moreover, L(A)⊆A as witnessed by taking the trivial cover of X by X itself.
We now prove that L(A) is the largest partition regular subclass of A.
Indeed, let B be a partition regular subclass of A. Then for every X∈B, every X0∪⋯∪Xk−1⊇X, there is some j<k such that Xj∈B⊆A. Thus X∈L(A), so B⊆L(A).
∎
2.3 M-cohesive classes
We now introduce the notion of M-cohesive largeness classes for a countable Scott set M. One would ideally need M-minimal largeness classes instead for the upcoming forcing (see Definition 2.10). Unfortunately these classes are definitionally too complex for us. We use instead M-cohesive largeness classes, which are definitionally simpler and can be seen as a way to “almost” build a minimal largeness class. The key property of these classes lies in Lemma 2.9, which is later used to show that an M-cohesive largeness class contains a unique M-minimal largeness class.
Given an infinite set X, we let LX be the Π20(X) largeness class of all sets having an infinite intersection with X.
Definition 2.8**.**
A class A is M-cohesive
if for every X∈M, either A⊆LX or A⊆LX.
In what follows, fix an effective enumeration U0Z,U1Z,… of all the Σ10,Z classes upward-closed under the superset relation, that is, if X∈UeZ and Y⊇X, then Y∈UeZ. Fix also a Scott set M={X0,X1,…} countable coded by a set M. Given a set C⊆ω2, we write
[TABLE]
Lemma 2.9
Let UCM be an M-cohesive class.
Let UDM and VEM be such that UCM∩UDM and UCM∩UEM are both largeness classes. Then UCM∩UDM∩UEM is a largeness class.
Proof.
Suppose for contradiction that UCM∩UDM∩UEM is not a largeness class. Then by Lemma 2.2, there is some finite C1⊆C, D1⊆D and E1⊆E such that UC1M∩UD1M∩UE1M is not a largeness class. Since UC1M∩UD1M∩UE1M is Σ10(M), the collection C of all sets Y0⊕⋯⊕Yk−1 such that Y0⊔⋯⊔Yk−1=ω and for every i<k, Yi∈UC1M∩UD1M∩UE1M⊇UCM∩UDM∩UEM, is a non-empty Π10(M) class.
Since M is a Scott set, C∩M=∅, so fix such a set Y0⊕⋯⊕Yk−1∈C∩M.
Since UCM is M-cohesive, there must be some i<k such that UCM⊆LYi. In particular, Yi∈UCM, so Yi∈UDM or Yi∈UEM. Suppose Yi∈UDM, as the other case is symmetric. Since Yj∩Yi=∅ for every j=i, then Yj∈UCM⊆LYi for every j=i. It follows that Y0,…,Yk−1 witnesses that UCM∩UDM is not a largeness class. Contradiction.
∎
2.4 M-minimal classes
Definition 2.10**.**
A class A is M-minimal if for every X∈M and e∈ω, either A⊆UeX or A∩UeX is not a largeness class.
The following is a corollary of lemma 2.9 and informally says that an M-cohesive largeness class contains a unique M-minimal largeness class, which can be build with a greedy algorithm.
Lemma 2.11
Given an M-cohesive largeness class UCM,
the collection of sets
[TABLE]
is an M-minimal largeness class contained in UCM.
Proof.
We first prove that ⟨UCM⟩ is a largeness class.
Let e0,e1,… and X0,X1,… be an enumeration of all pairs (e,X)∈ω×M such that UCM∩UeX is a largeness class.
By induction on n using Lemma 2.9,
⋂i<nUeiXi is a largeness class for every n∈ω. Thus, by Lemma 2.2, ⟨UCM⟩=⋂iUeiXi is a largeness class. By construction ⟨UCM⟩ is M-minimal.
∎
Note that we clearly have ⟨UCM⟩⊆UCM. The notation ⟨UCM⟩ for an M-cohesive largeness class will be used all along this document. Note that ⟨UCM⟩=UDM where D is the set of all ⟨e,i⟩ such that UCM∩UeXi is a largeness class.
Lemma 2.12
Let UCM be a largeness class. Then L(UCM)=UDM for some D⊆ω2. Furthermore D is computable from C.
Proof.
Let UCM be a largeness class. Note that L(UCM)⊆⋂⟨e,i⟩L(UeXi). By lemma 2.5 the class ⋂⟨e,i⟩L(UeXi) is partition regular. By lemma 2.7 we then must have L(UCM)=⋂⟨e,i⟩L(UeXi). Also we have by definition of L(U) for a class U that L(UeXi) is a Π20(Xi) class whose indices are computable uniformly in e.
Thus we have that L(UCM)=UDM for some D⊆ω2. Furthermore D is computable from C.
∎
Corollary 2.13
Suppose UCM is an M-minimal largeness class. Then UCM is partition regular.
Proof.
Let D be such that UDM=L(UCM).
By Lemma 2.7, UDM⊆UCM. By M-minimality of UCM, UCM⊆UDM. It follows that UCM=UDM. Since UDM is partition regular, then so is UCM.
∎
It follows that if UCM is an M-cohesive largeness class, then the M-minimal class ⟨UCM⟩ is a partition regular class.
2.5 The framework
We now build a sequence of sets {UCnMn}n∈ω which will be used for the forcing in the next section.
Proposition 2.14
There is a sequence of sets {Mn}n<ω such that:
-
Mn codes for a countable Scott set Mn
2. 2.
\cmsy;(n) is uniformly coded by an element of Mn
3. 3.
Each Mn′ is uniformly computable in \cmsy;(n+1)
Proof.
Let us show the following: there is a functional Φ:2ω→2ω such that for any oracle X, we have that M′=Φ(X′) is such that M=⊕n∈ωXn codes for a Scott set M with X0=X.
Fix a uniformly computable enumeration C0Y,C1Y,… of all non-empty Π10(Y) classes.
Let DX be the Π10(X) class of all ⨁nYn such that Y0=X and for every n=⟨a,b⟩∈ω, Yn+1∈Ca⨁j≤bYj. Note that this Π10(X) class is uniform in X and any member of DX is a code of a Scott set whose first element is X. Using the Low basis theorem [10], there is a Turing functional Φ such that Φ(X′) is the jump of a member of DX for any X.
Using this function Φ, it is clear that uniformly in \cmsy;(n+1) one can compute the jump of a set Mn coding for a Scott set Mn and containing \cmsy;(n) as its first element.
∎
Let us assume that {Mn}n<ω is a sequence which verifies Proposition 2.14. Recall the notation ⟨UCM⟩ : the unique minimal largeness subclass of an M-cohesive largeness class.
Proposition 2.15
There is a sequence of sets {Cn}n∈ω such that:
-
UCnMn is an Mn-cohesive largeness class
2. 2.
UCn+1Mn+1⊆⟨UCnMn⟩
3. 3.
Each Cn is coded by an element of Mn+1 uniformly in n and Mn+1.
In order to prove Proposition 2.15 we use the two following uniformity lemmas, which will also be helpful later to continue the sequence of Proposition 2.15 through the computable ordinals (see Proposition 5.8).
Lemma 2.16
There is a functional Φ:2ω×ω→2ω such that for any set M coding for a Scott set M, for any e such that C=Φe(M′′) is such that UCM is an M-cohesive largeness class, D=Φ(M′′,e) is such that C⊆D and UDM=⟨UCM⟩.
Proof.
Say M={X0,X1,…} with M=⨁iXi.
Let {⟨et,it⟩}t∈ω be an enumeration of ω×ω. Suppose that at stage t a finite set Dt⊆{⟨e0,i0⟩,…,⟨et,it⟩} has been defined such that UDtM∩UCM is a largeness class and such that for any s≤t, ⟨es,is⟩∈/Dt implies that UesXis∩UDtM∩UCM is not a largeness class.
Then at stage t+1, we ask M′′ if Uet+1Xit+1∩UDtM∩UCM is a largeness class. If so we define Dt+1=Dt∪{⟨et+1,it+1⟩}. Otherwise we define Dt+1=Dt. Then D=C∪⋃tDt is uniformly M′′-computable and UDM equals ⟨UCM⟩.
∎
Lemma 2.17
There is a functional Φ:2ω×ω×ω→ω such that for any set M coding for a Scott set M, for any set N coding for a Scott set N such that M′∈N with N-index iM, for any C∈N with N-index iC, such that UCM is a partition regular class, Φ(N,iM,iC) is an N-index for D⊇C such that UDM is an M-cohesive largeness class.
Proof.
The functional Φ does the following : It looks for M′ at index iM inside N. From M′ it computes M=⊕nXn. It then computes with M′+C the tree T containing all the elements σ such that
[TABLE]
Clearly [T] is not empty. The functional Φ then finds an N-index for an element Y∈[T]. For σ≺Y let Xσ=(⋂σ(i)=0(2ω−Xi))∩(⋂σ(i)=0Xi). We must have for every σ≺Y that Xσ∈UCM. It follows as UCM is partition regular, that for every σ≺Y, \LXσ∩UCM is a largeness class. Thus ⋂σ≺Y\LXσ∩UCM is an M-cohesive largeness class. Also M⊕Y⊕C uniformly computes a set D such that UDM=⋂σ≺Y\LXσ∩UCM. The function Φ then returns an N-index for D.
∎
Suppose that stage n we have defined Cn verifying (1)(2) and (3). Let us define Cn+1.
Note that the set Cn is coded by an element of Mn+1, and thus that Cn is computable in \cmsy;(n+2) and then computable in Mn′′. Using Lemma 2.16 we define Dn⊇Cn to be such that UDnMn=⟨UCnMn⟩ and such that Dn is uniformly Mn′′-computable. We define En+1 to be the transfer of the Mn-indices constituting Dn into Mn+1-indices, using that Mn is an element of Mn+1. So we have UEn+1Mn+1=UDnMn.
Note that as En+1 is computable in Mn′′⊕Mn+1 and thus in \cmsy;((n+1)+1). It is then coded by an element of M(n+1)+1. Note also that UEn+1Mn+1 is partition regular as it equals ⟨UCnMn⟩. Using Lemma 2.17 we uniformly find an M(n+1)+1-index of Cn+1⊇En+1 to be such that UCn+1Mn+1 is an Mn+1-cohesive largeness class.
∎
3 Generalized Pigeonhole forcing
The notion of forcing used to build solutions to the pigeonhole principle while controlling the first jump is a variant of Mathias forcing. In this section, we extend Mathias forcing to a more general notion of forcing while controlling iterated jumps, that is while tightly controlling the truth of Σn0 and Πn0 formulas.
Let M0,M1,…,Mn be countable Scott sets coded by sets M0,M1,…,Mn, respectively, satisfying (1)(2) and (3) of proposition 2.14. Let C0,C1,C2 be sequence of sets satisfying (1)(2) and (3) of proposition 2.15, that is, UCnMn is an M-cohesive largeness class, UCn+1Mn+1⊆⟨UCnMn⟩ and each Cn is coded by an element of Mn+1.
