1 Introduction
Computability theory is a useful tool to classify mathematical structures according to their intrinsic complexity. For the work on computable model theory, refer to books, e.g., Ash and Knight [Reference Ash and Knight1], Harizanov [Reference Harizanov, Ershov, Goncharov, Nerode, Remmel and Marek11, Section 5]. For the work on special algebraic structures such as abelian groups, rings and fields, see, for instance, [Reference Calvert2–Reference Calvert and Knight4, Reference Downey and Melnikov8–Reference Downey and Montalbán10, Reference Harizanov, Lempp, McCoy, Morozov and Solomon12, Reference Lempp14, Reference Melnikov15]. In [Reference Lempp14], Lempp showed that the complexity of the problem of being torsion-free for a finitely presented group is
$\Pi ^{0}_{2}$
-complete. Downey and Melnikov proved in [Reference Downey and Melnikov9] that a computable completely decomposable group is
$\Delta ^{0}_{5}$
-categorical; that is, any two computable presentations of such a group is isomorphic through a
$\Delta ^{0}_{5}$
-isomorphism. Riggs investigated the decomposability problem for torsion-free abelian groups in [Reference Riggs17]; he obtained that the decomposability problem for torsion-free abelian groups of finite rank is
$\Sigma ^{0}_{3}$
-complete, however, the same problem for general torsion-free abelian groups is
$\Sigma ^{1}_{1}$
-complete. Conidis investigated the complexity of radicals of computable rings and of computable modules in [Reference Conidis5, Reference Conidis6]; for instance, he constructed a computable noncommutative ring whose prime radical is
$\Pi ^{1}_{1}$
-complete in [Reference Conidis5]. Recently, we studied the complexity of decomposability of computable rings in [Reference Wu20] and obtained that the index set of computable decomposable rings is
$\Sigma ^{0}_{2}$
-complete within the index set of computable rings.
In [Reference Hirschfeldt, Miller and Podzorov13], Hirschfeldt, Miller and Podzorov proposed a seemingly simple notion of order-computable sets from the computable-model-theoretic point of view. However, their results reveal that there are no easy characterizations of order-computable sets from the perspective of pure computability theory. Hirschfeldt, Miller and Podzorov also analyzed the order-computability problem and left the conjecture on the complexity of order-computable sets open. In this paper, we affirmatively answer the conjecture on the complexity of order-computable sets in [Reference Hirschfeldt, Miller and Podzorov13].
Fix the standard linear order
$(\mathbb {N}, <)$
on natural numbers of order type
$\omega $
.
Definition 1 [Reference Hirschfeldt, Miller and Podzorov13].
A set A is order-computable if there is a computable structure
$(\mathbb {N}, \prec , R)$
in the language of linear orders together with a unary predicate such that
$(\mathbb {N}, \prec , R)\cong (\mathbb {N}, <, A)$
.
As proved in [Reference Hirschfeldt, Miller and Podzorov13], an order-computable set A can be computed via a special copy
$(\mathbb {N}, \prec , R)$
of
$(\mathbb {N}, <, A)$
with R the following standard sets:
-
(1)
$R=F_{k}:=\{0, 1, \ldots , k-1\}$
if A is a finite set with size
$|A|=k$
; -
(2)
$\overline {R}=F_{k}:=\{0, 1, \ldots , k-1\}$
if A is a cofinite set such that the size of the complement
$\overline {A}$
of A is
$|\overline {A}|=k$
; -
(3)
$R=E:=\{2m: m\in \mathbb {N}\}$
if A is an infinite coinfinite set.
In the above standard cases, say that
$\prec $
order-computes A. Let f be the predecessor function of the linear order
$(\mathbb {N},\prec )$
isomorphic to
$(\mathbb {N}, <)$
; that is,
$f(x)$
is the number of predecessors of x under
$\prec $
for all x. Then f is a permutation on the set of natural numbers and it can be computed via a
$\emptyset '$
oracle, i.e.,
$f\leq _{T} \emptyset '$
. Furthermore, for any n,
Then
$A\leq _{T}\emptyset '$
. This implies that order-computable sets are
$\Delta ^{0}_{2}$
.
Computable sets are order-computable, but there are order-computable sets that are not computable. In [Reference Hirschfeldt, Miller and Podzorov13], the authors proved various results on order-computable sets from the perspective of high/low hierarchy and Ershov hierarchy in pure computability theory. For instance, they proved that any low c.e. set is order-computable and that there is a low d.c.e. set that is not order-computable; they also showed that the Turing degree
$\textbf {0}'$
contains both order-computable sets and non order-computable sets.
Using the tool of computable predecessor approximation functions, Hirschfeldt, Miller, and Podzorov pointed out that the complexity of the property of being order-computable for a
$\Delta ^{0}_{2}$
set is
$\Sigma ^{0}_{4}$
, leaving the following two conjectures open.
-
– Conjecture I: The index set
$\{e\in \mathbb {N}: W_{e} \text { is order-computable}\}$
of c.e. order-computable sets is
$\Sigma ^{0}_{4}$
-complete, where
$W_{0}, W_{1}, \ldots , W_{e},\ldots $
is an effective listing of all c.e. sets. -
– Conjecture II: The index set
$\{e\in \mathbb {N}: A_{e} \text { is order-computable}\}$
of order computable sets is
$\Sigma ^{0}_{4}$
-complete, where
$A_{e}$
is a
$\Delta ^{0}_{2}$
set with index e. That is, the eth partial computable binary function
$\varphi ^{2}_{e}$
is total and it satisfies the condition
$(\forall x)[\lim _{s}\varphi ^{2}_{e}(x,s)\downarrow =0\text { or }1]$
; in this case,
$A_{e}(x)=\lim _{s}\varphi ^{2}_{e}(x,s)$
for all x.
In Section 3, we affirmatively answer the Conjectures I and II on the complexity of order-computable sets above.
The class of
$\Delta ^{0}_{2}$
sets plays an important role in pure computability theory. It is also interesting to consider the complexity of
$\Delta ^{0}_{2}$
sets themselves. We continue to prove that the index set of
$\Delta ^{0}_{2}$
sets is
$\Pi ^{0}_{3}$
-complete in Section 4.
The remaining sections are organized as follows. Section 2 provides basic notions of computability theory as well as basic properties of order-computable sets. Section 3 answers the conjectures of Hirschfeldt, Miller, and Podzorov on the complexity of c.e. order-computable sets and of general order-computable sets. Finally, Section 4 proves the result on the complexity of
$\Delta ^{0}_{2}$
sets.
2 Preliminary
For basic notions of computability theory, refer to books such as [Reference Downey and Hirschfeldt7, Reference Nies16, Reference Soare18, Reference Soare19].
A function
$f: A\rightarrow \mathbb {N}$
with domain A is partial computable if there is a Turing program that computes the value
$f(x)$
for any
$x\in A$
. Based on the effective coding of all Turing programs, partial computable functions can be effectively listed as
$\varphi _{0}, \varphi _{1}, \ldots , \varphi _{e}, \ldots $
, where
$\varphi _{e}$
is the function computed by the eth Turing program. Similarly, all partial computable binary functions are listed as
$\varphi _{0}^{2}, \varphi _{1}^{2}, \ldots , \varphi _{e}^{2}, \ldots .$
A set is computably enumerable if it is the domain of a partial computable function. All computably enumerable (often abbreviated as c.e.) sets can be effectively enumerated as
$W_{0}, W_{1},\ldots , W_{e},\ldots $
with
$W_{e}=dom(\varphi _{e})=\{x\in \mathbb {N}: \varphi _{e}(x)\downarrow \}$
. Computable functions are those partial computable functions
$\varphi _{e}$
with domain the set of all natural numbers, i.e.,
$\varphi _{e}$
is total. Computable sets are those with computable characteristic functions.
We now briefly introduce arithmetical hierarchy on sets. For
$n\geq 2$
, let
$\langle \cdot ,\cdots , \cdot \rangle : \mathbb {N}^{n}\rightarrow \mathbb {N}$
be an effective coding of n-tuples of natural numbers into natural numbers. For a set A,
-
(1) A is
$\Sigma ^{0}_{1}$
if there is a computable set B such that
$A=\{x: \exists y [\langle x,y\rangle \in B]\}$
. -
(2) A is
$\Pi ^{0}_{1}$
if there is a computable set B such that
$A=\{x: \forall y [\langle x,y\rangle \in B]\}$
. -
(3) For
$n\geq 2$
, A is
$\Sigma ^{0}_{n}$
if there is a
$\Pi ^{0}_{n-1}$
set B such that
$A=\{x: \exists y [\langle x,y\rangle \in B]\}$
.-
•
$\Sigma ^{0}_{2}$
sets are of the form
$\{x: \exists y_{1} \forall y_{2} \langle x, y_{1}, y_{2}\rangle \in B\}$
with B a computable set. -
•
$\Sigma ^{0}_{4}$
sets are of the form
$\{x: \exists y_{1} \forall y_{2}\exists y_{3} \forall y_{4} \langle x, y_{1}, y_{2}, y_{3}, y_{4}\rangle \in B\}$
with B a computable set.
-
-
(4) For
$n\geq 2$
, A is
$\Pi ^{0}_{n}$
if there is a
$\Sigma ^{0}_{n-1}$
set B such that
$A=\{x: \forall y [\langle x,y\rangle \in B]\}$
.-
•
$\Pi ^{0}_{2}$
sets are of the form
$\{x: \forall y_{1}\exists y_{2} \langle x, y_{1}, y_{2}\rangle \in B\}$
with B a computable set. -
•
$\Pi ^{0}_{3}$
sets are of the form
$\{x: \forall y_{1}\exists y_{2} \forall y_{3} \langle x, y_{1}, y_{2}, y_{3}\rangle \in B\}$
with B a computable set.
-
For two sets
$A, B\subseteq \mathbb {N}$
, A is many-one reducible (i.e., m-reducible) to B, if there is a computable function
$f:\mathbb {N}\rightarrow \mathbb {N}$
such that for all
$x\in \mathbb {N}$
,
$x\in A\Leftrightarrow f(x)\in B$
.
Definition 2. For a complexity class
$\Gamma $
(e.g.,
$\Pi ^{0}_{3}$
,
$\Sigma ^{0}_{4}$
), a
$\Gamma $
set A is m-complete
$\Gamma $
(or simply
$\Gamma $
-complete) if any
$\Gamma $
set B is m-reducible to A.
Let
$W_{0}, W_{1},\ldots , W_{e},\ldots $
be the effective listing of all c.e. sets. The index sets of subclasses of c.e. sets provide typical examples of arithmetic complete sets.
-
(1) The index set
${\mathrm {Tot}}=\{e: W_{e} =dom(\varphi _{e})=\mathbb {N}\}$
of (total) computable functions is
$\Pi ^{0}_{2}$
-complete. -
(2) The index set
$\mathrm {Cof}=\{e: W_{e} \text { is cofinite}\}$
of cofinite c.e. sets is
$\Sigma ^{0}_{3}$
-complete. -
(3) The index set of computable sets
$\{e: W_{e} \text { is computable}\}$
is
$\Sigma ^{0}_{3}$
-complete.
By definition,
$\Delta ^{0}_{2}$
sets are those that are both
$\Sigma ^{0}_{2}$
and
$\Pi ^{0}_{2}$
. By Post’s theorem, a set A is
$\Delta ^{0}_{2}$
if and only if
$A\leq _{T}\emptyset '$
; furthermore, by Shoenfield limit lemma, A is
$\Delta ^{0}_{2}$
if and only if there is a computable binary function f such that the characteristic function of A is
$A(x)=\lim _{s}f(x,s)\downarrow $
for all x. Based on the index of partial computable binary functions, we have the following index for a
$\Delta ^{0}_{2}$
set.
Definition 3. A number e is an index of a
$\Delta ^{0}_{2}$
set A if the eth partial computable binary function
$\varphi ^{2}_{e}$
is total and the characteristic function of A is
$A(x)=\lim _{s}\varphi ^{2}_{e}(x, s)\downarrow $
for all x.
For a number e, it becomes an index of some
$\Delta ^{0}_{2}$
set if and only if the following conditions on e hold:
-
(1)
$\varphi ^{2}_{e}$
is a computable function, that is, for all
$x,s$
, there is a stage t such that the computation
$\varphi ^{2}_{e,t}(x,s)$
converges at stage t; -
(2) for all x, the limit
$\lim _{s}\varphi ^{2}_{e}(x,s)$
converges to
$0$
or 1.
First, (1) is
$\Pi ^{0}_{2}$
; furthermore, similar to the fact that the index set of computable functions
${\mathrm {Tot}}=\{e\in \mathbb {N}: (\forall x)[\varphi _{e}(x)\downarrow ]\}$
is
$\Pi ^{0}_{2}$
-complete, the condition (1) is
$\Pi ^{0}_{2}$
-complete. More specifically, the index set
${\mathrm {Tot}}^{2}=\{e\in \mathbb {N}: (\forall x, y)[\varphi ^{2}_{e}(x, y)\downarrow ]\}$
of computable binary functions is
$\Pi ^{0}_{2}$
-complete. Second, the condition (2) is
$\Pi ^{0}_{4}$
because it can be described by the following
$\Pi ^{0}_{4}$
formula:
The condition (2) is indeed
$\Pi ^{0}_{4}$
-complete. We omit the detail proof here.
Proposition 1. The index set
$\{e\in \mathbb {N}: (\forall x)[\lim _{s}\varphi ^{2}_{e}(x,s)\downarrow =0\text { or }1]\} $
is
$\Pi ^{0}_{4}$
-complete.