3.1 The forcing conditions
Definition 3.1**.**
For each n≥0 let Pn be the set of pairs (σ,X) such that
X∩{0,…,∣σ∣}=∅
X∈⟨UCnMn⟩
Note that X is infinite for (σ,X)∈Pn since UCnMn contains only infinite sets. Mathias forcing builds a single object G by approximations (conditions) which consist in an initial segment σ of G, and an infinite reservoir of integers. The purpose of the reservoir is to restrict the set of elements we are allowed to add to the initial segment. The reservoir therefore enriches the standard Cohen forcing by adding an infinitary negative restrain.
Definition 3.2**.**
The partial order on Pn is defined by (τ,Y)≤(σ,X)
if σ⪯τ, Y⊆X and τ−σ⊆X.
Given a collection F⊆Pn, we let GF=⋃{σ:(σ,X)∈F}.
3.2 The forcing question
We now define what we call “the forcing question” : a relation between forcing conditions p∈Pn and Σm+10 formulas for m≤n. The goal of the forcing question is to be definitionally not too complex, while being able to find extensions of conditions forcing formulas or their negation. The forcing question will also be used in the definition of the forcing relation, which is why it is introduced first.
Definition 3.3**.**
Let σ∈2<ω. Let (∃x)Φe(G,x) be a Σ10 formula. Let σ?⊢(∃x)Φ(G,x) holds if
[TABLE]
is a largeness class. Then inductively, given a Σm+10 formula (∃x)Φe(G,x) with free variable x for 1≤m<ω, we let σ?⊢(∃x)Φe(G,x) holds if
[TABLE]
is a largeness class.
For a condition p=(σ,X)∈Pn for some n<ω and a Σm+10 formula (∃x)Φe(G,x) with free variable x for some m≤n, we write p?⊢(∃x)Φe(G,x) if σ?⊢(∃x)Φe(G,x).
Proposition 3.4
Let σ∈2<ω. Let (∃x)Φe(G,x) be a Σm+10 formula for m≥0
-
The set
[TABLE]
is an upward-closed Σ10 open set if m=0. The set
[TABLE]
is an upward-closed Σ10(Cm−1⊕\cmsy;(m)) open set if m>0.
2. 2.
The relation σ?⊢(∃x)Φe(G,x) is Π10(Cm⊕\cmsy;(m+1)).
This is uniform in σ and e.
Proof.
This is done by induction on m. We start with m=0. Let (∃x)Φe(G,x) be a Σ10 formula and σ∈2<ω. It is clear that
[TABLE]
is an upward closed Σ10 class. Then σ?⊢(∃x)Φe(G,x) iff U(e,σ)∩UC0M0 is a largeness class, that is, iff for every finite set F⊆C0, the class U(e,σ)∩UFM0 is a largeness class. By Lemma 2.3, for each F⊆C0, the statement is Π20(M0) uniformly in F, and thus Π10(M0′) uniformly in F. It is then Π10(\cmsy;′) uniformly in F. Thus the whole statement is Π10(C0⊕\cmsy;′).
Suppose (1) and (2) are true for m−1, every Σm0 formula and every σ. Let σ∈2<ω and let (∃x)Φe(G,x) be a Σm+10 formula. Let
[TABLE]
Let us show (1). For each x∈ω, the formula ¬Φe(G,x) is Σm0 uniformly in x and in e. By induction hypothesis, the relation σ∪τ?⊬¬Φe(G,x) is Σ10(Cm−1⊕\cmsy;(m)) uniformly in σ∪τ in x and in e. It follows that U(e,σ) is an upward closed Σ10(Cm−1⊕\cmsy;(m)) class.
Let us now show (2). We have σ?⊢(∃x)Φe(G,x) iff U(e,σ)∩UCmMm is a largeness class. Also U(e,σ)∩UCmMm is a largeness class if for all F⊆Cm, the class U(e,σ)∩UFMm is a largeness class. By Lemma 2.3, it is a Π20(Mm) statement uniformly in F and then a Π10(Mm′) statement uniformly in F and then a Π10(\cmsy;(m+1)) statement uniformly in F. It follows that the statement “U(e,σ)∩UCmMm is a largeness class” is Π10(Cm⊕\cmsy;(m+1)).
∎
3.3 The forcing relation
The relation ?⊢ is now used to define the forcing relation.
Definition 3.5**.**
Let n∈ω. Let p=(σ,X)∈Pn.
Let (∃x)Φe(G,x) be a Σ10 formula. We define
p⊩(∃x)Φe(G,x) if (∃x)Φe(σ,x)
p⊩(∀x)Φe(G,x) if (∀τ⊆X)(∀x)Φe(σ∪τ,x)
Then inductively for 1≤m≤n. Let (∃x)Φe(G,x) be a Σm+1 formula. We define
p⊩(∃x)Φe(G,x) if there is some x∈ω such that p⊩Φe(G,x)
p⊩(∀x)¬Φe(G,x) if for every τ⊆X and every x∈ω, σ∪τ?⊢¬Φe(G,x)
Lemma 3.6
Fix 0≤m≤n. Let p∈Pn. Let (∃x)Φe(G,x) be a Σm+10 formula. Then p⊩(∀x)¬Φe(G,x) iff q?⊢¬Φe(G,x) for every x∈ω and every q≤p.
Proof.
Suppose p⊩(∀x)¬Φe(G,x) with p=(σ,X). By definition of the forcing relation and forcing extensions it is clear that q?⊢¬Φe(G,x) for every x and every q≤p. Suppose now q?⊢¬Φe(G,x) for every x and every q≤p. Given any τ⊆X we have that (σ∪τ,X−{0,…,∣σ∪τ∣}) is a valid extension of p for which we have σ∪τ?⊢¬Φe(G,x) for every x. It follows that p⊩(∀x)¬Φe(G,x).
∎
Lemma 3.7
Fix 0≤m≤n. Let (∃x)Φe(G,x) be a Σm+10 formula. Let p,q∈Pn be such that q≤p.
If p⊩(∃x)Φe(G,x) then so does q.
If p⊩(∀x)¬Φe(G,x) then so does q.
Proof.
We proceed by induction on m. It is clear for Σ10 formulas. For m>0 let (∃x)Φe(G,x) be a Σm+10 formula.
For (a), by definition, there is some x∈ω such that p⊩Φe(G,x). As Φe(G,x) is a Πm0 formula, by induction hypothesis, q⊩Φe(G,x) and thus q⊩(∃x)Φe(G,x).
For (b), by Lemma 3.6, for all x∈ω and all r≤p, r?⊢¬Φe(G,x). Thus if q≤p, also for all x and all r≤q, r?⊢¬Φe(G,x). It follows still by Lemma 3.6 that q⊩(∀x)¬Φe(G,x).
∎
3.4 The core lemmas
We now show the core lemmas. The first one shows how to find extensions to force formulas, while the second one is the classic “forcing imply truth” whenever we work with generic enough filters.
Lemma 3.8
Let p∈Pn with p=(σ,X). Let (∃x)Φe(G,x) be a Σm+10 formula for 0≤m≤n.
-
Suppose p?⊢(∃x)Φe(G,x). Then there exists q≤p with q∈Pn such that q⊩(∃x)Φ(G,x).
2. 2.
Suppose p?⊬(∃x)Φe(G,x). Then there exists q≤p with q∈Pn such that q⊩(∀x)¬Φ(G,x).
Proof.
Let p∈Pn. We start with m=0. Suppose p?⊢(∃x)Φe(G,x). Let
[TABLE]
The class U(e,σ)∩UC0M0 is a largeness class. As UC0M0 is M0-cohesive, then ⟨UC0M0⟩⊆U(e,σ). As X∈⟨UCnMn⟩⊆⟨UC0M0⟩⊆U(e,σ), there is τ⊆X such that (∃x)Φe(σ∪τ,x) holds. As ⟨UCnMn⟩ contains only infinite sets and is partition regular, X−{0,…,∣σ∪τ∣}∈⟨UCnMn⟩. Then (σ∪τ,X−{0,…,σ∪τ}) is a valid extension of (σ,X) such that (σ∪τ,X−{0,…,∣σ∪τ∣})⊩(∃x)Φe(G,x).
Suppose now p?⊬(∃x)Φe(G,x). Then the class U(e,σ)∩UC0M0 is not a largeness class. It follows that there is a finite set F⊆C0 such that U(e,σ)∩UFM0 is not a largeness class. For k let Pk be the Π10(Z) class for some Z∈M0 of covers Y0∪⋯∪Yk⊇ω such that Yi∈/U(e,σ)∩UFM0 for each i≤k. As U(e,σ)∩UFM0 is not a largeness class there must be some k such that Pk is not empty. Then there are sets Y0⊕⋯⊕Yk∈M0∩Pk. As ⟨UCnMn⟩ is partition regular and as X∈⟨UCnMn⟩ we have some i≤k such that Yi∩X∈⟨UCnMn⟩⊆UC0M0. Thus (σ,Yi∩X) is a valid extension of (σ,X) for which (σ,Yi∩X)⊩(∀x)¬Φ(G,x).
Suppose now m>0. Suppose p?⊢(∃x)Φe(G,x). Let
[TABLE]
By definition, the class U(e,σ)∩UCmMm is a largeness class. As UCmMm is Mm-cohesive and as, by Proposition 3.4, the set U(e,σ) is a Σ10(Y) for some Y∈Mm, then ⟨UCmMm⟩⊆U(e,σ). As X∈⟨UCnMn⟩⊆⟨UCmMm⟩⊆U(e,σ), there is τ⊆X such that σ∪τ?⊬¬Φe(G,x) for some x. Note that as ⟨UCnMn⟩ contains only infinite sets and is partition regular we have X−{0,…,∣σ∪τ∣}∈⟨UCnMn⟩. Also (σ∪τ,X−{0,…,∣σ∪τ∣}) is a valid extension of (σ,X) such that (σ∪τ,X−{0,…,∣σ∪τ∣})?⊬¬Φe(G,x). Now by induction hypothesis we have some Y∈Mm with (σ∪τ,X∩Y)≤(σ,X) and such that (σ∪τ,X∩Y)⊩Φe(G,x). It follows that (σ∪τ,X∩Y)⊩(∃x)Φe(G,x).
Suppose now p?⊬(∃x)Φe(G,x). Then U(e,σ)∩UCmMm is not a largeness class. It follows that there is a finite set F⊆C0 such that U(e,σ)∩UFMm is not a largeness class. For k let Pk be the Π10(Z) class for some Z∈Mm of covers Y0∪⋯∪Yk⊇ω such that Yi∈/U(e,σ)∩UFMm for each i≤k. As U(e,σ)∩UFMm is not a largeness class there must be some k such that Pk is not empty. There are sets Y0⊕⋯⊕Yk∈Mm∩Pk. As ⟨UCnMn⟩ is partition regular and as X∈⟨UCnMn⟩, there is some i≤k such that Yi∩X∈⟨UCnMn⟩⊆UCmMm. It follows that Yi∩X∈/U(e,σ). It means that for every τ⊆Yi∩X and every x∈ω, σ∪τ?⊢¬Φe(G,x). It follows that (σ,Yi∩X)⊩(∀x)¬Φe(G,x).
∎
We now sow that forcing implies truth. We define first for that the precise level of genericity that we need.
Definition 3.9**.**
Let F⊆Pn be a filter. The set F is m-generic if for every k≤m and every Σk+10 formula (∃x)Φe(G,x) there is a condition p∈F such that p⊩(∃x)Φe(G,x) or p⊩(∀x)¬Φe(G,x).