For e to be a
$\Delta ^{0}_{2}$
index, both conditions (1) and (2) hold. Then under the condition (1) that
$\varphi ^{2}_{e}$
is total, the condition (2) becomes
$\Pi ^{0}_{3}$
because
$\varphi ^{2}_{e}(x,s)$
is always defined for all
$x,s$
. From the analysis above, we obtain the upper bound on the complexity of the index set
$\mathcal {I}$
of
$\Delta ^{0}_{2}$
sets. We further prove that
$\mathcal {I}$
is
$\Pi ^{0}_{3}$
-complete in Section 4.
Proposition 2. The index set
$\mathcal {I}=\{e\in \mathbb {N}: e \text { is an index of a }\Delta ^{0}_{2}\text { set}\} $
is
$\Pi ^{0}_{3}$
.
We next review basic properties of order-computable sets, for more details, refer to [Reference Hirschfeldt, Miller and Podzorov13]. Order-computable sets are always
$\Delta ^{0}_{2}$
and they are closely connected with predecessor functions of linear orders that order-compute them. Such linear orders are of order type
$\omega $
.
For a computable linear order of order type
$\omega $
, the predecessor function of it can be approximated via partial computable binary functions in a natural way.
Definition 4 [Reference Hirschfeldt, Miller and Podzorov13].
A partial computable binary function f is a computable predecessor approximation function if it satisfies the following properties:
-
(1) for all
$n, s$
,
$f(n, s)\downarrow $
if and only if
$n<s$
; -
(2) for all s,
$f(\cdot , s)$
is a permutation on
$\{0, 1, \ldots , s-1\}$
; -
(3) for all
$i<s$
,
$f(i, s)\leq f(i, s+1)\leq f(i, s)+1$
; -
(4) for all n,
$\lim _{s}f(n,s)$
exists.
For an order-computable set A order-computed via the linear order
$\prec $
, that is,
$(\mathbb {N}, <, A)$
is isomorphic to the computable structure
$ (\mathbb {N},\prec , R)$
with R the standard sets defined in introduction above, let
$$\begin{align*}f_{A}(n,s):=\left\{\begin{array}{ll} |\{x<s: x\prec n\}|, & \text{if}\ n<s\\ \uparrow, & \text{otherwise} \end{array}\right. \end{align*}$$
For
$n<s$
,
$f_{A}(n,s)$
is the number of predecessors of n under the restricted order
$(\mathbb {N},\prec )\upharpoonright _{s}$
on the finite set
$\{0,1,\ldots , s-1\}$
, and
$f_{A}(\cdot ,\cdot )$
is a computable predecessor approximation function such that
$$\begin{align*}A:=\left\{\begin{array}{@{}lll} \{\lim_{s}f_{A}(m,s): 0\leq m\leq k-1\}, & \text{if}\ (\exists k)[|A|=k]\\ \{\lim_{s}f_{A}(m,s): m\geq k\}, & \text{if}\ (\exists k)[|\overline{A}|=k]\\ \{\lim_{s}f_{A}(2m,s): m\geq 0\}, & \text{otherwise} \end{array}\right. \end{align*}$$
Conversely, consider the eth partial computable binary function
$\varphi _{e}^{2}(\cdot , \cdot )$
, if it is a computable predecessor approximation function under Definition 4, then for each
$s\geq 1$
,
$\varphi ^{2}_{e}(\cdot , s)$
is a permutation on
$\{0, 1, \ldots , s-1\}$
, so it determines a finite linear order
$\mathcal {L}_{s}=(\{0,1,\ldots , s-1\}, \prec _{s})$
such that
and
$\mathcal {L}=\bigcup _{s}\mathcal {L}_{s}=(\mathbb {N},\prec )$
is a computable linear order on
$\mathbb {N}$
of order type
$\omega $
such that the number of predecessors of n is just
$\lim _{s}\varphi ^{2}_{e}(n,s)$
. Then the following set
is an infinite coinfinite order-computable set, which is order-computed via the constructed order
$\prec $
. From this analysis, we see that any infinite coinfinite order-computable sets are of the form
$O_{e}$
for some e with
$\varphi ^{2}_{e}$
a computable predecessor approximation function.
The class of order-computable sets forms a subclass of
$\Delta ^{0}_{2}$
sets. To study the complexity of order-computable sets by using indices of
$\Delta ^{0}_{2}$
sets, rather than using usual m-reducibility, it is more suitable to consider the notion of m-reducibility within a given set proposed by Calvert and Knight, see [Reference Calvert3, Definitions 3.1 and 3.2], see also [Reference Calvert and Knight4, Definition 3.6].
Definition 5 [Reference Calvert3, Reference Calvert and Knight4].
Let
$A\subseteq B$
. A set S is m-reducible to A within B if there is a computable function
$f:\mathbb {N}\rightarrow B$
such that for all x,
$x\in S\Leftrightarrow f(x)\in A$
.
Similar to the usual m-reducibility, we have the following
$\Gamma $
-completeness within a given set.
Definition 6 [Reference Calvert3, Reference Calvert and Knight4].
Let
$A\subseteq B$
and
$\Gamma $
a complexity class (e.g.,
$\Pi ^{0}_{3}$
,
$\Sigma ^{0}_{4}$
). A set A is m-complete
$\Gamma $
within a set B (or simply
$\Gamma $
-complete within B) if
-
(1) A is
$\Gamma $
within B; that is, there is a
$\Gamma $
set C such that
$A= C\cap B$
; -
(2) any
$\Gamma $
set S is m-reducible to A within B.
We now consider the complexity of the index set of order-computable sets within the index set
$\mathcal {I}$
of
$\Delta ^{0}_{2}$
sets.
Proposition 3 [Reference Hirschfeldt, Miller and Podzorov13].
The index set
$\{e\in \mathcal {I}: A_{e} \text { is order-computable} \}$
of order computable sets is
$\Sigma ^{0}_{4}$
within
$\mathcal {I}$
.
Proof. Let
$e\in \mathcal {I}$
. For all x,
$A_{e}(x)=\lim _{s}\varphi _{e}^{2}(x,s)\downarrow $
.
$A_{e}$
is order-computable if and only if one of the following three conditions hold:
-
(1)
$A_{e}$
is finite; -
(2)
$A_{e}$
is cofinite; -
(3) there is an index i such that
-
(3.1)
$\varphi ^{2}_{i}$
is a computable predecessor approximation function, and -
(3.2) for any n,
$n\in A_{e}$
if and only if
$n=\lim _{s}\varphi ^{2}_{i}(2m,s)$
for some m.
-
First of all,
$\varphi _{e}^{2}$
is a computable approximation for the
$\Delta ^{0}_{2}$
set
$A_{e}$
, that is,
$\varphi _{e}^{2}$
is a total function such that for all x,
$\lim _{s}\varphi ^{2}_{e}(x,s)$
converges to 0 or 1. This can be described by the following
$\Pi ^{0}_{3}$
formula:
For (1),
$A_{e}$
is finite if and only if there is a large number N such that for all
$n>N$
,
$A_{e}(n)=\lim _{s}\varphi ^{2}_{e}(n,s)=0$
. This can be described by the
$\Sigma ^{0}_{4}$
formula:
Similarly,
$A_{e}$
is cofinite if and only if
Therefore, both (1) and (2) are
$\Sigma ^{0}_{4}$
properties on e.
Now consider the condition (3): there exists an index i satisfying (3.1) and (3.2). First, (3.1) says that
$\varphi ^{2}_{i}$
is a computable predecessor approximation function, which can be described by the following
$\Pi ^{0}_{3}$
formula:
$$ \begin{align*} &(\forall s)(\forall n<s)(\exists t)[ \varphi^{2}_{i,t}(n,s)\downarrow]\wedge\nonumber\\ &(\forall s)(\forall n\geq s)(\forall t)[ \varphi^{2}_{i,t}(n,s)\uparrow]\wedge\nonumber\\ &(\forall s)(\forall n,m<s)[ \varphi^{2}_{i}(n,s)<s \wedge (n\neq m \rightarrow \varphi^{2}_{i}(n,s)\neq \varphi^{2}_{i}(m,s))]\wedge\nonumber\\ &(\forall s)(\forall n<s)[ \varphi^{2}_{i}(n,s)\leq \varphi^{2}_{i}(n,s+1)\leq \varphi^{2}_{i}(n,s)+1]\wedge\nonumber\\ & (\forall n)(\exists s_{n}>n)(\forall s\geq s_{n})[ \varphi^{2}_{i}(n,s)=\varphi^{2}_{i}(n,s_{n})].\nonumber \end{align*} $$
Second, (3.2) says that for all n,
$A_{e}(n)=1\Leftrightarrow n=\lim _{s}\varphi ^{2}_{i}(2m,s)$
for some m. This condition can be expressed as
$$ \begin{align*} (\forall n)(\exists m)(\exists t>n+2m)(\forall s\geq t)[\varphi^{2}_{e}(n,s)&=\varphi^{2}_{e}(n,t)=1\rightarrow \varphi^{2}_{i}(2m, s)\\&=\varphi^{2}_{i}(2m,t)=n]\wedge\nonumber\\ (\forall n)(\forall m)(\exists t>n+2m)(\forall s\geq t)[\varphi^{2}_{e}(n,s)&=\varphi^{2}_{e}(n,t)=0\rightarrow \varphi^{2}_{i}(2m, s)\\&=\varphi^{2}_{i}(2m,t)\neq n].\nonumber \end{align*} $$
Therefore, the condition (3) is a
$\Sigma ^{0}_{4}$
property on e.
For
$e\in \mathcal {I}$
,
$A_{e}$
is order-computable if and only the
$\Sigma ^{0}_{4}$
properties (1)–(3) on e hold. This shows that the index set of order-computable sets is
$\Sigma ^{0}_{4}$
within
$\mathcal {I}$
.
Similar to the case of general order-computable sets, we have the same upper bound for the complexity of c.e. order-computable sets.
Proposition 4 [Reference Hirschfeldt, Miller and Podzorov13].
The index set
$\{e\in \mathbb {N}: W_{e} \text { is order-computable}\}$
of c.e. order-computable sets is
$\Sigma ^{0}_{4}$
.
3 Order-computable sets
Let
$\langle \Phi _{e}: e\in \mathbb {N}\rangle $
be an effective listing of all oracle Turing functionals. Fix the Halting set K. Then
$ \Phi ^{K}_{0}, \Phi ^{K}_{1}, \ldots , \Phi ^{K}_{e}, \ldots $
is an effective listing of all partial computable functions relative to K and
$W^{K}_{0}, W^{K}_{1}, \ldots , W^{K}_{e}, \ldots $
is an effective listing of all c.e. sets relative to K with
$W^{K}_{e}=\{x\in \mathbb {N}: \Phi ^{K}_{e}(x)\downarrow \}$
, the domain of
$ \Phi ^{K}_{e}$
. At a stage s, a number x goes into
$W^{K}_{e}[s]$
if
$\Phi ^{K}_{e}(x)[s]$
is defined with use
$\phi ^{K}_{e}(x)[s]$
; we also say that
$x\in W^{K}_{e}[s]$
with use
$\phi ^{K}_{e}(x)[s]$
. For any number x, it belongs to
$W^{K}_{e}$
if and only if there is a stage
$s_{x}$
such that at any stage
$t\geq s_{x}$
,
$x\in W^{K}_{e}[t]$
with use the same as
$\phi ^{K}_{e}(x)[s_{x}]$
. In this case, the convergent computation
$\Phi ^{K}_{e}(x)[s_{x}]\downarrow $
does not change after stage
$s_{x}$
, and thus, x stays in
$W^{K}_{e}$
forever. Let
$\mathrm {Cof}^{K}=\{e\in \mathbb {N}: W^{K}_{e}\text { is cofinite}\}$
. Then
$\mathrm {Cof}^{K}$
is
$\Sigma ^{0}_{3}$
-complete relative to the c.e. complete set K, and thus, it is
$\Sigma ^{0}_{4}$
-complete.
Theorem 1. The index set of c.e. order-computable sets is
$\Sigma ^{0}_{4}$
-complete.
Proof. An infinite coinfinite set A is order-computable if and only if there is a computable predecessor approximation function f such that for all n,
Consider the
$\Sigma ^{0}_{4}$
-complete set
$\mathrm {Cof}^{K}=\{e\in \mathbb {N}: W^{K}_{e}\text { is cofinite}\}$
. To prove the theorem, we enumerate a uniform sequence
$\langle C_{e}: e\in \mathbb {N}\rangle $
of noncomputable c.e. sets such that for all e,
For
$e\in \mathrm {Cof}^{K}$
, we build
$C_{e}$
to be low so that it is order-computable, because low c.e. sets are order-computable (see [Reference Hirschfeldt, Miller and Podzorov13, Theorem 2.6]). On the other hand, for
$e\notin \mathrm {Cof}^{K}$
, to ensure the non order-computability of
$C_{e}$
, we construct
$C_{e}$
to be not order-computed by
$\varphi ^{2}_{i}$
for any i; that is,
$C_{e}\neq O_{i}=\{\lim _{s}\varphi ^{2}_{i}(2m, s): m\in \mathbb {N}\}$
if
$\varphi ^{2}_{i}$
does become a computable predecessor approximation function.
3.1 Requirements and strategies
We enumerate a uniform sequence of c.e. sets
$\langle C_{e}: e\in \mathbb {N}\rangle $
such that the following requirements are satisfied.
-
(1)
$\mathcal {P}_{\langle e, i\rangle }$
:
$C_{e}\neq \varphi _{i}$
. -
(2)
$\mathcal {R}_{\langle e, i, i+j\rangle }$
: If
$[i,i+j+1]\subseteq W^{K}_{e}$
and
$(\exists ^{\infty } s) [\Phi ^{C_{e}}_{j}(j)[s]\downarrow ]$
, then
$\Phi ^{C_{e}}_{j}(j)\downarrow $
.If
$[i, i+j+1]\nsubseteq W^{K}_{e}$
and
$\varphi ^{2}_{i}$
is a computable predecessor approximation function, then
$C_{e}\neq O_{i}=\{\lim _{s}\varphi ^{2}_{i}(2m, s): m\in \mathbb {N}\}$
.