Note that if a filter is n-generic, then it is m-generic for every m<n.
Lemma 3.10
Let F⊆Pn be an n−1-generic filter. Let p∈F. Let (∃x)Φe(G,x) be a Σm+10 class for 0≤m≤n.
Suppose p⊩(∃x)Φe(G,x). Then (∃x)Φe(GF,x) holds.
Suppose p⊩(∀x)¬Φe(G,x). Then (∀x)¬Φe(GF,x) holds.
Proof.
The proof is done by induction on m. Let p∈Pn with p=(σ,X). The result is clear and well-known for m=0. Suppose now m>0 and let (∃x)Φe(G,x) be a Σm+10 formula. Suppose p⊩(∃x)Φe(G,x). Then there exists x such that p⊩Φ(G,x). By induction hypothesis Φ(GF,x) hods and then ∃x Φ(GF,x) holds.
Suppose p⊩(∀x)¬Φe(G,x). Then by Lemma 3.6 for every x and every q≤p, q?⊢¬Φe(G,x). From Lemma 3.8, for every x∈ω and every q≤p, there is some r≤q such that r⊩¬Φe(G,x). It follows that for every x, the set {r∈Pn : r⊩¬Φe(G,x)} is dense below p. As F is n−1-generic and p∈F there must be for every x some q∈F such that q⊩¬Φe(G,x). By induction hypothesis ¬Φe(GF,x) for every x and then (∀x)¬Φe(GF,x) holds.
∎
4 Cone avoidance under Δn0 reductions
We show in this section the first and third theorems of the introduction — Theorem 1.2 and Theorem 1.4. The proof of Theorem 1.3 will be postponed to the next section, where it will be achieved together with hyperarithmetic cone avoidance. We fix a set A0⊔A1=ω. We sometimes write A for A0 (with then ω−A=A1).
Unfortunately the above forcing is definitionally a bit too complex : the forcing question for Σm+10 statements is Πm+20, whereas we would need it to be Σm+10.
For this reason, we need to plug upon the previous forcing another forcing notion, used only for “the last step” in formula induction. The drawbacks of this other forcing notions is that we are compelled to build two generic objects : one inside A0 and one inside A1. We then used the pairing argument first designed by Dzhafarov and Jockusch [6] to show that one of the object we build is sufficiently generic in the sense of Definition 3.9.
4.1 Another forcing on the top
Definition 4.1**.**
Fix n≥0. Let Qn denote the set of conditions (σ0,σ1,X) such that
σi⊆Ai for every i<2
X∩{0,…,maxi∣σi∣}=∅
X∈Mn
X is infinite if n=0 and X∈⟨UCn−1Mn−1⟩ if n≥1.
A forcing condition (σ0,σ1,X)∈Qn is valid for side i if X∩Ai∈⟨UCn−1Mn−1⟩ for n>0 and if X∩Ai is infinite for n=0.
By definition of a Turing ideal M countable coded by a set M, then M can be written as {Z0,Z1,…} with M=⨁iZi.
We then say that i is an M-index of Zi. Thanks to the notion of index, any Qn-condition can be finitely presented as follows. An index of a Qn-condition c=(σ0,σ1,X) is a tuple (σ0,σ1,a) where a is an Mn-index for X.
Definition 4.2**.**
The partial order on Qn is defined by
[TABLE]
if for every i<2, (τi,Y)≤(σi,X).
Given a condition c=(σ0,σ1,X) and i<2, we write c[i]=(σi,X).
Each Qn-condition c represents two Pn−1-conditions c[0] and c[1].
We now design a disjunctive forcing question which builds upon the forcing question of Pn conditions. The difference is that it is only used at the last step of the induction of formulas.
Definition 4.3**.**
Let c=(σ0,σ1,X)∈Q0 and let (∃x)Φe0(G,x) and (∃x)Φe1(G,x) be two Σ1 formulas. Define the relation
[TABLE]
to hold if for every 2-cover Z0∪Z1=X, there is some side i<2, some finite set ρ⊆Zi and some x∈ω such that Φei(σi∪ρ,x) holds.
Let n>0. Let c=(σ0,σ1,X)∈Qn and let (∃x)Φe0(G,x) and (∃x)Φe1(G,x) be two Σn+10 formulas. Define the relation
[TABLE]
to hold if for every 2-cover Z0∪Z1=X, there is some side i<2, some finite set ρ⊆Zi and some x∈ω such that σi∪ρ?⊬¬Φei(G,x) holds.
4.2 The complexity aspects of the Qn forcing
This new forcing question now has the right definitional complexity
Lemma 4.4
Let n∈ω. Let c∈Qn and let (∃x)Φe0(G,x) and (∃x)Φe1(G,x) be two Σn+10 formulas. The relation
[TABLE]
is Σ10(Y) for some Y∈Mn. Moreover an Mn-index for Y can be found uniformly in an index for c.
Proof.
By compactness, for n=0 the relation holds if there is a finite set E⊆X such that for every E0∪E1=E, there is some i<2, some ρ⊆Ei and xn∈ω such that Φei(σi∪ρ,x) holds, which is a Σ10(X) event for X∈M0.
For n>0 the relation holds if there is a finite set E⊆X such that for every E0∪E1=E, there is some i<2, some ρ⊆Ei and xn∈ω such that σi∪ρ?⊬¬Φei(G,x) holds.
By Proposition 3.4, this statement is Σ10(X⊕Cn−1⊕\cmsy;(n)) and then Σ10(Y) for some Y∈Mn.
∎
Before we continue, we need to study the effectivness of Lemma 3.8 about the forcing question for the Pn forcing.
Lemma 4.5
Let n>0. Let c∈Qn with c=(σ0,σ1,X). Let (∃x)Φe(G,x) be a Σm+10 formula for 0≤m<n. Let p=c[i] for some i<2 with p=(σ,X).
-
Suppose p?⊢(∃x)Φe(G,x). The forcing condition q≤p of Lemma 3.8 which forces (∃x)Φe(G,x) can always be of the form (σ∪τ,X∩Y) for Y∈Mm where τ and an Mm-index for Y can be found uniformly in any PA over \cmsy;(n+1). If furthermore c is valid on side i one can ensure τ⊆Ai∩X uniformly in A⊕P for any P which is PA over \cmsy;(n+1).
2. 2.
Suppose p?⊬(∃x)Φe(G,x). The forcing condition q≤p of Lemma 3.8 which forces (∀x)¬Φe(G,x) can always be of the form (σ,X∩Y) for Y∈Mm where an Mm index for Y can be found uniformly in any PA over \cmsy;(n+1).
Proof.
Suppose p?⊢(∃x)Φe(G,x). By the proof of Lemma 3.8 there is τ⊆X such that (∃x)Φe(σ∪τ,x) holds if m=0 and such that σ∪τ?⊬¬Φe(G,x) for some x if m>0. Note that if X∩Ai∈⟨UCnMn⟩, still refering to the proof of Lemma 3.8 we can ensure τ⊆X∩Ai. Also finding τ is a Σ10(X) event if m=0 and a Σ10(X⊕Cm−1⊕\cmsy;m) if m>0 (resp. a Σ10(X⊕A) if m=0 and a Σ10(A⊕X⊕Cm−1⊕\cmsy;m) if m>0). As X∈Mn we can then find τ uniformly in \cmsy;n+1 (resp. in \cmsy;n+1⊕A).
Suppose now p?⊬(∃x)Φe(G,x). By the proof of Lemma 3.8 there is a finite set F⊆Cm such that U(e,σ)∩UFM0 is not a largeness class. Note that finding F is a Σ10(\cmsy;(m+2)) event. It can then be found uniformly in \cmsy;(m+2) and then uniformly in \cmsy;(n+1). Still by the proof of Lemma 3.8 there must be some k such that Pk is not empty where Pk is the Π10(Z) class for some Z∈Mm of covers Y0∪⋯∪Yk⊇ω such that Yi∈/U(e,σ)∩UFMm for each i≤k. Searching for the first such k is a Σ10(\cmsy;m+1) event. Once found, one also compute uniformly in Mm an index for Y0⊕⋯⊕Yk∈Mm∩Pk. As ⟨UCn−1Mn−1⟩ is partition regular and as X∈⟨UCn−1Mn−1⟩, there is some i≤k such that Yi∩X∈⟨UCn−1Mn−1⟩⊆UCmMm. Finding the right Yi for i≤k is a Π10(Cn−1⊕(Yi∩X⊕Mn−1)′) event. As X∈Mn it can then be found in any PA over \cmsy;(n+1).
∎
We shall now show the extension of Lemma 3.8 for the Qn forcing conditions.
Lemma 4.6
Let n∈ω. Let c∈Qn and let (∃x)Φe0(G,x) and (∃x)Φe1(G,x) be two Σn+10 formulas.
If c?⊢(∃x)Φe0(G0,x)∨(∃x)Φe1(G1,x), then there is some d≤c and some i<2 such that
[TABLE]
If c?⊬(∃x)Φe0(G0,x)∨(∃x)Φe1(G1,x), then there is some d≤c and some i<2 such that
[TABLE]
Moreover an index of d can be found in A⊕P for any set P which is PA over \cmsy;(n+1) uniformly in an index of c, e0 and e1.
Proof.
Say c=(σ0,σ1,X). Both (a) and (b) are trivial in the case n=0. We treat the case n>0.
(a) Let Z0=X∩A0 and Z1=X∩A1. Unfolding the definition of the forcing question, there is some i<2, some ρ⊆Zi and x∈ω such that σi∪ρ?⊬¬Φei(Gi,x). By Lemma 4.5 we have a set Y∈Mn such that (σi∪ρ,X∩Y)≤(σi∪ρ,X) and (σi∪ρ,X∩Y)⊩(∃x)Φei(Gi,x). Note that d=(σi∪ρ,σi−1,X∩Y) is a valid extension of c. From Proposition 3.4 finding ρ is a Σ10(A⊕X⊕Cn−1⊕\cmsy;(n)) event. From Lemma 4.5 one can then find and Mn-index of Y in any set P which is PA over \cmsy;(n+1). Overall an index for d can be found in A⊕P for any set P which is PA over \cmsy;(n+1), uniformly in an index of c, e0 and e1.
(b) Let D be the Π10(Mn) class of all Z0⊕Z1 with Z0∪Z1=X, such that for every i<2, every ρ⊆Zi, and every x∈ω we have σ∪ρ?⊢¬Φei(Gi,x). Let Z0⊕Z1∈D such that Z0⊕Z1∈Mn. Since ⟨UCn−1Mn−1⟩ is a partition regular class containing X, there is some i<2 such that Zi∈⟨UCn−1Mn−1⟩. Define the Qn-condition d=(σ0,σ1,Zi). Then d[i]⊩(∀x)¬Φei(G,x). Finding the right Zi is a Π10(Cn−1⊕(X⊕Zi⊕Mn−1)′) event. It can the be found uniformly in any set P which is PA over \cmsy;(n+1). This completes the proof of the lemma.