Here,
$\langle \varphi _{i}: i\in \mathbb {N}\rangle $
,
$\langle \varphi ^{2}_{i}: i\in \mathbb {N}\rangle $
and
$\langle \Phi _{j}: j\in \mathbb {N}\rangle $
are effective listing of partial computable functions, partial computable binary functions and oracle Turing functionals, respectively.
For each e, all
$\mathcal {P}_{\langle e, i\rangle }$
-requirements with
$i\in \mathbb {N}$
together ensure the noncomputability of
$C_{e}$
. For
$e\in \mathrm {Cof}^{K}$
,
$W^{K}_{e}$
is cofinite; that is, there is a number i such that
$[i, \infty )\subseteq W^{K}_{e}$
. In this case, for all j,
$[i, i+j+1] \subseteq W^{K}_{e}$
, and the requirement
$\mathcal {R}_{\langle e, i,j\rangle }$
ensures that the computation
$\Phi ^{C_{e}}_{j}(j)$
converges if and only if there are infinitely many stages s such that
$\Phi ^{C_{e}}_{j}(j)$
converges at stage s. This implies that
$C^{\prime }_{e}=\{j\in \mathbb {N}: \Phi ^{C_{e}}_{j}(j)\downarrow \}$
is
$\Delta ^{0}_{2}$
and thus
$C^{\prime }_{e}\leq _{T}\emptyset '$
, i.e.,
$C_{e}$
is low. As low c.e. sets are order-computable,
$C_{e}$
is order-computable. On the other hand, for
$e\notin \mathrm {Cof}^{K}$
,
$W^{K}_{e}$
is not cofinite. Then for all
$i\in \mathbb {N}$
, there exists a number
$j_{i}$
such that
$[i, i+j_{i}+1] \nsubseteq W^{K}_{e}$
, and the requirement
$\mathcal {R}_{\langle e, i, j_{i}\rangle }$
ensures that
$C_{e}$
is not order-computed by
$\varphi ^{2}_{i}$
. So
$C_{e}$
is not order-computable.
The construction of c.e. sets
$ \langle C_{e}: e\in \mathbb {N}\rangle $
proceeds on a priority tree T whose nodes are assigned
$\mathcal {P}$
- and
$\mathcal {R}$
-requirements. We view each node
$\alpha $
as a strategy for satisfying the assigned requirement whose possible outcomes are immediate successors of
$\alpha $
on T. A
$\mathcal {P}$
-strategy has two possible outcomes
$d, f$
with priority
$d<_{L}f$
on the priority tree T. While an
$\mathcal {R}$
-strategy has three possible outcomes
$\infty , d, f$
with priority
$\infty <_{L}d<_{L}f$
on T. We assign
$\mathcal {P}$
-requirements to nodes of length even and assign
$\mathcal {R}$
-requirements to nodes of length odd. So the priority tree T is simply a subtree of the full tree
$S=\{\infty , d, f\}^{<\omega }$
of finite strings on
$\{\infty , d, f\}$
, where S has the usual lexicographic order such that
$\alpha ^{\smallfrown }\infty <_{L}\alpha ^{\smallfrown }d<_{L}\alpha ^{\smallfrown }f$
for any
$\alpha \in S$
.
Definition 7. The priority tree T is defined as follows.
-
(1) Let the empty node
$\lambda \in T$
. -
(2) Let
$\alpha \in T$
with length
$|\alpha |\geq 0$
.-
• If
$|\alpha |$
is even, add
$\alpha ^{\smallfrown }d$
and
$\alpha ^{\smallfrown }f$
into T. -
• If
$|\alpha |$
is odd, add
$\alpha ^{\smallfrown }\infty $
,
$\alpha ^{\smallfrown }d$
and
$\alpha ^{\smallfrown }f$
into T.
-
At each stage s of the construction, we will define a current approximation
$\delta _{s}\in T$
of the true path
$\mathrm {TP}=\liminf _{s}\delta _{s}$
of the construction.
$\mathrm {TP}$
will be an infinite path on the priority tree T. For any node
$\alpha \in T$
, when
$\alpha \subseteq \delta _{s}$
, say that
$\alpha $
is visited at stage s, and call s an
$\alpha $
-stage.
For ease of description, we often write the
$\mathcal {P}_{\langle e, i\rangle }$
-requirement assigned to a node
$\alpha \in T$
as
$\mathcal {P}_{\langle e(\alpha ), i(\alpha )\rangle }$
(or simply
$\mathcal {P}_{\alpha }$
) with
$e(\alpha )=e$
and
$i(\alpha )=i$
. Similarly, we write the
$\mathcal {R}_{\langle e, i, j\rangle }$
-requirement assigned to a node
$\beta \in T$
as
$\mathcal {R}_{\langle e(\beta ), i(\beta ), j(\beta )\rangle }$
(or simply
$\mathcal {R}_{\beta }$
) with
$e(\beta )=e$
,
$i(\beta )=i$
and
$j(\beta )=j$
. In the following, we first give a basic
$\mathcal {P}$
- and
$\mathcal {R}$
-strategy for satisfying a single
$\mathcal {P}$
- and
$\mathcal {R}$
-requirement, respectively, and then define the assignment of the requirements to the priority tree T.
A basic
$\mathcal {P}_{\langle e, i\rangle }$
-strategy. Let
$\alpha $
be a node of length even on the priority tree T assigned the
$\mathcal {P}_{\langle e,i\rangle }$
-requirement. A basic
$\alpha $
-strategy works to diagonalize against
$C_{e}=\varphi _{i}$
at
$\alpha $
-stages.
-
(1) At the first
$\alpha $
-stage s, choose a new witness
$w_{\alpha ,s}$
and a set of fresh trigger elements
$ \{x^{k}_{\alpha ,s}: 1\leq k\leq q_{\alpha }=2^{3^{|\alpha |+1}}\}$
for higher priority
$\mathcal {R}$
-strategies
$\beta $
with
$C_{e(\beta )}=C_{e(\alpha )}$
on the priority tree T to enumerate into
$C_{e(\beta )}$
later such that
$$ \begin{align*}N_{\alpha, s}<x^{1}_{\alpha,s}< x^{2}_{\alpha,s}<\ldots <x^{q_{\alpha}}_{\alpha,s}<w_{\alpha,s},\end{align*} $$
where
$N_{\alpha , s}$
is a new number larger than all used numbers before; particularly,
$N_{\alpha ,s}$
is bigger than all restraints
$r(\beta , s)$
appointed on
$C_{e(\beta )}$
by
$\mathcal {R}$
-strategies
$\beta <\alpha $
(i.e.,
$\beta <_{L}\alpha $
or
$\beta \subset \alpha $
).The witness
$w_{\alpha , s}$
and the triggers
$x^{k}_{\alpha ,s} (1\leq k\leq q_{\alpha })$
keep unchanged at later stages unless the node
$\alpha $
is initialized by higher priority strategies. -
(2) Wait for an
$\alpha $
-stage
$t>s$
such that
$\varphi _{i,t}(w_{\alpha ,s})\downarrow =0$
. -
(3) Put
$w_{\alpha ,s}$
into
$C_{e,t}$
.
The possible outcomes of a basic
$\alpha $
-strategy are the following:
-
f : wait at Step (2) forever; in this case, either
$\varphi _{i}$
is not total or
$\varphi _{i}(w_{\alpha ,s})\downarrow =1\neq C_{e}(w_{\alpha ,s})=0$
; -
d : arrive at Step (3); in this case,
$\varphi _{i}(w_{\alpha ,s})\downarrow =0\neq C_{e}(w_{\alpha ,s})=1$
.
In both cases, the strategy ensures that
$C_{e}\neq \varphi _{i}$
. The priority of the two outcomes on the priority tree is
$d<_{L}f$
.
A basic
$\mathcal {R}_{\langle e, i, j\rangle }$
-strategy. Let
$\alpha $
be a node of length odd on the priority tree T assigned the
$\mathcal {R}_{\langle e,i,j\rangle }$
-requirement. First, define the following notion of expansionary stages to approximate the condition
$[i, i+j+1]\subseteq W^{K}_{e}$
. Since the condition
$[i, i+j+1]\subseteq W^{K}_{e}$
is
$\Sigma ^{0}_{2}$
, as in usual infinite injury constructions, we ensure that the
$\Sigma ^{0}_{2}$
condition
$[i, i+j+1]\subseteq W^{K}_{e}$
holds if and only if there are finitely many expansionary stages during the construction.
Definition 8. Let s be an
$\alpha $
-stage. If there was a last
$\alpha $
-stage
$s^{-}$
such that
$[i, i+j+1]\subseteq W^{K}_{e}[s^{-}]$
and for all
$x\in [i,i+j+1]$
,
$x\in W^{K}_{e}[s]$
with use the same as
$\phi ^{K}_{e}(x)[s^{-}]$
, then s is called a non
$\alpha $
-expansionary stage; otherwise, s is called an
$\alpha $
-expansionary stage.
Supposed that
$\alpha $
is visited infinitely often during the construction. The
$\Sigma ^{0}_{2}$
condition
$[i, i+j+1]\subseteq W^{K}_{e}$
is true if and only if there is an
$\alpha $
-stage s such that every
$\alpha $
-stage
$t\geq s$
is a non
$\alpha $
-expansionary stage. An
$\alpha $
-strategy works to satisfy its requirement
$\mathcal {R}_{\langle e, i,j\rangle }$
. At a non
$\alpha $
-expansionary stage s, it prevents numbers from enumerating into
$C_{e}$
to preserve convergent computations of the form
$\Phi ^{C_{e}}_{j}(j)[s]\downarrow $
. While at an
$\alpha $
-expansionary stage s, it devotes to diagonalize against
$\varphi ^{2}_{i}$
to be a computable predecessor approximation function for
$C_{e}$
by enumerating numbers into
$C_{e}$
.
Second, to measure the approximation of the order-computable set
$O_{i}$
computed by
$\varphi ^{2}_{i}$
, define the following length function
$l(i, s)$
of
$O_{i}$
.
-
(1) If there is a number
$x\in [1, s]$
such that the following conditions hold:-
•
$\varphi ^{2}_{i,s}(n, x)\downarrow <x$
for all
$n<x$
, and
$\varphi ^{2}_{i,s}(m, x)\uparrow $
for all
$x\leq m\leq s$
; -
•
$\varphi ^{2}_{i,s}(\cdot , x)$
is a permutation on
$\{0,1,\ldots , x-1\}$
; -
•
$\varphi ^{2}_{i,s}(n,t)\leq \varphi ^{2}_{i,s}(n,t+1)\leq \varphi ^{2}_{i,s}(n,t)+1$
for all
$n<t<x$
;
let
$l(i, s)$
be the largest such a number x, and define
$$ \begin{align*}O_{i,s}=\{\varphi^{2}_{i,s}(2m, l(i,s)): 2m<l(i,s)\}.\end{align*} $$
-
-
(2) Otherwise, such a number x does not exist, let
$l(i, s)=0$
and
$O_{i,s}=\emptyset $
.
If
$\varphi ^{2}_{i}$
does become a computable predecessor approximation function, then we have
$\lim _{s}l(i,s)=\infty $
, and the corresponding order-computable set is
In order to diagonalize against
$\varphi ^{2}_{i}$
to be a computable predecessor approximation function for
$C_{e}$
, an
$\alpha $
-strategy aims to make sure that either
$\lim _{s}l(i,s)<\infty $
, or
$\lim _{s}\varphi ^{2}_{i}(y,s)=\infty $
for some even number y, or
$\varphi ^{2}_{i}$
really becomes a computable predecessor approximation function with
$\lim _{s}l(i,s)=\infty $
but
$C_{e}(x)\neq O_{i}(x)$
for some x; that is, there is a large stage
$s_{x}$
such that for all
$t\geq s_{x}$
,
$C_{e,t}(x)\neq O_{i,t}(x)$
. This analysis motivates us to formally define the following approximation of the length of agreement between
$C_{e}$
and
$O_{i}$
. The idea behind this definition was already used in [Reference Hirschfeldt, Miller and Podzorov13, Theorem 3.11] to build a Turing degree which contains no order-computable sets.
Definition 9. Say that
$\varphi ^{2}_{i}$
appears to be a computable predecessor approximation function for
$C_{e}$
at an
$\alpha $
-stage s if
$l(i, s)>0$
,
$l(i, s)>l(i, t)$
for all
$\alpha $
-stages
$t<s$
, and
$C_{e,s}=\{\varphi ^{2}_{i,s}(2m, l(i,s)): 2m<l(i,s)\}=O_{i,s}$
.
A basic
$\alpha $
-strategy acts to satisfy its requirement
$\mathcal {R}_{\langle e(\alpha ), i(\alpha ), j(\alpha )\rangle }$
with
$e(\alpha )=e$
,
$i(\alpha )=i$
and
$j(\alpha )=j$
at
$\alpha $
-stages as follows. There are two cases:
Case 1. At a non
$\alpha $
-expansionary stage s, an
$\alpha $
-strategy proceeds to preserve the computation
$\Phi ^{C_{e}}_{j}(j)[s]$
. Let
$\phi ^{C_{e}}_{j}(j)[s]$
denote the use of the computation
$\Phi ^{C_{e}}_{j}(j)[s]$
if it converges.
-
(1) If
$\Phi ^{C_{e}}_{j}(j)[s]$
converges, appoint a restraint
$r(\alpha ,s)=\phi ^{C_{e}}_{j}(j)[s]$
on
$C_{e}$
to preserve the computation
$\Phi ^{C_{e}}_{j}(j)[s]$
. -
(2) If
$\Phi ^{C_{e}}_{j}(j)[s]$
diverges, set
$r(\alpha ,s)=0$
.