∎
4.3 The degenerate forcing question
The forcing question will be used with a disjunctive argument. Doing so we will build two generics, one in A0 and one in A1. Possibly only one of them will force every Σn0 statement or their negation. The challenge is to ensure in the same time that the same generic also forces every Σm0 statement or their negation for m<n, so that we can then apply Lemma 3.10 saying that forcing implies truth. It is only possible to do so on side i under the assumption that our current forcing condition is valid on side i:
Lemma 4.7
Let n≥0. Let c∈Qn be valid for side i. Let m<n and let (∃x)Φe(G,x) be a Σm+10 formula. Then one can find uniformly in A⊕P for any P which is PA over \cmsy;(n+1), a condition d≤c such that d[i]⊩(∃x)Φe(G,x) or d[i]⊩(∀x)¬Φe(G,x)
Proof.
We ask if (σi,X)?⊢(∃x)Φe(G,x). From Lemma 4.5 if the answer is yes there is a τ⊆X∩Ai and a set Y∈Mn such that d=(σi∪τ,Y∩X∩Ai)?⊢(∃x)Φe(G,x). If no then there is Y∈Mn such that d=(σi∪τ,Y∩X∩Ai)?⊢(∀x)¬Φe(G,x).
In any case from Lemma 4.5 an index for d can be found uniformly in A⊕P for any P which is PA over \cmsy;(n+1).
∎
The difficulty is now to make sure that the side i which turns out to be the right one, is also always a valid one. To do so we need a “degenerate forcing question”.
Definition 4.8**.**
Let n>0. Let c∈Qn. Let U be Σ10(\cmsy;(n)) large open set. Let (∃x)Φe(G,x) be a Σn+10 formula. We define
[TABLE]
to hold if for every Z0∪Z1=X, there exists i<2 such that Zi∈U and such that there is some ρ⊆Zi and xn∈ω for which σi∪ρ?⊬¬Φe(G,x) holds.
Lemma 4.9
Let n>0. Let (σ0,σ1,X)∈Qn. Let U⊇⟨UCn−1Mn−1⟩ be Σ10(\cmsy;(n)) large open set such that X∩Ai−1∈/U. Let (∃x)Φe(G,x) be a Σn+10 formula. The statement
[TABLE]
is Σ10(Y) for some Y∈Mn. Moreover an Mn-index for Y can be found uniformly in an index for c.
Proof.
The relation holds if there is a finite set E⊆X such that for every E0∪E1=E, there is some i<2, some ρ⊆Ei and xn∈ω such that [Ei]⊆U and σi∪ρ?⊬¬Φei(G,x) holds.
By Proposition 3.4, this statement is Σ10(X⊕Cn−1⊕\cmsy;(n)) and then Σ10(Y) for some Y∈Mn.
∎
Lemma 4.10
Let n>0. Let (σ0,σ1,X)∈Qn. Let U⊇⟨UCn−1Mn−1⟩ be Σ10(\cmsy;(n)) large open set such that X∩Ai−1∈/U. Let (∃x)Φe(G,x) be a Σn+10 formula.
Suppose (σ0,σ1,X)?⊢U(∃x)Φe(G,x).
Then there exists d≤c such that d[i]⊩(∃x)Φe(G,x)
Suppose (σ0,σ1,X)?⊬U(∃x)Φe(G,x).
Then there exists d≤c such that d[i]⊩(∀x)¬Φe(G,x)
Furthermore an index for d can be found in A⊕P for any set P which is PA over \cmsy;(n+1), uniformly in an index for c.
Proof.
Say c=(σ0,σ1,X).
(a) Let Z0=X∩A0 and Z1=X∩A1. Unfolding the definition of the forcing question, there is some j<2 such that Zj∈U and such that for some ρ⊆Zj and x∈ω we have σj∪ρ?⊬¬Φei(Gi,x). By hypothesis Zi−1∈/U. Thus i=j and by Lemma 4.5 we have a set Y∈Mn such that (σi∪ρ,X∩Y)≤(σi∪ρ,X) and (σi∪ρ,X∩Y)⊩(∃x)Φei(Gi,x). Note that (σi∪ρ,σi−1,X∩Y) is a valid extension of (σ0,σ1,X). From Proposition 3.4 finding ρ is a Σ10(A⊕X⊕Cn−1⊕\cmsy;(n)) event. From Proposition 3.4 finding ρ is a Σ10(A⊕X⊕Cn−1⊕\cmsy;(n)) event. From Lemma 4.5 one can then find and Mn-index of Y in any set P which is PA over \cmsy;(n+1). Overall an index for d can be found in A⊕P for any set P which is PA over \cmsy;(n+1), uniformly in an index of c, e0 and e1.
(b) Let D be the Π10(Mn) class of all Z0⊕Z1 with Z0∪Z1=X, such that for every i<2, Zi∈/U or for every ρ⊆Zi, and every x∈ω we have σ∪ρ?⊢¬Φe(G,x). Let Z0⊕Z1∈D be such that Z0⊕Z1∈Mn. Since ⟨UCn−1Mn−1⟩ is a partition regular class containing X, there is some i<2 such that Zi∈⟨UCn−1Mn−1⟩. Since U⊇⟨UCn−1Mn−1⟩ we must have Zi∈U and thus d=(σ0,σ1,Zi) is a Qn extension of (σ0,σ1,X) such that d[i]⊩(∀x)¬Φei(G,x). Finding the right Zi is a Π10(Cn−1⊕(X⊕Zi⊕Mn−1)′) event. It can the be found uniformly in any set P which is PA over \cmsy;(n+1). This completes the proof of the lemma.
∎
We are now ready to derive our main theorems
4.4 Preservation of non-Σn0 definitions
Our first application shows the existence, for every instance of the pigeonhole principle, of a solution which does not collapse the definition of a non-Σn0 set into a Σn0 one. This corresponds to preservation of one non-Σn0 definition, following the terminology of Wang who showed that given A non Σn0, any non-empty Π10 class contains an element X such that A is not Σn0(X) [31].
Theorem 4.11
Fix n≥0 and let B be a non-Σn+10 set. For every set A, there is an infinite set G⊆A or G⊆A such that B is not Σn+10(G).
Proof.
We let A0=A and A1=A. We work with the Qn forcing. By Wang [31, Theorem 3.6.], we can also assume that B is not Σ10(Mn). We also suppose n>0, the case n=0 was proved by Dzhafarov and Jockusch [6].
The asymmetric case:
Suppose first there exists a Qn-condition b=(σ0,σ1,X) which is invalid for some side i−1<2. Let U⊆⟨UCn−1Mn−1⟩ be a Σ10(\cmsy;(n)) largeness class such that X∩Ai∈/U. Note that every condition c≤b must be valid for side i as otherwise we would have Y∩A0 and Y∩A1 both not in ⟨UCn−1Mn−1⟩ for some Y∈⟨UCn−1Mn−1⟩ which would contradict that ⟨UCn−1Mn−1⟩ is partition regular.
We then work below b=(σ0,σ1,X). Given c≤b and a Σn+10 statement (∃x)Φe(G,x,y) with one free variable y, the set {y : c?⊢U(∃x)Φe(G,x,y)} is Σ10(Mn) from Lemma 4.9. As B is not Σ10(Mn) there exists y∈B such that d?⊬U(∃x)Φe(G,x,y) or there exists y∈/B such that c?⊢U(∃x)Φe(G,x,y). In the first case using Lemma 4.10 we find an extension d≤c such that d[i]⊩(∀x)¬Φe(G,x,y) and in the second case an extension d≤c such that d[i]⊩(∃x)Φe(G,x,y).
Now given c≤b and a Σm+10 statement (∃x)Φe(G,x) for m<n we ask if c[i]?⊢(∃x)Φe(G,x). Using Lemma 4.5 if the answer is positive we find an extension d≤c such that d[i]⊩(∃x)Φe(G,x) and otherwise we find an extension d≤c such that d[i]⊩(∀x)¬Φe(G,x).
In the end we build a n−1-generic filter F⊆Pn−1 such that GF⊆Ai with in addition that some p forces B={y : (∃x)Φe(G,x,y)} for every Σn+10 statement (∃x)Φe(G,x,y). By Lemma 3.10 we then have that B={y : (∃x)Φe(GF,x,y)} for every Σn+10 statement (∃x)Φe(G,x,y). Thus B is not Σn+10(GF).
The symmetric case:
Suppose now that every Qn-condition c=(σ0,σ1,X) is valid for both sides. Given a condition c and two Σn+10 statement (∃x)Φe0(G,x,y),(∃x)Φe1(G,x,y) with one free variable y, the set {y : c?⊢(∃x)Φe0(G,x,y)∨(∃x)Φe1(G,x,y)} is Σ10(Mn) from Lemma 4.4. As B is not Σ10(Mn) there exists y∈B such that c?⊬(∃x)Φe0(G,x,y)∨(∃x)Φe1(G,x,y) or there exists y∈/B such that c?⊢(∃x)Φe0(G,x,y)∨(∃x)Φe1(G,x,y). In the first case using Lemma 4.6 we find an extension d≤c such that d[i]⊩(∀x)¬Φei(G,x,y) for some i<2 and in the second case an extension d≤c such that d[i]⊩(∃x)Φei(G,x,y) for some i<2.
Now given c and a Σm+10 statement (∃x)Φe(G,x) for m<n we find using Lemma 4.5 an extension d≤c such that d[i]⊩(∀x)Φe(G,x) or d[i]⊩(∀x)¬Φe(G,x) for both i=0 and i=1.
In the end we have one filter F⊆Qn giving two filters F0,F1⊆Pn−1 corresponding to side [math] and 1, which are both n−1-generic and such that GF0⊆A0 and GF1⊆A1. Also for every Σn+10 formulas (∃x)Φe0(G,x,y),(∃x)Φe1(G,x,y) we have d∈F such that d[0] forces B={y : (∃x)Φe0(G,x,y)} or d[1] forces B={y : (∃x)Φe1(G,x,y)}. By a usual pairing argument, there must be i<2 such that for every Σn+10 formula (∃x)Φe(G,x,y) we have d∈F such that d[i] forces B={y : (∃x)Φe(G,x,y)}. By Lemma 3.10 we then have that B={y : (∃x)Φe(GFi,x,y)} for every such formula and then that B is not Σn+10(GF).
∎
The following corollary would correspond to strong iterated jump cone avoidance of RT21,
following the terminology of Wang [32].
Theorem** **(Main Theorem 1 (Theorem 1.2))
Fix n≥0. Let B be non ∅(n)-computable. Every set A has an infinite subset H⊆A or H⊆A such that B is not H(n)-computable.
Proof.
Given a set B which is not ∅(n)-computable, either B or B is not Σn+10. By Theorem 4.11, for every set A, there is an infinite set H⊆A or H⊆A such that either B or B is not Σn+10(H), hence such that B is not H(n)-computable.
∎
4.5 Preservation of Δn0 hyperimmunities
Our second application concerns the ability to prevent solutions from computing fast-growing functions. Recall the definition of hyperimmunity.
Definition 4.12**.**
A function f dominates a function g if f(x)≥g(x)
for every x. A function f is X-hyperimmune if it is not dominated by any X-computable function.
The following lemma is proven by Downey et al. [5, Lemma 3.3].
Lemma 4.13** **([5])
For every k≤ω and every Z, for any nondecreasing functions (fi)i<k which are Z-hyperimmune, there is a G and sets (Ai)i<k such that none of the Ai is Σ10(Z⊕G), but for any i and any function h dominating fi, Ai is Σ10(Z⊕G⊕h).
Theorem 4.14
Fix a ∅(n)-hyperimmune function f. For every set A, there is an infinite set H⊆A
or H⊆A such that f is H(n)-hyperimmune.
Proof.
By Lemma 4.13, letting Z=∅(n), there is a set G and a set B such that B is not Σ10(∅(n)⊕G) but for any function h dominating f, B is Σ10(∅(n)⊕G⊕h).
By the jump inversion theorem, there is a set Q such that Q(n)≡T∅(n)⊕G.
In particular, B is not Σ10(Q(n)), so it is not Σn+10(Q).
By Theorem 4.11, there is an infinite set H⊆H or H⊆A such that B is not Σn+10(H⊕Q). In particular B is not Σ10((H⊕Q)(n)) and therefore not Σ10(H(n)⊕G). Suppose for the contradiction that f is dominated by an H(n)-computable function h. Then B is Σ10(∅(n)⊕G⊕h), hence B is Σ10(H(n)⊕G). Contradiction.
∎
4.6 Lown solutions
An effectivization of the forcing construction enables us to obtain lowness results for the infinite pigeonhole principle. The existence of low2 solutions for Δ20 sets, and of low2 cohesive sets for computable sequences of sets, was proven by Cholak, Jockusch and Slaman [2, sections 4.1 and 4.2]. The existence of low3 cohesive sets for Δ20 sequences of sets was proven by Wang [30, Theorem 3.4]. Wang [30, Questions 6.1 and 6.2] and the second author [18, Question 5.4] asked whether such results can be generalized for every Δn+10 instances of the pigeonhole and every Δn0 instances of cohesiveness. We answer positively both questions.
Theorem 4.15
Let n≥0. For every \cmsy;(n+1)-computable set A and every P PA over ∅(n+1), there is an infinite set G⊆A or G⊆A such that G(n+1)≤TP.
Proof.
The case n=0 is proven by Cholak, Jockusch and Slaman [2, sections 4.1 and 4.2]. Suppose n>0. Fix P and A, and let A0=A and A1=A. We work with the Qn forcing. We again have two constructions, based on whether every condition have both valid sides or not.
Asymmetric case:
Suppose first there exists a Qn-condition b=(σ0,σ1,X) which is invalid for some side i−1<2. Let U⊆⟨UCn−1Mn−1⟩ be a Σ10(\cmsy;(n)) largeness class such that X∩Ai∈/U. Note that every condition c≤b must be valid for side i as otherwise we would have Y∩A0 and Y∩A1 both not in ⟨UCn−1Mn−1⟩ for some Y∈⟨UCn−1Mn−1⟩ which would contradict that ⟨UCn−1Mn−1⟩ is partition regular. We then work below b=(σ0,σ1,X).
Given c≤b and a Σn+10 statement (∃x)Φe(G,x,y) with one free variable y, we ask if c?⊢U(∃x)Φe(G,x,y). From Lemma 4.9 we obtain the answer uniformly in \cmsy;(n+1) and thus uniformly in P. If the answer is yes, from Lemma 4.10 we find uniformly in P an extension d≤c such that d[i]⊩(∀x)¬Φe(G,x,y) and in the second case an extension d≤c such that d[i]⊩(∃x)Φe(G,x,y).
Now given c≤b and a Σm+10 statement (∃x)Φe(G,x) for m<n we ask if c[i]?⊢(∃x)Φe(G,x). From Proposition 3.4 we obtain the answer uniformly in \cmsy;(n+1) and thus uniformly in P. Using Lemma 4.5 if the answer is positive we find uniformly in P an extension d≤c such that d[i]⊩(∃x)Φe(G,x) and otherwise we find an extension d≤c such that d[i]⊩(∀x)¬Φe(G,x).
In the end we build effectively in P a n-generic filter F⊆Pn−1 such that GF⊆Ai. Using lemma 3.10 and by construction, P can also decide every Σn+10(GF) statement. Thus (GF)(n+1)≤TP.
The symmetric case:
Suppose now that every Qn-condition c=(σ0,σ1,X) is valid for both sides. Given a condition c and two Σn+10 statement (∃x)Φe0(G,x,y),(∃x)Φe1(G,x,y) with one free variable y, we ask if c?⊢(∃x)Φe0(G,x,y)∨(∃x)Φe1(G,x,y). From Lemma 4.4 we obtain the answer uniformly in \cmsy;(n+1) and then uniformly in P. Using Lemma 4.6 we find uniformly in P an extension d≤c such that d[i]⊩(∃x)Φei(G,x,y) or d[i]⊩(∀x)¬Φei(G,x,y) for some i<2.
Now given c and a Σm+10 statement (∃x)Φe(G,x) for m<n we ask if c[0]?⊢(∃x)Φe(G,x). From Proposition 3.4 we obtain the answer uniformly in \cmsy;(n+1) and thus uniformly in P. Using Lemma 4.5 if the answer is positive we find uniformly in P an extension d≤c such that d[0]⊩(∃x)Φe(G,x) and otherwise we find an extension d≤c such that d[0]⊩(∀x)¬Φe(G,x). We then ask whether d[1]?⊢(∃x)Φe(G,x) and find similarly an extension h≤d such that h[1]⊩(∀x)¬Φe(G,x) or h[1]?⊢(∃x)Φe(G,x).
In the end we build effectively in P a filter F⊆Qn giving two filters F0,F1⊆Pn−1 corresponding to side [math] and 1, which are both n−1-generic and such that GF0⊆A0 and GF1⊆A1. By a pairing argument there must be i<2 such that Fi is n-generic. Using lemma 3.10 and by construction, P can decide every Σn+10(GFi) statement. Thus (GFi)(n+1)≤TP.
∎
Theorem** **(Main theorem 3 (Theorem 1.4))
Fix n≥0. Every \cmsy;(n+1)-computable set A has an infinite subset H⊆A or H⊆A of lown+2 degree.
Proof.
By the relativized low basis theorem [10], there is some P PA over ∅(n+1) such that P′≤T∅(n+2). By Theorem 4.15, there is an infinite set G⊆A or G⊆A such that G(n+1)≤TP. In particular, G(n+2)≤TP′≤T∅(n+2). Thus G is of lown+2 degree.
∎
5 Arithmetic and Hyperarithmetic cone avoidance
In this section, we extend the jump control of solutions to the pigeonhole principle to ordinal iterations of the jump. We then derive a proof of strong cone avoidance for arithmetic and hyperarithmetic reductions. We prove in the mean time cone avoidance for arithmetical reductions. The reader already familiar with higher recursion theory may jump directly to section 5.1.7 where we give the general strategy which will be used to show hyperarithmetic cone avoidance.
5.1 Background on higher recursion theory
5.1.1 Computable ordinals
We let ω1ck denote the first non-computable ordinal. There is a Π11 set O1⊆ω such that each o∈O1 codes for an ordinal α<ω1ck and each ordinal α<ω1ck has a unique code in O1. Furthermore given that o∈O1, one can computably recognize if o codes for [math], if o codes for a successor ordinal α+1, in which case we can uniformly and computably produce a code in O1 for α, and if o codes for a limit ordinal supnβn, in which case we can uniformly and computably produce for each n codes in O1 for βn. See [23] for more details about O1. In this section, we manipulate each ordinal α<ω1ck via its respective code in O1. To simplify the reading, we use the notation α instead of the code for α.
5.1.2 The effective Borel sets
We also use codes for effective Borel subsets of ω or of 2ω : For α<ω1ck a code for a Σα+10 set B=⋃n<ωBn is the code of a function that effectively enumerate codes for each Πα0 set Bn. A code for a Πα+10 set B=⋂n<ωBn is the code of a function that effectively enumerate codes for each Σα0 set Bn. For α=supnβn limit a code of a Σα0 set B=⋃n<ωBβn is the code of a function that effectively enumerate codes for each Πβn0 set Bβn with supnβn=α. The code of a Πα0 set B=⋂n<ωBβn is the code of a function that effectively enumerate codes for each Σβn0 set Bβn with supnβn=α. We also assume the codes for effective Borel sets include some information so that we can computably distinguish Πα0 from Σα0 codes as well as distinguish if α=1, if α is successor or if it is limit.
5.1.3 The iterated jumps
We use such codes to iterate the jump through the ordinals:
-
\cmsy;(0)=∅
2. 2.
\cmsy;(α+1)=(\cmsy;(α))′
3. 3.
\cmsy;(supnαn)=⊕n∈ω\cmsy;(αn)
Note that for n<ω the set \cmsy;(n) is Σn0 and complete for Σn0 questions. Above the first limit ordinal the situation is slightly different : \cmsy;(ω) is Δω0 and not Σω0. Also given α≥ω we have that \cmsy;(α+1) is Σα0 and complete for Σα0 questions.
Proposition 5.1
Let n∈ω.
-
Let m>0. The set {X : n∈X(m)} is a Σm0 class.
2. 2.
Let α be limit. The set {X : n∈X(α)} is a Δβ0 class for some β<α.
3. 3.
Let α=β+1 with β≥ω. The set {X : n∈X(α)} is a Σβ0 class.
Proof.
The set {X : n∈X′} is clearly Σ10. Let m>1. the set {X : n∈X(m)} equals
[TABLE]
This is by induction a Σm0 set.
Let α be limit. Let p1,p2 be projections of the pairing function, that is, x=⟨p1(x),p2(x)⟩. Then {X : n∈X(α)} equals {X : p1(n)∈X(p2(n))}, which is a Δβ0 set for β<α.
Let α=β+1. The set {X : n∈X(β+1)} equals
[TABLE]
This is by induction a Σβ0 class.
∎
Proposition 5.2
Let Φ be a functional. Let n,i∈ω.
-
Let m>0. The set {X : ∃t Φ(X(m),n)[t]↓=i} is a Σm+10 class.
2. 2.
Let α≥ω. The set {X : ∃t Φ(X(α),n)[t]↓=i} is a Σα0 class.
Proof.
Trivial using Proposition 5.1
∎
5.1.4 Π11 and Σ11 sets of integers
We previously mentioned a Π11 set O1 of unique notations for ordinals. This set is included in Kleene’s O, the set of all the constructible codes for the computable ordinals. Given an ordinal α<ω1ck, let O<α denote the elements of O which code for an ordinal strictly smaller than α. Each O<α is Δ11 uniformly in α (it actually is always a Σα+10 set [14]). It is well-known that O is a Π11-complete set [23], that is, for any Π11 set B⊆ω there is a computable function f:ω→ω such that n∈B↔f(n)∈O. Let us define Bα={n : f(n)∈O<α}. In particular, each Bα is Δ11 uniformly in α and B=⋃α<ω1ckBα. In particular B is a Σω1ck0 set. Note that contrary to Σα0 sets for α<ω1ck, the Σω1ck0 are not described with a computable code, but rather with a Π11 set of codes for all the Πα0 that constitutes the Σω1ck0 set B. With a little hack, we can even make sure that at most one new element appears in each Bα. For this reason, we often see Π11 sets as enumerable along the computable ordinals.