Any lower priority
$\beta $
-strategy on T can only enumerate numbers
$>r(\alpha ,s)$
into
$C_{e(\beta )}$
later.
Case 2. At
$\alpha $
-expansionary stages, a basic
$\alpha $
-strategy acts to diagonalize against
$\varphi ^{2}_{i}$
to be a computable predecessor approximation function for
$C_{e}$
.
-
(1) At the first
$\alpha $
-expansionary stage
$s_{0}$
, choose a large new witness
$w_{\alpha ,s_{0}}$
and a set of fresh trigger elements
$ \{x^{k}_{\alpha ,s_{0}}: 1\leq k\leq q_{\alpha }=2^{3^{|\alpha |+1}}\}$
for higher priority
$\mathcal {R}$
-strategies
$\beta $
with
$e(\beta )=e(\alpha )$
and
$\beta \leq \alpha $
(i.e.,
$\beta <_{L} \alpha $
or
$\beta \subseteq \alpha $
) to enumerate into
$C_{e(\beta )}$
later such that
$$ \begin{align*}N_{\alpha, s_{0}}<x^{1}_{\alpha,s_{0}}< x^{2}_{\alpha,s_{0}}<\ldots <x^{q_{\alpha}}_{\alpha,s_{0}}<w_{\alpha,s_{0}},\end{align*} $$
where
$N_{\alpha , s_{0}}$
is a new number larger than all used numbers before; particularly,
$N_{\alpha ,s_{0}}$
is bigger than all restraints
$r(\beta , s_{0})$
appointed on
$C_{e(\beta )}$
by
$\mathcal {R}$
-strategies
$\beta $
with
$\beta <\alpha $
.-
• Enumerate
$w_{\alpha ,s_{0}}$
into
$C_{e(\alpha ),s_{0}}$
.
The witness
$w_{\alpha , s_{0}}$
and the triggers
$x^{k}_{\alpha ,s_{0}} (1\leq k\leq q_{\alpha })$
keep unchanged at later stages unless the node
$\alpha $
is initialized by higher priority strategies. -
-
(2) Wait for an
$\alpha $
-expansionary stage
$t_{0}>s_{0}$
such that the length approximation of the order-computable set
$l(i(\alpha ), t_{0})>w_{\alpha ,s_{0}}$
, and
$\varphi ^{2}_{i(\alpha )}$
appears to be a computable predecessor approximation function for
$C_{e(\alpha )}$
at stage
$t_{0}$
. -
(3) Let
$y_{\alpha , t_{0}}$
be the unique even number such that
$\varphi ^{2}_{i(\alpha )}(y_{\alpha , t_{0}}, l(i(\alpha ), t_{0}))=w_{\alpha ,s_{0}}\in C_{e(\alpha ),s_{0}}$
.-
• Pick the largest trigger element
$x^{k}_{\alpha ,s_{0}}<w_{\alpha , s_{0}}$
that has not been enumerated into
$C_{e(\beta )}$
by
$\beta $
-strategies with
$\beta <\alpha $
. -
• Enumerate
$x^{k}_{\alpha ,s_{0}}$
into
$C_{e(\alpha ),t_{0}}$
. -
• Go to Step (4.n) with
$n=1$
.
The even number
$y_{\alpha , t_{0}}$
remains the same at later stages as long as
$\alpha $
is not initialized. -
-
(4.n) Wait for an
$\alpha $
-expansionary stage
$t_{n}>t_{n-1}$
such that
$\varphi ^{2}_{i(\alpha )}$
appears to be a computable predecessor approximation function for
$C_{e(\alpha )}$
at stage
$t_{n}$
. -
(5.n) Let
$u_{\alpha , t_{0}}=w_{\alpha , s_{0}}$
and
$u_{\alpha , t_{n}}=\varphi ^{2}_{i(\alpha )}(y_{\alpha , t_{0}}, l(i(\alpha ), t_{n}))$
. Then we have because the enumeration of the trigger element
$$ \begin{align*} w_{\alpha,s_{0}} \leq u_{\alpha, t_{n-1}}&=\varphi^{2}_{i(\alpha)}(y_{\alpha, t_{0}}, l(i(\alpha), t_{n-1}))\nonumber\\ &<\varphi^{2}_{i(\alpha)}(y_{\alpha, t_{0}}, l(i(\alpha), t_{n}))=u_{\alpha, t_{n}}\in O_{i(\alpha), t_{n}}= C_{e(\alpha), t_{n}}\nonumber \end{align*} $$
$x^{k}_{\alpha , s_{0}}< w_{\alpha , s_{0}}$
in Step (3) for
$n=1$
or
$x^{k}_{\beta , t}\in (w_{\alpha ,s_{0}}, u_{\alpha , t_{n-1}})$
in Step (5.
$(n-1)$
) for
$n\geq 2$
forces the number of predecessors of
$y_{\alpha , t_{0}}$
computed by
$\varphi ^{2}_{i(\alpha )}$
to move up.
As
$u_{\alpha , t_{n}}\in C_{e(\alpha ), t_{n}}$
and
$u_{\alpha , t_{n}}> w_{\alpha , s_{0}}$
, there is a unique node
$\beta>\alpha $
on the priority tree T such that where
$$ \begin{align*}u_{\alpha, t_{n}}=w_{\beta, t} \text{ or }u_{\alpha, t_{n}}=x^{k}_{\beta, t} \text{ for some }k,\end{align*} $$
$w_{\beta ,t}$
and
$x^{k}_{\beta ,t}(1\leq k\leq q_{\beta }=2^{3^{|\beta |+1}})$
were first appointed on
$\beta $
at some
$\beta $
-stage
$t\in (t_{0}, t_{n})$
.
-
• Pick the largest trigger number
$x^{k}_{\beta ,t}<u_{\alpha ,t_{n}}\leq w_{\beta ,t}$
that has not been enumerated into
$C_{e(\beta ')}$
for any
$\beta '\leq \beta $
. -
• Enumerate
$x^{k}_{\beta ,t}$
into
$C_{e(\alpha ),t_{n}}$
. -
• Go to Step (4.(
$n+1$
)).
For each node
$\beta \in T$
, since the number of nodes
$\beta '\in T$
with
$\beta '<_{L}\beta $
or
$\beta ' \subseteq \beta $
is strictly less than
$3^{|\beta |+1}$
, we appoint enough (i.e.,
$2^{3^{|\beta |+1}}$
many) trigger elements
$x^{k}_{\beta ,t}$
on node
$\beta $
for higher priority
$\beta '$
-strategies working for
$\mathcal {R}$
-requirements to enumerate into
$C_{e(\beta ')}$
during the construction. That is, the trigger elements in Step (3) or Step (5.n) always exist if needed (see Lemma 1 below). -
The possible outcomes of a basic
$\alpha $
-strategy is listed as follows:
-
f: finitely many
$\alpha $
-expansionary stages; -
d: wait at Step (2) or Step (4.n) for some
$n\geq 1$
forever at
$\alpha $
-expansionary stages; -
∞: go to Step (4.
$(n+1)$
) from Step (5.n) infinitely often at
$\alpha $
-expansionary stages.
The priority of the outcomes on the priority tree T is
$\infty <_{L} d<_{L}f$
.
If there are finitely many
$\alpha $
-expansionary stages,
$\alpha $
has the finite outcome f, and the computation
$\Phi ^{C_{e(\alpha )}}_{j(\alpha )}(j(\alpha ))$
will be preserved after certain stage if it converges at infinitely many
$\alpha $
-stages. If there are infinitely many
$\alpha $
-expansionary stages,
$\alpha $
has two possible outcomes
$\infty <_{L}d$
.
-
(i) If
$\alpha $
has the outcome d, then either
$\lim _{s}l(i(\alpha ),s)<\infty $
or
$C_{e(\alpha )}\neq O_{i(\alpha )}$
in which case
$\alpha $
only enumerates finitely many triggers into
$C_{e(\alpha )}$
. -
(ii) If
$\alpha $
has the outcome
$\infty $
, then
$\lim _{s}\varphi ^{2}_{i(\alpha )}(y_{\alpha , t_{0}}, s)=\lim _{n}u_{\alpha ,t_{n}}=\infty $
in which case
$\alpha $
enumerates infinitely many triggers into
$C_{e(\alpha )}$
.
In both cases,
$\varphi ^{2}_{i(\alpha )}$
cannot be a computable predecessor approximation function for
$C_{e(\alpha )}$
. In other words,
$C_{e(\alpha )}$
is not order-computed via
$\varphi ^{2}_{i(\alpha )}$
.
This ends the description of basic strategies.
Fix a bijection
$\langle \cdot , \cdot \rangle : \mathbb {N}^{2}\rightarrow \mathbb {N}$
such that
$\langle e, i\rangle <\langle e, i'\rangle $
for all
$e,i,i'$
with
$i<i'$
. For
$e,i,j\in \mathbb {N}$
, let
$\langle e, i, j\rangle =\langle \langle e,i\rangle ,j\rangle $
. Then we can fix a linear order
$\prec $
on all
$\mathcal {P}_{\langle e, i\rangle }$
- and
$\mathcal {R}_{\langle e, i, j\rangle }$
-requirements (
$e,i,j\in \mathbb {N}$
) of order type
$\omega $
as follows.
-
(1) For all
$e,i, e', i'$
, let
$\mathcal {P}_{\langle e, i\rangle }\prec \mathcal {P}_{\langle e', i'\rangle }$
if and only if
$\langle e, i\rangle < \langle e', i'\rangle $
, and let the priority of all
$\mathcal {P}$
-requirements be listed as
$$ \begin{align*}\mathcal{P}_{\langle e_{0},i_{0}\rangle} \prec \mathcal{P}_{\langle e_{1}, i_{1}\rangle}\prec\ldots\prec \mathcal{P}_{\langle e_{n}, i_{n}\rangle}\prec\ldots.\end{align*} $$
Particularly, for any number e, we have
$$ \begin{align*}\mathcal{P}_{\langle e,0\rangle} \prec \mathcal{P}_{\langle e, 1\rangle}\prec\ldots\prec \mathcal{P}_{\langle e, i\rangle}\prec\ldots.\end{align*} $$
-
(2) For all
$e,i,j, e', i',j'$
, let
$\mathcal {R}_{\langle e, i,j\rangle }\prec \mathcal {R}_{\langle e', i', j'\rangle }$
if and only if
$\langle e, i,j\rangle < \langle e', i', j'\rangle $
, and let the priority of all
$\mathcal {R}$
-requirements be listed as
$$ \begin{align*}\mathcal{R}_{\langle e^{\prime}_{0},i^{\prime}_{0},j^{\prime}_{0}\rangle} \prec \mathcal{R}_{\langle e^{\prime}_{1}, i^{\prime}_{1}, j^{\prime}_{1}\rangle}\prec\ldots\prec \mathcal{R}_{\langle e^{\prime}_{n}, i^{\prime}_{n}, j^{\prime}_{n}\rangle}\prec\ldots.\end{align*} $$
Particularly, for fixed numbers
$e,i$
, we have
$$ \begin{align*}\mathcal{R}_{\langle e,i,0\rangle} \prec \mathcal{R}_{\langle e, i, 1\rangle}\prec\ldots\prec \mathcal{R}_{\langle e, i, j\rangle}\prec\ldots.\end{align*} $$
-
(3) Define the priority of all
$\mathcal {P}$
- and
$\mathcal {R}$
- requirements as
$$ \begin{align*}\mathcal{P}_{\langle e_{0},i_{0}\rangle}\prec \mathcal{R}_{\langle e^{\prime}_{0},i^{\prime}_{0},j^{\prime}_{0}\rangle} \prec \mathcal{P}_{\langle e_{1},i_{1}\rangle} \prec \mathcal{R}_{\langle e^{\prime}_{1}, i^{\prime}_{1}, j^{\prime}_{1}\rangle}\prec\ldots\prec \mathcal{P}_{\langle e_{n},i_{n}\rangle}\prec \mathcal{R}_{\langle e^{\prime}_{n}, i^{\prime}_{n}, j^{\prime}_{n}\rangle}\prec\ldots.\end{align*} $$
The tree of strategies. The priority tree T of the construction is a subtree of
$S=\{\infty , d, f\}^{<\omega }$
such that any node
$\alpha \in T$
of length even has two immediate extensions
$\alpha ^{\smallfrown } d$
and
$\alpha ^{\smallfrown }f$
on T and any node
$\alpha \in T$
of length odd has three immediate extensions
$\alpha ^{\smallfrown }\infty $
,
$\alpha ^{\smallfrown } d$
and
$\alpha ^{\smallfrown }f$
on T. Say that a node
$\alpha \in T$
is a
$\mathcal {P}_{\langle e, i\rangle }$
- or an
$\mathcal {R}_{\langle e, i, j\rangle }$
-strategy if it is assigned the corresponding requirement. As before, we write the
$\mathcal {P}_{\langle e, i\rangle }$
-requirement assigned to a node
$\alpha $
of T with length even as
$\mathcal {P}_{\langle e(\alpha ), i(\alpha )\rangle }$
(or simply
$\mathcal {P}_{\alpha }$
). Similarly, we write the
$\mathcal {R}_{\langle e, i, j\rangle }$
-requirement assigned to a node
$\beta $
of T with length odd as
$\mathcal {R}_{\langle e(\beta ), i(\beta ), j(\beta )\rangle }$
(or simply
$\mathcal {R}_{\beta }$
).
According to the priority of
$\mathcal {P}$
-,
$\mathcal {R}$
-requirements above, assign the requirements to nodes of the priority tree T by induction on their length as follows.