By complementation a Σ11 set B⊆ω can be seen as co-enumerable along the computable ordinals and we have B=⋂α<ω1ckBα where each Bα is Δ11 uniformly in α. We also say in this case that B is Πω1ck0.
5.1.5 Σ11-boundedness
A central theorem when working with Σ11 and Π11 sets is Σ11-boundedness:
Theorem 5.3** **(Σ11-boundedness [26])
Let B be a Σ11 set of codes for ordinals, then the supremum of the ordinals coded by elements of B is strictly smaller than ω1ck.
We mostly here use the following corollary:
Corollary 5.4
Let f:ω→ω1ck be a total Π11 function. Then supnf(n)=α<ω1ck.
Note that f:ω→ω1ck means the range of f is a subset of O1. The corollary comes from the fact that if f is total, then it becomes Δ11 and its range is then a Σ11 set of codes for ordinals. As an example we apply here Σ11-boundedness to show a simple fact that will be needed later : adding an ω-bounded quantifier to a Σω1ck0 or a Πω1ck0 set does not change its complexity.
Lemma 5.5
Every Σω1ck+10 set of integers is Πω1ck0.
Proof.
Let B be Σω1ck+10, that is, B=⋃n∈ω⋂α∈ω1ckBn,α where each Bn,α is Σα0 uniformly in α. Then B is Πω1ck0 via the following equality : ⋃n∈ω⋂α∈ω1ckBn,α=⋂α∈ω1ck⋃n∈ω⋂β∈αBn,β.
∎
It is clear that if m is in the leftmost set it is also in the rightmost set. The reader should have no trouble to apply Σ11-boundedness to show that if m is not in the leftmost set, then it is not in the rightmost one.
5.1.6 Π11 and Σ11 sets of reals
Given X∈2ω we let OX be the set of X-constructible codes for X-computable ordinals. We let ω1X≥ω1ck be the smallest non X-computable ordinal. For α<ω1X, we let O<αX be the elements of OX coding for an ordinal strictly smaller than α.
One can show that a set B⊆2ω is Π11 iff there exists some e∈ω such that B={X : e∈OX}, that is, B is the set of elements relative to which e codes for an X-computable ordinal. In particular, B=⋃α<ω1{X : e∈O<αX}. Note that the union may go up to ω1, indeed, Π11 sets of reals are not necessarily Borel.
A Π11 set of particular interest is the set of element X such that ω1X>ω1ck. The set is Borel, but not effectively. One can even prove that it contains no non-empty Σ11 subset : this is known as the Gandy Basis theorem (see Sacks [23, III.1.5]):
Theorem 5.6** **(Gandy Basis theorem)
Let B⊆2ω be a non-empty Σ11 set. Then there exists X∈B such that ω1X=ω1ck.
5.1.7 The general strategy to show hyperarithmetic cone avoidance
Let Z be non Δ11. Our goal is to build a generic G⊆A or G⊆ω−A such that Z is not Δ11(G). This is done in two steps: first show that Z is not G(α)-computable for any α<ω1ck and second show that ω1G=ω1ck, so in particular we cannot have that Z is G(α)-computable for ω1ck≤α<ω1G.
The first part is simply an iteration of the forcing through the computable ordinals, and raises no particular issue. This is done in Section 5.3.
The second part is a little bit trickier but still follows a canonical technique, which has often been used, up to some cosmetic changes in its presentation, to show this kind of preservation theorem (see for instance [8], [22] or [27]) : Suppose ω1G>ω1ck, in particular there is an element e∈OG which codes for ω1ck, that is e is the code of a functional with ∀n Φe(G,n)↓∈O<ω1ckG with supn∣Φe(G,n)∣=ω1ck where ∣Φe(G,n)∣ is the ordinal coded by Φe(G,n). All we have to do is to show that such a code e does not exist. Given e we show that one of the following holds:
-
∃n ∀α<ω1ck Φe(G,n)∈/O<αG
2. 2.
∃α<ω1ck ∀n Φe(G,n)∈O<αG
Each set {X : Φe(X,n)∈/O<αX} is Δ11 uniformly in α. It follows that the set {X : ∃n ∀α<ω1ck Φe(X,n)∈/O<αX} is a Σω1ck+10 set of reals. Contrary to Σω1ck+10 sets of integers, such sets cannot be simplified. We are then required to extend our forcing questions in order to control the truth of Σω1ck+10-statements. This is what will be done in Section 5.4.
5.2 Preliminaries
We now design a notion of forcing for controlling the α-jump of solutions
to the pigeonhole principle. Unlike the notion of forcing for controlling finite iterations of the jump, this notion is non-disjunctive and initially fixes the side of the instance A from which we will construct a solution. This is at the cost of a forcing question whose definitional complexity is higher than the question it asks.
Proposition 5.7
There is a sequence of sets {Mα}α<ω1ck such that:
-
Mα codes for a countable Scott set Mα
2. 2.
\cmsy;(α) is uniformly coded by an element of Mα
3. 3.
Each Mα′ is uniformly computable in \cmsy;(α+1)
Proof.
In the proof of Proposition 5.7 we show how to build a functional Φ:2ω→2ω such that for any oracle X, we have that M′=Φ(X′) is such that M=⊕n∈ωXn codes for a Scott set M with X0=X.
We simply use here this functionnal with any \cmsy;(α+1) for α<ω1ck.
∎
Note \cmsy;(β) is computable in \cmsy;(α) for β<α in a uniform way : there is a unique computable function f(\cmsy;(α),α,β) which outputs \cmsy;(β) for every β<α. Also Proposition 5.7 implies that Mβ is computable in \cmsy;(α) for β<α and similarly, the computation is uniform in β,α.
We now turn to an extention of proposition 2.15 to the computable ordinals, for which we reuse lemma 2.16 and lemma 2.17.
Proposition 5.8
There is a sequence of sets {Cα}α<ω1ck such that:
-
UCαMα is an Mα-cohesive largeness class
2. 2.
β<α implies UCαMα⊆⟨UCβMβ⟩
3. 3.
Each Cα is coded by an element of Mα+1 uniformly in α and Mα+1.
Proof.
Let Xiα be the element of Mα of code i, so that each Mα=⊕iXiα. Let us argue that there is a computable function f:ω1ck×ω1ck×ω such that whenever β<α, then Xiβ=Xf(α,β,i)α: Given an ordinal α the function f considers the Mα-code of \cmsy;(α) (which is uniformly coded in Mα) and uses it produce an Mα-code of Mβ=⊕iXiβ (as Mβ is computable in \cmsy;(α), uniformly in β,α) and then returns an Mα-code of Xiβ. Given α<β and C⊆ω2, we then let g(α,β,C)={⟨e,f(α,β,i)⟩:⟨e,i⟩∈C}. In particular, Ug(α,β,C)Mα=UCMβ.
Suppose that stage α we have defined by induction sets Cβ for each β<α, verifying (1)(2) and (3). Let us proceed and define Cα.
Suppose first that α=β+1 is successor. Note that the set Cβ is coded by an element of Mβ+1 uniformly in β, and thus that Cβ is uniformly computable in \cmsy;(β+2) and then uniformly computable in Mβ′′. Using Lemma 2.16 we define Dβ⊇Cβ to be such that UDβMβ=⟨UCβMβ⟩ and such that Dβ is uniformly Mβ′′-computable. We define Eα to be g(α,β,Dβ), so that UEαMα=UDβMβ. Note that as Eα is uniformly computable in Mβ′′ and thus in \cmsy;(α+1), it is uniformly coded by an element of Mα+1. Note also that UEαMα is partition regular as it equals ⟨UCβMβ⟩. Using Lemma 2.17 we uniformly find an Mα+1-index of Cα⊇Eα to be such that UCαMα is an Mα-cohesive largeness class.
At limit stage α=supnβn, each set Cβn is coded by an element of Mβn+1 uniformly in βn and that Mβn+1 is uniformly computable in \cmsy;(α). It follows that ⋃nCβn is uniformly computable in \cmsy;(α). We define Dα to be ⋃ng(α,βn,Cβn). Note that Dα is uniformly computable in \cmsy;(α) and thus coded by an element of Mα uniformly in α. Note also that UDαMα=⋂n∈ωUCβnMβn=⋂n∈ω⟨UCβnMβn⟩. As an intersection of partition regular class, UDαMα is partition regular. Using Lemma 2.17 there is a set Cα⊇Dα such that UCαMα is Mα-cohesive and such that Cα is uniformly coded by an element of Mα+1.
∎
5.3 The forcing
From now on, fix sequences {Mα}α<ω1ck and {Cα}α<ω1ck which verify Proposition 5.7 and Proposition 5.8, respectively. Assume also that we have a class S⊆⋂β<ω1ckUCβMβ which is partition regular and that will be detailed later.
Let A0∪A1=ω. Note that there must be i<2 such that Ai∈S. Let then A=Ai for some i such that Ai∈S.
Definition 5.9**.**
Let Pω1ck be the set of conditions (σ,X) such that:
-
σ⊆A
2. 2.
X⊆A
3. 3.
X∩{0,…,∣σ∣}=∅.
4. 4.
X∈S
Given two conditions (σ,X),(τ,Y)∈Pω1ck we let (σ,X)≤(τ,Y) be the usual Mathias extension, that is, σ⪰τ, X⊆Y and σ−τ⊆Y.
We now define an abstract forcing question for Σα0 sets, which is merely an extension of the forcing question of the Pn forcing for Σn+10 sets : when α<ω, the definition below is merely a reformulation of Definition 3.3 with the use of effective Borel sets instead of formulas.
Definition 5.10**.**
Let σ∈2<ω. Given a Σ10 class U, let σ?⊢U hold if
[TABLE]
is a largeness class. Then inductively, given a Σm0 class B=⋃n<ωBn with 1<m<ω, we let σ?⊢B hold if
[TABLE]
is a largeness class. Then inductively, given a Σα0 class B=⋃n<ωBβn with ω≤α<ω1ck, we define σ?⊢B if
[TABLE]
is a largeness class.
For a condition p=(σ,X)∈Pω1ck and an effectively Borel set B, we write p?⊢B if σ?⊢B.
We shall now study the effectivity of the relation ?⊢. To do so we introduce the following notation.
Definition 5.11**.**
Let σ∈2<ω. Given a Σ10 class B, we write U(B,σ) for the open set:
[TABLE]
Given a Σα0 class B=⋃n<ωBβn for 1<α<ω1ck we write U(B,σ) for the open set:
[TABLE]
Proposition 3.4 settled the complexity of the relation ?⊢ by showing that it is Π10(Cm−1⊕\cmsy;(m)) for a Σm0 class. We extend here the proposition for Σα0 classes. Note that in the following one might have the false impression that we loose one jump compare to proposition 3.4. This is due to the fact that for α≥ω the Σα0-complete set is \cmsy;(α+1) and not \cmsy;(α).
Proposition 5.12
Let σ∈2<ω.
-
Let B be a Σm0 class for 0<m<ω
- (a)
The set U(B,σ) is an upward-closed Σ10(Cm−2⊕\cmsy;(m−1)) open set if m>1 and an upward-closed Σ10 open set if m=1.
2. (b)
The relation σ?⊢B is Π10(Cm−1⊕\cmsy;(m)).
2. 2.
Let B be a Σα0 class for α≥ω.
- (a)
The set U(B,σ) is an upward closed Σ10(Cα−1⊕\cmsy;(α)) open set if α is successor and an upward closed Σ10(\cmsy;(α)) open set if α is limit.
2. (b)
The relation σ?⊢B is Π10(Cα⊕\cmsy;(α+1)).
This is uniform in σ and a code for the class B.
Proof.
(1) was already proved in Proposition 3.4. We then only prove (2). This is done by induction on the effective Borel codes. Let ω≤α<ω1ck. Suppose (a) and (b) are true for any ω≤β<α. Let σ∈2<ω and let B=⋃n<ωBβn be a Σα0 class. Let
[TABLE]
Let us show (a). Suppose first α is limit. For each n∈ω, the class 2ω−Bβn is a Σβn0 class uniformly in σ∪τ and in a code for Bβn. By induction hypothesis, or by proposition 3.4 in case α=ω, the relation σ∪τ?⊬2ω−Bβn is, in any case, Σ10(\cmsy;(βn+2)) and thus Σ10(\cmsy;(α)). It follows that U(B,σ) is an upward-closed Σ10(\cmsy;(α)) open set.
Suppose now α≥ω with α=β+1. For each n we have that 2ω−Bβn is a Σβ0 class uniformly in n. By induction hypothesis, the relation σ∪τ?⊬2ω−Bβn is Σ10(Cβ⊕\cmsy;(β+1)). It follows that U(B,σ) is an upward closed Σ10(Cα−1⊕\cmsy;(α)) class.
Let us now show (b). Suppose α≥ω successor or limit. Then U(B,σ)∩UCαMα is a largeness class if for all F⊆Cα, the class U(B,σ)∩UFMα is a largeness class. It is a Π20(Mα) statement uniformly in F and then a Π10(Mα′) statement uniformly in F and then a Π10(\cmsy;(α+1)) statement uniformly in F. It follows that the statement U(B,σ)∩UCαMα is a largeness class is Π10(Cα⊕\cmsy;(α+1)).
∎
We finally extend the forcing relation of Definition 3.5 to the transfinite.
Definition 5.13**.**
Let (σ,X)∈Pω1ck. Let U be a Σ10 class. We define
[TABLE]
Then inductively for Σα0 classes B=⋃n<ωBβn, we define:
[TABLE]
Note that the relation ⊩ does not change compare to the arithmetical case : the definition goes through exactly the same way in the transfinite. It is the same for the relation ?⊢. For these reasons the following lemmas and propositions and theorems are all proved exactly the same way as for the arithmetical case, only now our set S is included in ⋂β<ω1ckUCβMβ and not just in ⋂m<ωUCmMm.
Lemma 5.14
Let p∈Pω1ck. Let B=⋂n<ωBβn be a Πα0 class. Then p⊩⋂n<ωBβn iff for every n∈ω and every q≤p, q?⊢Bβn.
Proof.
Same as Lemma 3.6.
∎
Proposition 5.15
Let p∈Pω1ck. Let B be an effectively Borel set. If p⊩B and q≤p then q⊩B.
Proof.
Same as Lemma 3.7.
∎
Proposition 5.16
Let p∈Pω1ck. Let B=⋃n<ωBβn be a Σα0 class for 0<α<ω1ck.
-
Suppose p?⊢B. Then there exists q≤p such that q⊩B.
2. 2.
Suppose p?⊬B. Then there exists q≤p such that q⊩2ω−B.
Proof.
Same as Lemma 3.8.
∎
Definition 5.17**.**
Let F⊆Pω1ck be a sufficiently generic filter. Then there is a unique set GF∈2ω such that for every (σ,X)∈F we have σ≺GF.
Theorem 5.18
Let F⊆Pω1ck be a generic enough filter. Let p∈F. Let Bα=⋃n<ωBβn be a Σα0 class for 0<α<ω1ck. Suppose p⊩Bα. Then GF∈Bα. Suppose p⊩2ω−Bα. Then GF∈2ω−Bα.
Proof.
Same as Lemma 3.10.
∎
We now have all the necessary parts to show arithmetic strong cone avoidance, and more generally α cone avoidance for a limit ordinal α.
Theorem 5.19
Let α≤ω1ck be a limit ordinal. Suppose Z is not Δ10(\cmsy;(β)) for every β<α. Let F be a sufficiently generic filter. Then for every β<α, Z is not Δ10(GF(β)).
Proof.
Let Φ be a functional and β<α. Let Bn={X :Φ(X(β),n)↓}. We want to show that Z={n :GF(β)∈Bn}. From Proposition 5.2, Bn is a Σβ+10 set for each n∈ω (Σβ0 if β≥ω and Σβ+10 if β<ω).
Let p∈Pω1ck be a condition. From Proposition 5.12, the set {n : p?⊢Bn} is Π10(\cmsy;(β+3)). As Z is not Π10(\cmsy;(β+3)), then there is some n∈Z such that p?⊬Bn or some n∈/Z such that p?⊢Bn. In the first case, there is an extension q≤p such that q⊩2ω−Bn for some n∈Z. In the second case, there is an extension q≤p such that q⊩Bn for some n∈/Z. By Theorem 5.18, in the first case Φ(GF(β),n)↑ holds for some n∈Z, and in the second case, Φ(GF(β),n)↓ holds for some n∈/Z.
If F is sufficiently generic, this is true for any β<α and any functional Φ. It follows that for any ordinal β the set Z is not Σ10(GF(β)) and thus not Δ10(GF(β)).
∎
This shows in particular cone avoidance for arithmetic degrees.
Theorem** **(Main theorem 2 (Theorem 1.3))
Let B be non arithmetical. Every set A has an infinite subset H⊆A or H⊆A such that B is not arithmetical in H.
Proof.
A direct corollary of the above theorem with α=ω.
∎
In order to show cone avoidance for hyperarithmetic degrees, one should additionally argue that if F is sufficiently generic, then ω1GF=ω1ck. The remainder of this section is devoted to the proof of this fact.
5.4 Preservation of hyperarithmetic reductions
We now prove that the infinite pigeonhole principle admits strong cone avoidance for hyperarithmetic reductions.
Definition 5.20**.**
A largeness class A is Γ-minimal, where Γ is a class of complexity, if for every Γ-open set U we have A∩U large implies A⊆U.
Proposition 5.21
The class ⋂α<ω1ckUCαMα is Δ11-minimal.
Proof.
For every α<ω1ck we have that \cmsy;(α)∈Mα and ⋂α<ω1ckUCαMα⊆⟨Mα⟩ where ⟨Mα⟩ is Mα-minimal. As \cmsy;(α)∈Mα we also have that ⟨Mα⟩ is minimal for Σ10(\cmsy;(α)) open sets. It follows that ⋂α<ω1ckUCαMα is Δ11-minimal.
∎
Proposition 5.22
There is a set C∈⋂α<ω1ckUCαMα such that C is Δ11-cohesive and ω1C=ω1ck
Proof.
Let us argue that for any upward closed partition regular class ⋂n<ωUn where each Un is open, not necessarily effectively of uniformly, there is a Δ11-cohesive C in ⋂n<ωUn. This is done by Mathias forcing with conditions (σ,X) such that X∩{0,…,∣σ∣}=∅ and such that X is Δ11 with X∈⋂n<ωUn. Given a condition (σ,X) and n we can force the generic to be in Un as follows : As X∈Un we must have that σ∪X∈Un because Un is upward closed. Thus there must be τ⊆X∩{0,…,∣σ∣} such that [σ∪τ]⊆Un. As ⋂n<ωUn contains only infinite set we must have X−{0,…,σ∪τ}∈⋂n<ωUn. Thus (σ∪τ,X−{0,…,σ∪τ}) is a valid extension. Let now Y be Δ11. We can force the generic to be included in Y or ω−Y up to finitely many elements as follow : We have X∩Y∈⋂n<ωUn or X∩(ω−Y)∈⋂n<ωUn. Then (σ,X∩Y) or (σ,X∩(ω−Y)) is a valid extension.
We have that the set ⋂α<ω1ckUCαMα is a Σ11 class which is also upward closed and partition regular. We also have that the class of Δ11-cohesive sets is a Σ11 class. By the previous argument their intersection is non-empty. By the Σ11-basis theorem it must contains C with ω1C=ω1ck.
∎
Lemma 5.23
Suppose C is Δ11-cohesive with C∈⋂α<ω1ckUCαMα. Let U be a Δ11 open set. If LC∩U is a largeness class, then ⋂α<ω1ckUCαMα⊆U
Proof.
Suppose LC∩U is a largeness class. Let us show that U∩⋂α<ω1ckUCαMα is a largeness class. Suppose first for contradiction that it is not. Then there is a Δ11 cover Y0∪⋯∪Yk−1⊇ω together with a Δ11 open largeness class V⊇⋂α<ω1ckUCαMα such that Yi∈/U∩V for every i<k. As each Yi is Δ11, there is some i<k such that C⊆∗Yi. Note also that since C∈⋂α<ω1ckUCαMα, then C∈L(V) and thus LC∩V is a largeness class. It follows that Yj∈LC∩V for some j<k. As j=i implies ∣Yj∩C∣<∞, then Yi∈LC∩V and thus Yi∈V. As LC∩U is a largeness class then by a similar argument, Yi∈LC∩U and thus Yi∈U. It follows that Yi∈U∩V, contradicting our hypothesis. Thus U∩⋂α<ω1ckUCαMα is a largeness class.
Now from Proposition 5.21 we have that ⋂α<ω1ckUCαMα is minimal for Δ11 open sets, then ⋂α<ω1ckUCαMα⊆U.
∎
Definition 5.24**.**
Let B=⋃α<ω1ckBα be a Σω1ck0 class. Let p=(σ,X)∈Pω1ck. We define p?⊢B if the set
[TABLE]
is a largeness class.
Given a Σω1ck0 class B=⋃α<ω1ckBα the following set
[TABLE]
is a Π11 open set, that is an open set ⋃σ∈B[σ] where B=⋃α<ω1ckBα is a Π11 set of strings. We also suppose that each Bα is \cmsy;(α)-computable and that {Bα}α<ω1ck is increasing. Given such sets we write Uα for the Δ11 open set ⋃σ∈Bα[σ].
Proposition 5.25
Let U be an upward-closed Π11 open set. The class U∩LC is a largeness class iff there exists some α<ω1ck such that Uα∩LC is a largeness class.
Proof.
Suppose Uα∩LC is a largeness class. Then clearly U∩LC is a largeness class. Suppose now that U∩LC is a largeness class. For each n let UnC be the Σ10(C) open set such that LC=⋂nUnC. We have
[TABLE]
Note that given k and α the predicate Pαn,k≡∀Y0∪⋯∪Yk−1 ∃i<k ∃σ⊆Yi [σ]⊆Uα∩UnC is Σ10(C⊕\cmsy;(α+1)) uniformly in n,k and α. Thus the function f:ω2→ω1ck which to n,k associates the smallest α such that Pαn,k is true is a total Π11(C) function. By Σ11-boundedness we have β=supn,kf(n,k)<ω1C=ω1ck. It follows that
[TABLE]
Also Uβ⊆U is such that Uβ∩LC is a largeness class.