-
(1) For the empty node
$\lambda \in T$
, assign the highest priority
$\mathcal {P}$
-requirement
$\mathcal {P}_{\langle e_{0}, i_{0}\rangle }$
to node
$\lambda $
. -
(2) For nodes
$d,f\in T$
, assign the highest priority
$\mathcal {R}$
-requirement
$\mathcal {R}_{\langle e^{\prime }_{0}, i^{\prime }_{0}, j^{\prime }_{0}\rangle }$
to
$d, f$
. -
(3) Assume that
$\alpha ={\alpha ^{-}}^{\smallfrown }o\in T$
with length
$|\alpha |\geq 1$
. There are two cases depending on the parity of
$|\alpha |$
.-
• If
$|\alpha |$
is odd, then
$\alpha ^{\smallfrown }\infty $
,
$\alpha ^{\smallfrown }d$
and
$\alpha ^{\smallfrown }f\in T$
. Suppose that the immediate predecessor
$\alpha ^{-}$
of
$\alpha $
is assigned the
$\mathcal {P}_{\langle e_{n}, i_{n}\rangle }$
-requirement with
$n\geq 0$
.-
– For
$o\in \{\infty , d, f\}$
, assign
$\mathcal {P}_{\langle e_{n+1}, i_{n+1}\rangle }$
to node
$\alpha ^{\smallfrown }o$
.
-
-
• If
$|\alpha |$
is even, then
$\alpha ^{\smallfrown }d$
and
$\alpha ^{\smallfrown }f\in T$
. Suppose that the immediate predecessor
$\alpha ^{-}$
of
$\alpha $
is assigned the
$\mathcal {R}_{\langle e^{\prime }_{n}, i^{\prime }_{n}, j^{\prime }_{n}\rangle }$
-requirement with
$n\geq 0$
.-
* For
$o\in \{d,f\}$
, find the least
$m>n$
such that
$\langle e^{\prime }_{m}, i^{\prime }_{m}\rangle \neq \langle e(\beta ), i(\beta )\rangle $
for all nodes
$\beta $
of length odd assigned the
$\mathcal {R}_{\langle e(\beta ), i(\beta ), j(\beta )\rangle }$
-requirement with
$\beta ^{\smallfrown }d\subseteq \alpha $
or
$\beta ^{\smallfrown }\infty \subseteq \alpha $
, and assign
$\mathcal {R}_{\langle e^{\prime }_{m}, i^{\prime }_{m}, j^{\prime }_{m}\rangle }$
to node
$\alpha ^{\smallfrown }o$
.
-
Note that a node
$\beta ^{\smallfrown }o\in T$
with
$|\beta |$
odd and
$o\in \{d, \infty \}$
represents that the
$\beta $
-strategy has an infinite outcome o. In this case,
$[i(\beta ), i(\beta )+j(\beta )+1]\nsubseteq W^{K}_{e(\beta )}$
and the
$\beta $
-strategy works to diagonalize against
$\varphi ^{2}_{i(\beta )}$
to be a computable predecessor approximation function for
$C_{e(\beta )}$
. So we do not need to assign
$\mathcal {R}_{\langle e(\beta ), i(\beta ), \cdot \rangle }$
-requirements to nodes of T below
$\beta ^{\smallfrown }o$
. -
We now describe possible conflictions between multiple
$\mathcal {R}$
-strategies on the priority tree T. Let
$\alpha $
be an
$\mathcal {R}_{\langle e, i, j\rangle }$
-strategy on T. Suppose that
$[i, i+j+1]\nsubseteq W^{K}_{e}$
. For all
$j'>j$
, as
$[i, i+j+1]\subseteq [i, i+j'+1]$
, we have
$ [i, i+j'+1]\nsubseteq W^{K}_{e}$
. So we do not need to assign
$\mathcal {R}_{\langle e, i,j'\rangle }$
requirements with
$j'>j$
to nodes below the infinite outcomes of
$\alpha $
(i.e., below
$\alpha ^{\smallfrown } d$
or
$\alpha ^{\smallfrown }\infty $
) on the priority tree. However, for
$i'\neq i$
,
$\mathcal {R}_{\langle e,i',\cdot \rangle }$
-requirements are still assigned to nodes below the infinite outcomes of
$\alpha $
. Let
$\alpha '\supset \alpha $
be an
$\mathcal {R}_{\langle e, i', j'\rangle }$
-strategy on T.
-
(i) If
$\alpha ^{\smallfrown }d\subset \alpha '$
, then there are no conflictions because
$\alpha $
only enumerates finitely many triggers of nodes with lower priority into
$C_{e}$
. -
(ii) If
$\alpha ^{\smallfrown } \infty \subset \alpha '$
, then
$\alpha $
acts infinitely often to enumerate triggers of nodes
$\beta \in T$
with
$\beta> \alpha $
into
$C_{e}$
to force
$\lim _{s}\varphi ^{2}_{i}(y,s)=\infty $
for some even number y; this may injure a convergent computation
$\Phi ^{C_{e}}_{j'}(j')[s]\downarrow $
, which
$\alpha '$
needs to preserve, infinitely often. Since the triggers enumerated by
$\alpha $
during the construction tend to infinity, to deal with this problem, we only preserve believable computations
$\Phi ^{C_{e}}_{j'}(j')[s]\downarrow $
where
$\alpha $
will not enumerate triggers
$<\phi ^{C_{e}}_{j'}(j')[s]$
, the use of the computation, after stage s.
Definition 10. Let
$\alpha '\in T$
be an
$\mathcal {R}_{\langle e, i', j'\rangle }$
-strategy. A convergent computation
$\Phi ^{C_{e}}_{j'}(j')[s]\downarrow $
is believable at a non
$\alpha '$
-expansionary stage s if for any
$\mathcal {R}$
-strategy
$\alpha \in T$
with
$e(\alpha )=e$
and
$\alpha ^{\smallfrown }\infty \subset \alpha '$
, the
$\alpha $
-strategy acts as in Step (5.n) for some
$n\geq 1$
to enumerate a trigger
$x^{k}_{\beta ,t}$
of some node
$\beta>\alpha $
into
$C_{e}$
at stage s, then the use of the convergent computation
$\phi ^{C_{e}}_{j'}(j')[s]$
is strictly less than
$x^{1}_{\beta ,t}$
, where
$x^{1}_{\beta ,t}<\ldots <x^{q_{\beta }}_{\beta ,t}$
with
$q_{\beta }=2^{3^{|\beta |+1}}$
are all triggers of the node
$\beta $
first defined at some
$\beta $
-stage
$t<s$
.
3.2 Construction and verification
We are ready to provide a formal construction of the c.e. sets
$C_{e}(e\in \mathbb {N})$
by stages according to the tree of strategies.
Construction.
Stage 0. Let
$\delta _{0}=\lambda $
, the empty node on T. Initialize all nodes on T. For all e, let
$C_{e,0}=\emptyset $
. For all nodes
$\alpha \in T$
with length
$|\alpha |$
odd, set the
$C_{e(\alpha )}$
-restraint
$r(\alpha ,0)=0$
.
Stage
$s\geq 1$
. Define the current true path
$\delta _{s}\in T$
with length
$|\delta _{s}|\leq s$
at substages m with
$0\leq m\leq s-1$
, starting at substage 0. Let
$\alpha _{0}=\lambda $
, the empty node on T, and assume that we have defined
$\alpha _{m}=\delta _{s}(0)\ldots \delta _{s}(m-1)$
by the end of substage
$m-1$
for
$1\leq m\leq s$
.
Substage
$m(0\leq m\leq s-1)$
. Define the current true outcome
$\delta _{s}(m)$
of
$\alpha _{m}$
and enumerate numbers into
$C_{e(\alpha _{m}),s}$
according to the basic
$\alpha _{m}$
-strategy with additional initializations to strategies with lower priority on the priority tree T.
-
– If a node
$\alpha \in T$
is initialized at stage s, then the witness
$w_{\alpha ,s}$
and triggers
$x^{k}_{\alpha ,s}(1\leq k\leq q_{\alpha }=2^{3^{|\alpha |+1}})$
are undefined. -
– If
$m=s-1$
, let
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{s-1}}^{\smallfrown }\delta _{s}(s-1)=\delta _{s}(0)\ldots \delta _{s}(s-1)$
. Initialize all nodes
$\alpha \geq \delta _{s}$
, also initialize all nodes of length
$\geq s+1$
. End current stage s and go to next stage.
Substage m proceeds as follows. There are two cases depending on the parity of m.
Case I. If m is even, then
$\alpha _{m}$
is a
$\mathcal {P}$
-strategy. Check whether there was a last
$\alpha _{m}$
-stage
$s^{-}$
such that
$\alpha _{m}$
has not been initialized since then.
-
(1) If such a last
$\alpha _{m}$
-stage
$s^{-}$
did not exist, then s is the first
$\alpha _{m}$
-stage after last initialization. Act as in the basic
$\alpha _{m}$
-strategy.-
• Choose a large new witness
$w_{\alpha _{m},s}$
and a set of fresh trigger elements
$ \{x^{k}_{\alpha _{m},s}: 1\leq k\leq q_{\alpha _{m}}=2^{3^{|\alpha _{m}|+1}}\}$
for
$\beta $
-strategies with
$|\beta |$
odd and
$\beta \leq \alpha _{m}$
(i.e.,
$\beta <_{L} \alpha _{m}$
or
$\beta \subseteq \alpha _{m}$
) on the priority tree T to enumerate into
$C_{e(\beta )}$
later such that
$$ \begin{align*}N_{\alpha_{m}, s}<x^{1}_{\alpha_{m},s}< x^{2}_{\alpha_{m},s}<\ldots <x^{q_{\alpha_{m}}}_{\alpha_{m},s}<w_{\alpha_{m},s},\end{align*} $$
where
$N_{\alpha _{m}, s}$
is a new number larger than all used numbers before; particularly,
$N_{\alpha _{m},s}$
is bigger than all restraints
$r(\beta , s)$
appointed on
$C_{e(\beta )}$
by higher priority
$\beta $
-strategies. -
• Go to Step (2); that is, wait for
$\varphi _{i(\alpha _{m})}(w_{\alpha _{m},s})\downarrow =0$
. -
• Let
$\delta _{s}(m)=f$
. Define
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }f$
. Initialize all nodes
$\alpha \geq {\alpha _{m}}^{\smallfrown }f$
, also initialize all nodes of length
$\geq s+1$
. -
• End Stage s and go to next stage.
The witness
$w_{\alpha _{m}, s}$
and the triggers
$x^{k}_{\alpha _{m},s} (1\leq k\leq q_{\alpha _{m}})$
keep unchanged at later stages unless the node
$\alpha _{m}$
is initialized by higher priority strategies. -
-
(2) If such a last
$\alpha _{m}$
-stage
$s^{-}$
did exist, then there was a largest
$\alpha _{m}$
-stage
$s_{0}\leq s^{-}<s$
such that the witness
$w_{\alpha _{m}, s_{0}}$
and trigger elements
$x^{k}_{\alpha _{m}, s_{0}}$
with
$1\leq k\leq q_{\alpha _{m}}=2^{3^{|\alpha _{m}|+1}}$
were defined at stage
$s_{0}$
and
$\alpha _{m}$
has not been initialized since then. Define the current outcome
$\delta _{s}(m)$
of the
$\alpha _{m}$
-strategy started at stage
$s_{0}$
according to the current state of the strategy.-
• If the
$\alpha _{m}$
-strategy waits at Step (2), let
$\delta _{s}(m)=f$
.-
* Initialize all nodes
$\alpha>_{L}{\alpha _{m}}^{\smallfrown }f$
. Go to substage
$m+1$
of current stage s if
$m+1<s$
.
-
-
• If the
$\alpha _{m}$
-strategy currently arrives at Step (2), act as in Step (3).-
* Enumerate
$w_{\alpha _{m},s_{0}}$
into
$C_{e(\alpha _{m}),s}$
. -
* Let
$\delta _{s}(m)=d$
. Define
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }d$
. Initialize all nodes
$\alpha \geq {\alpha _{m}}^{\smallfrown }d$
and all nodes of length
$\geq s+1$
. -
* End Stage s and go to next stage.
-
-
• Otherwise, the
$\alpha _{m}$
-strategy was already arrived at Step (2) at last
$\alpha _{m}$
-stage
$s^{-}$
, let
$\delta _{s}(m)=d$
.-
* Initialize all nodes
$\alpha>_{L}{\alpha _{m}}^{\smallfrown }d$
. Go to substage
$m+1$
of current stage s if
$m+1<s$
.
-
-
Case II. If m is odd, then
$\alpha _{m}$
is an
$\mathcal {R}$
-strategy. Act as follows.
Case 1. If s is a non
$\alpha _{m}$
-expansionary stage, let
$\delta _{s}(m)=f$
. Act as in the basic
$\alpha _{m}$
-strategy.
-
(1) If the computation
$\Phi ^{C_{e(\alpha _{m})}}_{j(\alpha _{m})}(j(\alpha _{m}))[s]$
newly converges and it is a believable computation at stage s, let
$\phi ^{C_{e(\alpha _{m})}}_{j(\alpha _{m})}(j(\alpha _{m}))[s]$
be the use of the computation.-
• Appoint a new
$C_{e(\alpha _{m})}$
-restraint
$r(\alpha _{m},s)=\phi ^{C_{e(\alpha _{m})}}_{j(\alpha _{m})}(j(\alpha _{m}))[s]$
. -
• Define
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }f$
. Initialize all nodes
$\alpha \geq \delta _{s}$
(i.e.,
$\alpha>_{L}\delta _{s}$
or
$\alpha \supseteq \delta _{s}$
). Also initialize all nodes of length
$\geq s+1$
. -
• End Stage s and go to next stage.
-
-
(2) Otherwise, there are two possible subcases:
-
(i) if
$\Phi ^{C_{e(\alpha _{m})}}_{j(\alpha _{m})}(j(\alpha _{m}))[s]$
diverges or it converges but not believable at current stage, let the
$C_{e(\alpha _{m})}$
-restraint
$r(\alpha _{m},s)=0$
. -
(ii) otherwise, it is a believable computation already convergent at last non
$\alpha _{m}$
-expansionary stage
$s^{-}$
, let the
$C_{e(\alpha _{m})}$
-restraint
$r(\alpha _{m},s)= r(\alpha _{m},s^{-})$
.
In both subcases, initialize all nodes
$\alpha>_{L}{\alpha _{m}}^{\smallfrown }f$
. Go to substage
$m+1$
of current stage s if
$m+1<s$
. -
Case 2. If s is an
$\alpha _{m}$
-expansionary stage, check whether there was a last
$\alpha _{m}$
-expansionary stage
$s^{-}$
such that
$\alpha _{m}$
has not been initialized since then.
-
(1) If such a last
$\alpha _{m}$
-expansionary stage
$s^{-}$
did not exist, then s is the first
$\alpha _{m}$
-expansionary stage after last initialization. Act as in the basic
$\alpha _{m}$
-strategy.-
• Choose a large new witness
$w_{\alpha _{m},s}$
and a set of fresh trigger elements
$ \{x^{k}_{\alpha _{m},s}: 1\leq k\leq q_{\alpha _{m}}=2^{3^{|\alpha _{m}|+1}}\}$
for higher priority
$\beta $
-strategies of length odd with
$\beta \leq \alpha _{m}$
(i.e.,
$\beta <_{L} \alpha _{m}$
or
$\beta \subseteq \alpha _{m}$
) on the priority tree T to enumerate into
$C_{e(\beta )}$
later such that
$$ \begin{align*}N_{\alpha_{m}, s}<x^{1}_{\alpha_{m},s}< x^{2}_{\alpha_{m},s}<\ldots <x^{q_{\alpha_{m}}}_{\alpha_{m},s}<w_{\alpha_{m},s},\end{align*} $$
where
$N_{\alpha _{m}, s}$
is a new number larger than all used numbers before; particularly,
$N_{\alpha _{m},s}$
is bigger than all restraints
$r(\beta , s)$
appointed on
$C_{e(\beta )}$
by
$\mathcal {R}$
-strategies
$\beta $
with priority strictly higher than
$\alpha _{m}$
. -
• Enumerate the witness
$w_{\alpha _{m},s}$
into
$C_{e(\alpha _{m}),s}$
. -
• Define
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }d$
. Initialize all nodes
$\alpha \geq {\alpha _{m}}^{\smallfrown }d$
and all nodes of length
$\geq s+1$
. -
• End Stage s and go to next stage.
The witness
$w_{\alpha _{m}, s}$
and the triggers
$x^{k}_{\alpha _{m},s} (1\leq k\leq q_{\alpha _{m}})$
keep unchanged at later stages unless the node
$\alpha _{m}$
is initialized by higher priority strategies. -
-
(2) If such a last
$\alpha _{m}$
-expansionary stage
$s^{-}$
did exist, then there was a largest
$\alpha _{m}$
-expansionary stage
$s_{0}\leq s^{-}<s$
such that the witness
$w_{\alpha _{m}, s_{0}}$
and trigger elements
$x^{k}_{\alpha _{m}, s_{0}}$
with
$1\leq k\leq q_{\alpha _{m}}=2^{3^{|\alpha _{m}|+1}}$
were defined at stage
$s_{0}$
and
$\alpha _{m}$
has not been initialized since then. Define the current outcome
$\delta _{s}(m)$
of the
$\alpha _{m}$
-strategy started at stage
$s_{0}$
according to the current state of the strategy.-
• If the
$\alpha _{m}$
-strategy waits at Step (2) or at Step (4.n) for some
$n\geq 1$
, let
$\delta _{s}(m)=d$
.-
* Initialize all nodes
$\alpha>_{L}{\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }d$
. Go to substage
$m+1$
of current stage s if
$m+1<s$
.
-
-
• If the
$\alpha _{m}$
-strategy currently arrives at Step (2), let
$\delta _{s}(m)=d$
. Act as in Step (3).-
* Let
$t_{0}=s$
and
$u_{\alpha _{m}, t_{0}}=w_{\alpha _{m}, s}=w_{\alpha _{m}, s_{0}}$
. Let
$y_{\alpha _{m}, s}$
be the unique even number such that The even number
$$ \begin{align*}\varphi^{2}_{i(\alpha_{m})}(y_{\alpha_{m}, s}, l(i(\alpha_{m}), s))=w_{\alpha_{m},s}=w_{\alpha_{m},s_{0}}\in O_{i(\alpha_{m}),s}= C_{e(\alpha_{m}),s}.\end{align*} $$
$y_{\alpha _{m}, s}$
remains the same at later stages as long as
$\alpha _{m}$
is not initialized.
-
* Pick the largest trigger element
$x^{k}_{\alpha _{m},s}=x^{k}_{\alpha _{m},s_{0}}<w_{\alpha _{m}, s_{0}}$
that has not been enumerated into
$C_{e(\beta )}$
by
$\beta $
-strategies with
$\beta <\alpha _{m}$
(i.e.,
$\beta <_{L}\alpha _{m}$
or
$\beta \subset \alpha _{m}$
). -
* Enumerate
$x^{k}_{\alpha _{m},s}$
into
$C_{e(\alpha _{m}),s}$
. Go to Step (4.1).By Lemma 1 below, such a trigger
$x^{k}_{\alpha _{m},s_{0}}$
always exists. -
* Define
$\delta _{s}={\alpha _{m}}^{\smallfrown }\delta _{s}(m)={\alpha _{m}}^{\smallfrown }d$
. Initialize all nodes
$\alpha \geq {\alpha _{m}}^{\smallfrown }d$
and all nodes of length
$\geq s+1$
. -
* End Stage s and go to next stage.
-
-
• If the
$\alpha _{m}$
-strategy arrives at Step (4.n) for some
$n\geq 1$
, let
$\delta _{s}(m)=\infty $
. Act as in Step (5.n).-
* Let
$t_{n}=s$
and
$u_{\alpha _{m}, t_{n}}=\varphi ^{2}_{i(\alpha _{m})}(y_{\alpha _{m}, t_{0}}, l(i(\alpha _{m}), s))$
. Then we have because the enumeration of the trigger element
$$ \begin{align*} w_{\alpha_{m},s_{0}} \leq u_{\alpha_{m}, t_{n-1}}&=\varphi^{2}_{i(\alpha_{m})}(y_{\alpha_{m}, t_{0}}, l(i(\alpha_{m}), t_{n-1}))\nonumber\\ &<\varphi^{2}_{i(\alpha_{m})}(y_{\alpha_{m}, t_{0}}, l(i(\alpha_{m}), t_{n}))=u_{\alpha_{m}, t_{n}}\in C_{e(\alpha_{m}), t_{n}}\nonumber \end{align*} $$
$x^{k}_{\alpha _{m}, t_{0}}< w_{\alpha _{m}, s_{0}}$
in Step (3) for
$n=1$
or
$x^{k}_{\beta , t}\in (w_{\alpha _{m},s_{0}}, u_{\alpha _{m}, t_{n-1}})$
in Step (5.
$(n-1)$
) for
$n\geq 2$
forces the number of predecessors of
$y_{\alpha _{m}, t_{0}}$
computed by
$\varphi ^{2}_{i(\alpha _{m})}$
to move up.
As
$u_{\alpha _{m}, t_{n}}\in C_{e(\alpha _{m}), t_{n}}$
and
$u_{\alpha _{m}, t_{n}}> w_{\alpha _{m}, s_{0}}$
, there is a unique node
$\beta>\alpha _{m}$
on the priority tree T with
$e(\beta )=e(\alpha _{m})$
such that where
$$ \begin{align*}u_{\alpha_{m}, t_{n}}=w_{\beta,t} \text{ or }u_{\alpha_{m}, t_{n}}=x^{k}_{\beta,t} \text{ for some }k,\end{align*} $$
$w_{\beta ,t}$
and
$x^{k}_{\beta ,t}(1\leq k\leq q_{\beta }=2^{3^{|\beta |+1}})$
were first appointed on
$\beta $
at some
$\beta $
-stage
$t\in (s_{0}, t_{n})$
.
-
* Pick the largest trigger number
$x^{k}_{\beta ,t}<u_{\alpha _{m},t_{n}}\leq w_{\beta ,t}$
that has not been enumerated into
$C_{e(\beta ')}$
for any
$\beta '\leq \beta $
. -
* Enumerate
$x^{k}_{\beta ,t}$
into
$C_{e(\alpha _{m}),t_{n}}$
. Go to Step (4.(
$n+1$
)).By Lemma 1 below, such a trigger
$x^{k}_{\beta ,t}$
always exists. -
* Initialize all nodes
$\alpha>_{L}{\alpha _{m}}^{\smallfrown }\infty $
. Go to substage
$m+1$
of current stage s if
$m+1<s$
.
-
-
This ends the construction.
Lemma 1. For each node
$\alpha \in T$
, let
$q_{\alpha }=2^{3^{|\alpha |+1}}$
. Suppose that
$s_{0}$
is a first
$\alpha $
-stage after last initialization during the construction such that the witness
$w_{\alpha , s_{0}}$
and the set of trigger elements
$X_{\alpha ,s_{0}}=\{x^{k}_{\alpha , s_{0}}: 1\leq k\leq q_{\alpha }\}$
were first chosen at stage
$s_{0}$
. Then there are enough trigger elements from
$X_{\alpha , s_{0}}$
for higher priority
$\beta $
-strategies to enumerate into
$C_{e(\beta )}$
after stage
$s_{0}$
. That is,
Proof. During the construction, only higher priority
$\mathcal {R}$
-strategies
$\beta \leq \alpha $
with
$e(\beta )=e(\alpha )$
can enumerate triggers from
$X_{\alpha , s_{0}}$
into
$C_{e(\beta )}$
after stage
$s_{0}$
. Furthermore, if
$\beta \leq \alpha $
is initialized at some stage
$s>s_{0}$
, then it will initiate a new strategy later; thus
$\beta $
will not use triggers from
$X_{\alpha , s_{0}}$
after stage s.
Let
$\beta _{1}$
be the first
$\mathcal {R}$
-strategy with
$\beta _{1}\leq \alpha $
that acts as in Step (3) or Step (5.n) for some n to enumerate a trigger
$x^{k}_{\alpha ,s_{0}}$
into
$ C_{e(\beta _{1}),s_{1}}$
at some stage
$s_{1}> s_{0}$
. Then there is a unique even number
$y_{\beta _{1}, s_{1}}$
such that
so we have
$e(\beta _{1})=e(\alpha )$
, and the
$\beta _{1}$
-strategy enumerates the largest
$x^{q_{\alpha }}_{\alpha ,s_{0}}$
into
$ C_{e(\beta _{1}), s_{1}}=C_{e(\alpha ),s_{1}}$
. This enumeration forces the number of predecessors of
$y_{\beta _{1}, s_{1}}$
approximated by
$\varphi ^{2}_{i(\beta _{1})}$
to move up if the
$\beta _{1}$
-strategy next arrives at Step (4.1) from Step (3) or at Step (4.
$(n+1)$
) from Step (5.n) at some stage
$s>s_{1}$
. That is, at stage s, we have
Since we only enumerate witnesses and triggers of nodes of T into
$C_{e(\alpha )}$
during the construction,
$\varphi ^{2}_{i(\beta _{1})}(y_{\beta _{1}, s_{1}}, l(i(\beta _{1}), s))$
is a trigger or witness of some node
$\beta \in T$
with priority strictly lower than
$\alpha $
. The
$\beta _{1}$
-strategy enumerates some trigger of
$\beta $
into
$C_{e(\beta _{1})}=C_{e(\alpha )}$
at stage s. From this analysis, we see that
$\beta _{1}$
never enumerates triggers from the set
$X_{\alpha , s_{0}}$
into
$C_{e(\beta _{1})}$
after stage
$s_{1}$
. So
$\beta _{1}$
uses at most one trigger from
$X_{\alpha , s_{0}}$
.
Let
$\beta _{2}$
be the first
$\mathcal {R}$
-strategy in
$\{\beta \in T: \beta \leq \alpha \}\setminus \{\beta _{1}\}$
that acts as in Step (3) or Step (5.n) for some n to enumerate a trigger
$x^{k}_{\alpha ,s_{0}}$
into
$ C_{e(\beta _{2}),s_{2}}$
at some stage
$s_{2}>s_{1}$
. Then there is a unique even number
$y_{\beta _{2}, s_{2}}$
such that
then
$e(\beta _{2})=e(\alpha )$
and
$k=q_{\alpha }-1$
.
-
(i) If
$\varphi ^{2}_{i(\beta _{2})}(y_{\beta _{2}, s_{2}}, l(i(\beta _{2}), s_{2}))=w_{\alpha ,s_{0}}$
, as in the case of
$\beta _{1}$
-strategy above,
$\beta _{2}$
never enumerates triggers from
$X_{\alpha ,s_{0}}$
into
$C_{e(\beta _{2})}$
after stage
$s_{2}$
. -
(ii) If
$\varphi ^{2}_{i(\beta _{2})}(y_{\beta _{2}, s_{2}}, l(i(\beta _{2}), s_{2}))=x^{q_{\alpha }}_{\alpha ,s_{0}}<w_{\alpha ,s_{0}}$
, the enumeration of
$x^{q_{\alpha }-1}_{\alpha ,s_{0}}$
forces
$\varphi ^{2}_{i(\beta _{2})}(y_{\beta _{2}, s_{2}}, l(i(\beta _{2}), s))>x^{q_{\alpha }}_{\alpha ,s_{0}}$
if the
$\beta _{2}$
-strategy acts as in Step (5.m) for some m to enumerate triggers at some least stage
$s>s_{2}$
.-
• If
$\varphi ^{2}_{i(\beta _{2})}(y_{\beta _{2}, s_{2}}, l(i(\beta _{2}), s))>w_{\alpha , s_{0}}$
, then
$\beta _{2}$
acts to enumerate a trigger of node
$\beta $
with
$\beta>\alpha $
at stage s. -
• If
$\varphi ^{2}_{i(\beta _{2})}(y_{\beta _{2}, s_{2}}, l(i(\beta _{2}), s))=w_{\alpha , s_{0}}$
, then
$\beta _{2}$
acts to enumerate the largest unused trigger
$x^{k}_{\alpha , s_{0}}$
at stage s.