∎
Corollary 5.26
Let B=⋃α<ω1ckBα be a Σω1ck0 class. Let (σ,X)∈Pω1ck. The relation p?⊢B is Σω1ck0(C)
Proof.
The relation p?⊢B is equivalent to
[TABLE]
is a largeness class
∎
Corollary 5.27
The class ⋂α<ω1ckUCαMα is minimal for Π11 open sets U such that U∩LC is a largeness class.
Proof.
Given a Π11-open set U such that U∩LC, there must be α<ω1ck such that Uα∩LC is a largeness class. By Lemma 5.23 it must be that ⋂α<ω1ckUCαMα⊆Uα.
∎
Definition 5.28**.**
Let B=⋂α<ω1ckBα be a Πω1ck0 class. Let p=(σ,X)∈Pω1ck. We define p⊩B if for every τ⊆X−{0,…,∣σ∣} and for every α<ω1ck we have σ∪τ?⊢Bα
Proposition 5.29
Let B=⋂α<ω1ckBα be a Πω1ck0 class. Let F be sufficiently generic with p∈F. If p⊩B, then GF∈B.
Proof.
Using Proposition 5.16, for every α and every q≤p, there is some r≤q such that r⊩Bα. Thus for every α the set {r : r⊩Bα} is dense below p. It follows from Theorem 5.18 that if F is sufficiently generic, GF∈B.
∎
Definition 5.30**.**
Let B=⋃n∈ωBn be a Σω1ck+10 class where each Πω1ck0 set Bn=⋂α<ω1ckBn,α. We define
p?⊢B if the set
[TABLE]
is a largeness class.
Given a Σω1ck+10 class B=⋃n∈ωBn with Bn=⋂α<ω1ckBn,α, the following set
[TABLE]
is a Σ11(C) open set, that is an open set U=⋃σ∈B[σ] where B=⋂α<ω1ckBα is a Σ11(C) set of strings. We furthermore assume that {Bα}α<ω1ck is decreasing. We then write Uα for the Δ11(C)-open set ⋃σ∈Bα[σ].
Computability theorists have a strong habits of working with enumerable open sets. With that respect, Σ11-open sets, that is, co-enumerable along the computable ordinals, are strange objects to consider. Note that given such an open set we have U⊆⋂α<ω1ckUα, but not necessarily equality. However the elements X of ⋂α<ω1ckUα−U are all such that ω1X>ω1ck. It is in particular a meager and nullset.
Let us detail a little bit the set B=⋂α<ω1ckBα that we can consider so that U=⋃σ∈B[σ]. To ease the notation we introduce the following definition, in the same spirit as U(B,σ) defined above:
Definition 5.31**.**
Let B be a Σα0 class. We define
V(B,σ) to be the set
[TABLE]
Given a Σω1ck+10 class B=⋃n∈ωBn with Bn=⋂α<ω1ckBn,α, given
[TABLE]
we have by Corollary 5.26 that U equals:
[TABLE]
Let
[TABLE]
Let
[TABLE]
By Σ11-boundedness we have that B=⋂αBα. We also have U=⋃σ∈B[σ].
We now show the core lemma that will be used to show ω1GF=ω1ck for F a sufficiently generic filter:
Lemma 5.32
Let B=⋂α<ω1ckBα be a Σ11(C) set of strings where each Bα is Δ11(C) uniformly in α and where β<α implies Bα⊆Bβ. Let U=⋃σ∈B[σ] be a Σ11(C) upward closed open set with Uα=⋃σ∈Bα[σ] be a Δ11(C) upward closed open set. We have U⊆⋂α<ω1ckUα. Furthermore, U∩LC is a largeness class iff for every α<ω1ck , Uα∩LC is a largeness class.
Proof.
It is clear that U⊆⋂α<ω1ckUα. Also it is clear that if U∩LC is a largeness class, then also ⋂α<ω1ckUα∩LC is a largeness class.
Suppose U∩LC is not a largeness class. Then there is a cover Y0∪⋯∪Yk−1⊇ω with Yi∈/U∩LC for every i<k. There must be a Σ10(C) open set V such that Yi∈/U∩V for every i≤k.
Let f:ω→ω1ck be the function which on n finds a cover σ0∪⋯∪σk⊇{0,…,n} and α such that for i<k and every τ⪯σi we have [τ]⊆V implies τ∈/Bα. As U∩V is not a largeness class, f is a total Π11(C) function. By Σ11-boundedness, β=supnf(n)<ω1C=ω1ck. By compactness, there is a cover Y0∪⋯∪Yk−1 such that for every i<k if Yi∈V then for every τ≺Yi, τ∈/Bβ and thus Yi∈/Uβ.
It follows that Uβ∩LC is not a largeness class.
∎
Corollary 5.33
LC contains a unique largeness subclass, which is minimal for both Π11 and Σ11(C)-open sets U.
Proof.
Suppose U0,U1 are two Σ11(C) open sets with Ui=⋃σ∈Bi[σ] and Ui,α=⋃σ∈Bi,α[σ]. for i<2. Suppose also U0∩LC and U1∩LC are largeness classes. By Lemma 5.32 it follows that ⋂α<ω1ckU0,α∩LC and ⋂α<ω1ckU1,α∩LC are largeness classes. By Lemma 5.23 it follows that ⋂α<ω1ckUCαMα⊆⋂α<ω1ckU0,α and ⋂α<ω1ckUCαMα⊆⋂α<ω1ckU1,α.
Thus ⋂α<ω1ckU0,α∩⋂α<ω1ckU1,α=⋂α<ω1ck(U0,α∩U1,α) is a largeness class and thus by Lemma 5.32 we have that U0∩U1 is a largeness class.
It follow that the intersection I of every Σ11(C) open set U such that U∩LC is a largeness class, is a largeness class. Furthermore as UCαMα∩LC is a largeness class for every α, the class I must be included in ⋂α<ω1ckUCαMα. Also from Corollary 5.27 the class ⋂α<ω1ckUCαMα is minimal for Π11-open sets U such that U∩LC is a largeness class. It follows that the class I∩LC is minimal for Σ11(C) and Π11 open sets.
∎
We can now detail the class S involved in the definition of Pω1ck : Let S be the unique largeness class included in LC which is minimal for Σ11(C) and Π11 open sets. Note that S must be partition regular.
Lemma 5.34
Consider a Σω1ck+10 class B=⋃n∈ωBn with Πω1ck0 set Bn=⋂α∈ω1ckBn,α. Let p=(σ,X)∈Pω1ck.
Suppose σ?⊢B. Then there is a condition q≤p together with some n such that q⊩⋂α<ω1ckBn,α
Proof.
Let
[TABLE]
The class U is a Σ11(C)-open set and U∩LC is a largeness class. As S is minimal for Σ11(C)-open sets, S⊆U. As X∈S⊆U. Then there is some τ⊆X−{0,…,∣σ∣} and some n such that
σ∪τ?⊬2ω−Bn.
Let now
[TABLE]
As σ∪τ?⊬⋃α∈ω1ck2ω−Bn,α then V∩LC is not a largeness class. Thus there is a cover Y0∪⋯∪Yk−1=ω such that Yi∈/V∩LC for every i<k. As V∩LC is upward-closed, X∩Yi∈/V∩LC for every i<k. As S⊆LC is partition regular, there is some i<k such that X∩Yi∈S⊆LC. Therefore we must have X∩Yi∈/V and thus
[TABLE]
Thus (σ∪τ,X∩Yi) is an extension of (σ,X) such that:
[TABLE]
∎
Lemma 5.35
Consider a Σω1ck+10 class B=⋃n∈ωBn with Πω1ck0 set Bn=⋂α<ω1ckBn,α. Let p=(σ,X)∈Pω1ck.
Suppose σ?⊬B. Then there is a condition q≤p together with some β<ω1ck such that q⊩⋂n∈ω⋃α<β2ω−Bn,α
Proof.
Let
[TABLE]
The class U is a Σ11(C)-open set and U∩LC is not a largeness class. Let us recall Definition 5.31 together with the notation coming after it: V(B,σ) is the set
[TABLE]
Together with
[TABLE]
with B=⋂α<ω1ckBα such that
[TABLE]
and with U=⋃σ∈B[σ].
Using Lemma 5.32, there is some α<ω1ck such that the set
[TABLE]
is such that Uα∩LC is not a largeness class. Thus there is a cover Y0∪⋯∪Yk−1⊇ω such that Yi∈/Uα∩LC for every i<k. As Uα∩LC is upward-closed, then also X∩Yi∈/Uα∩LC for every i<k. As X∈S⊆LC and as S is partition regular, there is some i<k such that X∩Yi∈S⊆LC. It follows that X∩Yi∈/Uα and thus that:
[TABLE]
Let {βm}m∈ω be such that supmβm=α. Let τ⊆Y−{0,…,∣σ∣} and n∈ω. We have for some m that V(Bn,βm,σ∪τ)∩LC is a largeness class. Then the set
[TABLE]
is a largeness class and then
[TABLE]
is a largeness class and thus that σ∪τ?⊢⋃m2ω−Bn,βm. As this is true for every n and every τ⊆Y−{0,…,∣σ∣} it follows that (σ,X∩Yi) is an extension of (σ,X) such that
[TABLE]
∎
We now show that if F⊆Pω1ck is sufficiently generic, then ω1GF=ω1ck. We use the following fact : If ω1G>ω1ck, then in particular some G-computable ordinal must code for ω1ck, that is, there must be a G-computable function Φ such that for every n, Φ(G,n) codes, relative to G, for an ordinal smaller than ω1ck and with supn∣Φ(G,n)∣=ω1ck. We show that this never happens by forcing that for every functional Φ either for some n, Φ(G,n) does not code for an ordinal smaller than ω1ck, or there is an ordinal α<ω1ck such that Φ(G,n) always codes for some ordinal smaller than α.
Given G and α let OαG be the set of G-codes for ordinals smaller than α. For α<ω1ck, the class {G : n∈OαG} is Δ11 uniformly in α and n.
Theorem 5.36
Suppose F⊆Pω1ck is sufficiently generic. Then ω1GF=ω1ck
Proof.
Let p∈Pω1ck be a condition. Given a functional Φ:2ω×ω→ω, let
[TABLE]
Suppose p?⊢B. Then from Lemma 5.34, there is an extension q≤p and some n such that
[TABLE]
It follows from Proposition 5.29 that if F is sufficiently generic for every α<ω1ck, Φ(GF,n)∈/OαGF.
Suppose now p?⊬B. Then from Lemma 5.35, there is an extension q≤p and some α<ω1ck such that
[TABLE]
It follows from Theorem 5.18 that if F is sufficiently generic, supnΦ(GF,n)≤α.
∎
We can finally deduce our final theorem
Theorem** **(Main theorem 4 (Theorem 1.5))
Let B be non hyperarithmetical. Every set A has an infinite subset H⊆A or H⊆A such that B is not hyperarithmetical in H, in particular with ω1H=ω1ck.
Proof.
By combining Theorem 5.36 together with Theorem 5.19
∎