Therefore, the
$\beta _{2}$
-strategy requires at most two triggers from
$X_{\alpha , s_{0}}$
into
$C_{e(\beta _{2})}$
after stage
$s_{0}$
. -
Let
$\beta _{3}$
be the first
$\mathcal {R}$
-strategy in
$\{\beta \in T: \beta \leq \alpha \}\setminus \{\beta _{1}, \beta _{2}\}$
that acts as in Step (3) or Step (5.n) for some n to enumerate a trigger
$x^{k}_{\alpha ,s_{0}}$
into
$ C_{e(\beta _{3}),s_{3}}$
at some stage
$s_{3}>s_{2}$
. Then there is a unique even number
$y_{\beta _{3}, s_{3}}$
such that
and there are at most 1+2=3 triggers
$x^{k}_{\alpha ,s_{0}}\in C_{e(\alpha ), s_{3}} $
. Now it requires at most 4 enumerations of new triggers from
$X_{\alpha , s_{0}}$
into
$C_{e(\beta _{3})}=C_{e(\alpha )}$
to force the number of predecessors of
$y_{\beta _{3}, s_{3}}$
approximated by
$\varphi ^{2}_{i(\beta _{3})}$
, namely,
$\varphi ^{2}_{i(\beta _{3})}(y_{\beta _{3}, s_{3}}, \cdot )$
, to exceed
$w_{\alpha , s_{0}}$
. The total number of triggers from
$X_{\alpha , s_{0}}$
used by
$\beta _{1}, \beta _{2}$
and
$\beta _{3}$
is at most
$1+2+2^{2}=2^{3}-1$
.
Generally, for
$m\geq 2$
, suppose that
$\beta _{m}$
is the first
$\mathcal {R}$
-strategy in
$\{\beta \in T: \beta \leq \alpha \}\setminus \{\beta _{1}, \ldots , \beta _{m-1}\}$
that acts as in Step (3) or Step (5.n) for some n to enumerate a trigger
$x^{k}_{\alpha ,s_{0}}$
into
$ C_{e(\beta _{m}),s_{m}}$
at some stage
$s_{m}>s_{m-1}$
. Then there is a unique even number
$y_{\beta _{m}, s_{m}}$
such that
and there are at most
$1+2+\ldots +2^{m-2}=2^{m-1}-1$
triggers
$x^{k}_{\alpha ,s_{0}}\in C_{e(\alpha ), s_{m}} $
. Since the value of
$\varphi ^{2}_{i(\beta _{m})}(y_{\beta _{m}, s_{m}}, l(i(\beta _{m}), s_{m}))$
has at most
$2^{m-1}$
many possible choices, it requires at most
$2^{m-1}$
many enumerations of new triggers from
$X_{\alpha , s_{0}}$
into
$C_{e(\beta _{m})}=C_{e(\alpha )}$
to force the number of predecessors of
$y_{\beta _{m}, s_{m}}$
to exceed
$w_{\alpha , s_{0}}$
. So the total number of triggers from
$X_{\alpha , s_{0}}$
used by
$\beta _{1},\ldots , \beta _{m}$
is at most
$1+2+\ldots +2^{m-1}=2^{m}-1$
.
Since the number of nodes of length
$\leq |\alpha |$
in the priority tree T is strictly less than
the number of higher priority nodes
$\beta \in T$
with
$\beta \leq \alpha $
is strictly less than
$3^{|\alpha |+1}$
, and we have
$m< 3^{|\alpha |+1}$
. This implies that the total number of triggers from
$X_{\alpha , s_{0}}$
used by all higher priority
$\mathcal {R}$
-strategies
$\beta $
with
$\beta \leq \alpha $
is strictly less than
Therefore, we appoint enough trigger elements
$x^{k}_{\alpha ,s_{0}}$
on node
$\alpha $
for higher priority
$\beta $
-strategies to enumerate into
$C_{e(\beta )}=C_{e(\alpha )}$
during the construction. That is, the trigger elements in Step (3) or Step (5.n) of a basic
$\alpha $
-strategy initiated at stage
$s_{0}$
always exist if needed. This completes the proof of the lemma.
Let
$\mathrm {TP}=\liminf _{s}\delta _{s}$
be the leftmost path on T visited infinitely often during the construction, called the true path of the construction. That is, for any
$n\geq 1$
, the node
$\mathrm {TP}\upharpoonright _{n}=\mathrm {TP}(0)\ldots \mathrm {TP}(n-1)\in T$
is visited infinitely often, but any node
$\alpha <_{L} \mathrm {TP}\upharpoonright _{n}$
is visited finitely often during the construction.
Lemma 2.
$\mathrm {TP}$
is an infinite path on the priority tree T.
Proof. The empty node
$\lambda \subset \mathrm {TP}$
because every stage is a
$\lambda $
-stage; furthermore,
$\lambda $
has the highest priority on the priority tree T, it is not initialized at stages
$s>0$
. Let
$\alpha \subset \mathrm {TP}$
with
$|\alpha |\geq 0$
. Assume that there is a least stage
$s_{\alpha }$
such that
$\alpha $
is not initialized at any stage
$s> s_{\alpha }$
. There are two cases.
Case 1. If
$|\alpha |$
is even,
$\alpha $
is a
$\mathcal {P}$
-strategy. Let
$t_{\alpha }$
be the first
$\alpha $
-stage
$> s_{\alpha }$
. The
$\alpha $
-strategy picks a new witness
$w_{\alpha , t_{\alpha }}$
and a finite set
$\{x^{k}_{\alpha , t_{\alpha }}: 1\leq k\leq q_{\alpha }=2^{3^{|\alpha |+1}}\}$
of new triggers at stage
$t_{\alpha }$
. Since
$\alpha $
has the highest priority after stage
$s_{\alpha }$
, the witness
$w_{\alpha , t_{\alpha }}$
and the triggers
$x^{k}_{\alpha , t_{\alpha }}$
are never redefined later.
-
(1) If the
$\alpha $
-strategy waits at Step (2) forever after stage
$t_{\alpha }$
, then any
$\alpha $
-stage
$s\geq t_{\alpha }$
is an
$\alpha ^{\smallfrown }f$
-stage. In this case,
${\alpha }^{\smallfrown }f$
is not initialized after stage
$t_{\alpha }$
,
$\alpha $
has true outcome f, and we have
${\alpha }^{\smallfrown }f\subset \mathrm {TP}$
. -
(2) Otherwise, the
$\alpha $
-strategy arrives at Step (2) and acts as in Step (3) at some stage
$s>t_{\alpha }$
; the strategy enumerates the witness
$w_{\alpha , t_{\alpha }}$
into
$C_{e(\alpha ),s}$
, making
$C_{e(\alpha )}\neq \varphi _{i(\alpha )}$
, and the construction is terminated at stage s with the current true path
$\delta _{s}=\alpha ^{\smallfrown }d$
. Then any
$\alpha $
-stage
$s'\geq s$
is an
$\alpha ^{\smallfrown }d$
-stage, and
$\alpha ^{\smallfrown }d$
is not initialized after stage s. So we have
$\alpha ^{\smallfrown } d\subset \mathrm {TP}$
.
Case 2. If
$|\alpha |$
is odd, then
$\alpha $
is an
$\mathcal {R}$
-strategy. There are two subcases.
-
(1) If there are finitely many
$\alpha $
-expansionary stages, let
$t_{\alpha }$
be the least stage
$>s_{\alpha }$
such that any
$s\geq t_{\alpha }$
is not an
$\alpha $
-expansionary stage. The basic
$\alpha $
-strategy acts at most once to appoint a new restraint on
$C_{e(\alpha )}$
at some stage
$s\geq t_{\alpha }$
if the believable computation
$\Phi ^{C_{e(\alpha )}}_{j(\alpha )}(j(\alpha ))[s]$
newly converges in which case the
$\alpha $
-strategy terminates current construction by setting the current true path
$\delta _{s}={\alpha }^{\smallfrown }f$
and initializing all nodes
$\geq {\alpha }^{\smallfrown }f$
. This action preserves the believable computation
$\Phi ^{C_{e(\alpha )}}_{j(\alpha )}(j(\alpha ))[s]$
forever, and the
$\alpha $
-strategy never sets new
$C_{e(\alpha )}$
-restraints later. Then
${\alpha }^{\smallfrown }f$
is not initialized after stage s and any
$\alpha $
-stage
$s'\geq s$
is an
${\alpha }^{\smallfrown }f$
-stage. So we have
${\alpha }^{\smallfrown }f\subset \mathrm {TP}$
. -
(2) If there are infinitely many
$\alpha $
-expansionary stages, let
$t_{\alpha }$
be the first
$\alpha $
-expansionary stage
$> s_{\alpha }$
. The
$\alpha $
-strategy picks a new witness
$w_{\alpha , t_{\alpha }}$
and a finite set
$\{x^{k}_{\alpha , t_{\alpha }}: 1\leq k\leq q_{\alpha }=2^{3^{|\alpha |+1}}\}$
of new triggers, it first enumerates
$w_{\alpha ,t_{\alpha }}$
into
$C_{e(\alpha ), t_{\alpha }}$
at the same stage
$t_{\alpha }$
. Since
$\alpha $
has the highest priority after stage
$s_{\alpha }$
, the witness
$w_{\alpha , t_{\alpha }}$
and the triggers
$x^{k}_{\alpha , t_{\alpha }}$
are never redefined later.-
• If the
$\alpha $
-strategy waits at Step (2) forever after stage
$t_{\alpha }$
, then any
$\alpha $
-expansionary stage
$s\geq t_{\alpha }$
is an
$\alpha ^{\smallfrown }d$
-stage. In this case,
${\alpha }^{\smallfrown }d$
is not initialized after stage
$t_{\alpha }$
, and we have
${\alpha }^{\smallfrown }d\subset \mathrm {TP}$
. -
• Otherwise, the
$\alpha $
-strategy arrives at Step (2) and acts as in Step (3) at some stage
$t_{0}>t_{\alpha }$
. At stage
$t_{0}$
, the strategy enumerates the largest unused trigger
$x^{k}_{\alpha , t_{\alpha }}$
into
$C_{e(\alpha ), t_{0}}$
; the construction is terminated by setting the current true path
$\delta _{t_{0}}=\alpha ^{\smallfrown }d$
, and initializing all nodes
$\geq \alpha ^{\smallfrown }d$
. There are two possible situations after stage
$ t_{0}$
.-
* The
$\alpha $
-strategy waits at Step (4.n) forever after certain stage
$s>t_{0}$
. Then any
$\alpha $
-expansionary stage
$s'\geq s$
is an
$\alpha ^{\smallfrown }d$
-stage. In this case,
$\alpha ^{\smallfrown }d$
is not initialized after stage s and
${\alpha }^{\smallfrown }d\subset \mathrm {TP}$
. -
* The
$\alpha $
-strategy arrives at Step (4.
$(n+1)$
) from Step (5.n) infinitely often after stage
$t_{0}$
. Then there are infinitely many
$\alpha $
-expansionary stages
$s>t_{0}$
such that the
$\alpha $
-strategy acts as in Step (5.n) for some n at stage s by enumerating a largest unused trigger of some node with lower priority into
$C_{e(\alpha ), s}$
. Such a stage s is an
${\alpha }^{\smallfrown }\infty $
-stage. In this case,
$\alpha ^{\smallfrown }\infty $
is not initialized after stage
$t_{0}$
and
${\alpha }^{\smallfrown }\infty \subset \mathrm {TP}$
.
-
-
We have seen that for any
$\alpha \subset \mathrm {TP}$
with
$|\alpha |\geq 0$
, there is a least stage
$s_{\alpha }$
such that
$\alpha $
is not initialized after stage
$s_{\alpha }$
. The
$\alpha $
-strategy acts after stage
$s_{\alpha }$
with an outcome o such that
$\alpha ^{\smallfrown }o\subset \mathrm {TP}$
. This shows that
$\mathrm {TP}$
is an infinite path on the priority tree T.
Lemma 3. For all e,
$C_{e}$
is noncomputable.
Proof. For fixed numbers
$e, i$
, let
$\alpha $
be the unique
$\mathcal {P}_{\langle e, i\rangle }$
-strategy along the true path
$\mathrm {TP}$
of the construction, then
$\alpha $
is initialized finitely often, and there are infinitely many
$\alpha $
-stages during the construction. Suppose that
$\alpha $
has the highest priority after some least stage
$s_{\alpha }$
. The
$\alpha $
-strategy acts to diagonalize against
$\varphi _{i}$
computing
$C_{e}$
after stage
$s_{\alpha }$
.
-
(i) If the strategy waits at Step (2) forever after certain stage, then there is a witness w such that either
$\varphi _{i}(w)$
diverges or it converges with
$\varphi _{i}(w)\downarrow =1\neq C_{e}(w)=0$
; in this case,
$\alpha $
has true outcome
$ f$
. -
(ii) If the strategy arrives at Step (2) and acts as in Step (3) at some stage
$s>s_{\alpha }$
, then there is a witness w such that
$\varphi _{i}(w)\downarrow =0\neq C_{e}(w)=1$
; in this case,
$\alpha $
has true outcome
$ d$
.
The
$\alpha $
-strategy succeeds to ensure that
$C_{e}\neq \varphi _{i}$
after stage
$s_{\alpha }$
. Then
$C_{e}\neq \varphi _{i}$
for all i, and thus it is not computable.
Lemma 4. For all e,
$e\in \mathrm {Cof}^{K}$
if and only if
$C_{e}$
is order-computable.
Proof. Fix a number e. If
$e\in \mathrm {Cof}^{K}$
,
$W^{K}_{e}$
is cofinite. Then there exists a number i such that
$[i, \infty )\subseteq W^{K}_{e}$
, that is,
$[i, i+j+1] \subseteq W^{K}_{e}$
for all j. For any node
$\alpha $
assigned an
$\mathcal {R}_{\langle e, i,\cdot \rangle }$
-requirement on the priority tree, there are only finitely many
$\alpha $
-expansionary stages. For each j, there is a unique node
$\alpha _{\langle e, i,j\rangle }$
working for
$\mathcal {R}_{\langle e, i,j\rangle }$
along the true path
$\mathrm {TP}$
of the construction such that
For each j, the
$\alpha _{\langle e, i,j\rangle }$
-strategy is not initialized after certain stage
$s_{j}$
. Then
$s_{0}\leq s_{1}\leq \ldots \leq s_{j}\leq \ldots $
because of the priority of the strategies.
$\alpha _{\langle e, i,j\rangle }$
acts at most once to appoint a new
$C_{e}$
-restraint
$\phi ^{C_{e}}_{j}(j)[s]$
to preserve the believable computation
$\Phi ^{C_{e}}_{j}(j)[s]$
if it newly converges at some stage
$s\in (s_{j}, s_{j+1}]$
. Since the computation
$\Phi ^{C_{e}}_{j}(j)[s]\downarrow $
is believable, all higher priority
$\mathcal {R}$
-strategies
$\beta $
with
$\beta ^{\smallfrown } \infty \subset \alpha _{\langle e, i,j\rangle }$
only enumerate triggers
$x^{k}_{\beta ', s'}$
of nodes
$\beta '>\alpha _{\langle e, i, j\rangle }$
at any stage
$s'\geq s$
such that
$x^{1}_{\beta ', s'}>\phi ^{C_{e}}_{j}(j)[s]$
, the use of the believable computation. Then the computation
$\Phi ^{C_{e}}_{j}(j)[s]\downarrow $
is not injured by
$\beta $
-strategy after stage s, and thus, it is preserved forever. Then
$C^{\prime }_{e}$
is a
$\Delta ^{0}_{2}$
set because for all j,
$j\in C^{\prime }_{e}$
if and only
$\Phi ^{C_{e}}_{j}(j)$
converges if and only if there are infinitely many stages s such that the computation
$\Phi ^{C_{e}}_{j}(j)[s]\downarrow $
is believable. Therefore,
$C_{e}$
is a low c.e. set, and thus, it is order-computable.
If
$e\notin \mathrm {Cof}^{K}$
,
$W^{K}_{e}$
is not cofinite. Now for all i, there is a least number
$j_{i}$
such that
$[i, i+j_{i}+1]\nsubseteq W^{K}_{e}$
. For all i, there are only finitely many nodes for
$\mathcal {R}_{\langle e, i,\cdot \rangle }$
-requirements along the true path
$\mathrm {TP}$
of the construction, one node
$\alpha _{\langle e, i,j\rangle }$
for
$\mathcal {R}_{\langle e, i,j\rangle }$
with
$0\leq j\leq j_{i}$
such that each
$\alpha _{\langle e, i,j\rangle }$
with
$j<j_{i}$
has the finite outcome f and the longest node
$\alpha _{\langle e, i,j_{i}\rangle }$
has an infinite outcome
$o\in \{d,\infty \}$
. That is,
Let
$\alpha =\alpha _{\langle e, i,j_{i}\rangle }$
be the
$\mathcal {R}_{\langle e, i, j_{i}\rangle }$
-strategy along the true path
$\mathrm {TP}$
of the construction, then
$\alpha $
is initialized finitely often, and there are infinitely many
$\alpha $
-expansionary stages.
$\alpha $
has the highest priority after certain stage
$s_{\alpha }$
. After stage
$s_{\alpha }$
, the
$\alpha $
-strategy acts to diagonalize against
$\varphi ^{2}_{i}$
to be a computable predecessor approximation function for
$C_{e}$
.
-
(i) If the strategy waits at Step (2) or Step (4.n) forever after certain stage, then either
$\lim _{s}l(i,s)<\infty $
or
$C_{e}\neq O_{i}$
, the order-computable set computed by
$\varphi ^{2}_{i}$
; in this case,
$\alpha $
has true outcome d, and
$\alpha ^{\smallfrown } d\subset \mathrm {TP}$
. -
(ii) If the strategy first arrives at Step (2) and then arrives at Step (4.
$(n+1)$
) from Step (5.n) infinitely often, then there is an even number y such that
$\lim _{s}\varphi ^{2}_{i}(y,s)=\infty $
; in this case,
$\alpha $
has true outcome
$\infty $
, and
$\alpha ^{\smallfrown }\infty \subset \mathrm {TP}$
.
The
$\alpha $
-strategy succeeds in ensuring that
$C_{e}$
is not order-computed by
$\varphi ^{2}_{i}$
after stage
$s_{\alpha }$
. Then
$C_{e}$
is not order-computed by
$\varphi ^{2}_{i}$
for all i, and thus it is not order-computable.
We have constructed a uniform sequence of c.e. sets
$\langle C_{e}: e\in \mathbb {N}\rangle $
such that
$e\in \mathrm {Cof}^{K}$
if and only if
$ C_{e}$
is order-computable for all e. Since
$\mathrm {Cof}^{K}$
is
$\Sigma ^{0}_{4}$
-complete, so is the index set of c.e. order-computable sets. This completes the proof of Theorem 1.
Recall that
$\mathcal {I}=\{e\in \mathbb {N}: \varphi ^{2}_{e} \text { is total, and }(\forall x)[\lim _{s}\varphi ^{2}_{e}(x,s)\downarrow \in \{0,1\}]\}$
is the index set of
$\Delta ^{0}_{2}$
sets. For
$e\in \mathcal {I}$
,
$A_{e}=\{x\in \mathbb {N}: (\forall x)[\lim _{s}\varphi ^{2}_{e}(x,s)\downarrow =1]\}$
is the
$\Delta ^{0}_{2}$
set with index e. Since both c.e. sets and order-computable sets form subclasses of
$\Delta ^{0}_{2}$
sets, based on Theorem 1, we obtain the exact complexity for general order-computable sets.
Corollary 1. The index set
$\{e\in \mathcal {I}: A_{e}\text { is order-computable}\}$
is
$\Sigma ^{0}_{4}$
-complete within
$\mathcal {I}$
.
Proof. For a number e,
$e\in \mathcal {I}$
if and only if
$\varphi ^{2}_{e}$
is a computable binary function such that
$\lim _{s}\varphi ^{2}_{e}(x,s)$
converges to 0 or 1 for all x. To prove the corollary, it suffices to construct a uniform sequence
$\langle F_{e}: e\in \mathbb {N}\rangle $
of computable binary functions such that the following two conditions hold:
-
(1) for all e,
$ \lim _{s}F_{e}(x,s)$
converges to 0 or 1 for all x; -
(2) for all e,
$e\in \mathrm {Cof}^{K}\Leftrightarrow B_{e}=\{x\in \mathbb {N}: \lim _{s}F_{e}(x,s)\downarrow =1\} \text { is order-computable}.$
Let
$\langle C_{e}: e\in \mathbb {N}\rangle $
be the uniform sequence of c.e. sets constructed in Theorem 1 such that
$e\in \mathrm {Cof}^{K}\Leftrightarrow C_{e}$
is order-computable for all e. For any
$e,x,s$
and
$t>x,s$
, define
$F_{e,t}(x,s)=C_{e,s}(x)$
. Then the sequence
$\langle F_{e}: e\in \mathbb {N}\rangle $
meets the desired conditions above. First,
$F_{e}(x,s)$
is defined for all
$x,s$
, so
$F_{e}$
is a computable binary function. Second, since
$C_{e,s}(x)$
changes from 0 to 1 for at most once when x is first enumerated into
$C_{e}$
at stage s, the condition (1) holds. Third,
$\lim _{s}F_{e}(x,s)$
converges to 1 if and only if
$x\in C_{e}$
, so
$B_{e}=\{x\in \mathbb {N}: \lim _{s}F_{e}(x,s)\downarrow =1\}=C_{e}$
for all e; the condition (2) holds.
4 Index set of
$\Delta ^{0}_{2}$
sets
We continue to study the complexity of the index set
$\mathcal {I}$
of
$\Delta ^{0}_{2}$
sets.
Theorem 2. The index set
$\mathcal {I}$
of
$\Delta ^{0}_{2}$
sets is
$\Pi ^{0}_{3}$
-complete.
Proof. For any number e, e is an index of a
$\Delta ^{0}_{2}$
set if and only if
$\varphi ^{2}_{e}$
is total and
$\lim _{s}\varphi ^{2}_{e}(x,s)$
converges to 0 or 1 for all x in which case e is the index of the
$\Delta ^{0}_{2}$
set
$A_{e}=\{x\in \mathbb {N}: \lim _{s}\varphi ^{2}_{e}(x,s)\downarrow =1\}$
. As
${\mathrm {Tot}}^{K}=\{e\in \mathbb {N}: (\forall x)[\Phi ^{K}_{e}(x) \text { converges}]\}$
is
$\Pi ^{0}_{2}$
-complete relative the c.e. complete set K, it is
$\Pi ^{0}_{3}$
-complete. To prove the theorem, it suffices to construct a uniform sequence
$\langle F_{e}: e\in \mathbb {N}\rangle $
of computable binary functions such that for all e,
We will build a computable ternary function
$F(\cdot , \cdot ,\cdot )$
satisfying the following requirements:
-
: If
$\Phi ^{K}_{e}(x)$
is defined, then
$\lim _{s}F(e,x,s)$
converges to 0.If
$\Phi ^{K}_{e}(x)$
is undefined, then
$\lim _{s}F(e,x,s)$
diverges.
Then
$\langle F_{e}=F(e,\cdot , \cdot ): e\in \mathbb {N}\rangle $
is the desired sequence of computable binary functions.
If
$e\in {\mathrm {Tot}}^{K}$
,
$\Phi ^{K}_{e}$
is total, i.e.,
$\Phi ^{K}_{e}(x)$
is defined for all x, then
$\mathcal {R}_{\langle e, x\rangle }$
ensures that
$\lim _{s}F_{e}(x,s)$
converges to 0. In this case,
$F_{e}$
approximates the empty set
$\emptyset =\{x: \lim _{s}F_{e}(x,s)\downarrow =1\}$
. If
$e\notin {\mathrm {Tot}}^{K}$
,
$\Phi ^{K}_{e}$
is not total, i.e., there is a number x such that
$\Phi ^{K}_{e}(x)$
is undefined, then
$\mathcal {R}_{\langle e, x\rangle }$
ensures that
$\lim _{s}F(e,x,s)$
diverges. In this case,
$F_{e}$
cannot approximate a
$\Delta ^{0}_{2}$
set.
Fix an effective bijection
$\langle \cdot ,\cdot \rangle :\mathbb {N}^{2}\rightarrow \mathbb {N}$
, and for all
$i,j,k$
, let
$\langle i, j, k\rangle =\langle \langle i,j\rangle ,k \rangle $
. We construct the computable ternary function
$F(\cdot ,\cdot ,\cdot )$
by stages.
Construction.
Stage 0. Define
$F(0,0,0)=F(0,0,1)=0$
.
Assume that we have defined
$F(e,x,y)$
for all
$e,x$
with
$e,x\leq s-1$
and
$y\leq 2s-1$
by the end of stage
$s-1$
.
Stage
$s\geq 1$
. For all
$e,x\leq s$
, define
$F(e,x,\cdot )$
as follows:
Step 1. For all
$ e, x < s$
, define
$F(e,x,2s)$
and
$F(e,x,2s+1)$
as follows. There are two cases:
-
(1) If there was a last stage
$s^{-}<s$
such that
$\Phi ^{K}_{e}(x)[s^{-}]$
was defined with use
$\phi ^{K}_{e}(x)[s^{-}]$
and the computation has not been changed since then, that is,
$\Phi ^{K}_{e}(x)[s] $
is defined with use
$\phi ^{K}_{e}(x)[s]=\phi ^{K}_{e}(x)[s^{-}]$
, define
$$ \begin{align*}F(e,x,2s)= F(e,x,2s+1)=0.\end{align*} $$
-
(2) Otherwise, either
$\Phi ^{K}_{e}(x)[t]$
was undefined for all
$t<s$
, or there was a convergent computation
$\Phi ^{K}_{e}(x)[s^{-}]$
at last stage
$s^{-}<s$
but the computation is changed currently, that is, either
$\Phi ^{K}_{e}(x)[s]$
is undefined or it is defined with use
$\phi ^{K}_{e}(x)[s]>\phi ^{K}_{e}(x)[s^{-}]$
, define
$$ \begin{align*}F(e,x,2s)=0\text{ and } F(e,x,2s+1)=1.\end{align*} $$
Step 2. For all
$e,x\leq s$
and
$t\leq 2s+1$
, define
$ F(e,s,t)=F(s,x,t)=0$
.
This ends the construction.
For all
$e,x\in \mathbb {N}$
, at any stage s bigger than
$ e, x $
of the construction, we have defined
$F(e,x,y)$
for all
$y\leq 2s+1$
by the end of stage s. Furthermore, the value of
$F(e,x,y)$
is never changed during the construction. So F is a computable ternary function.
Lemma 5. For all
$e,x\in \mathbb {N}$
,
$\mathcal {R}_{\langle e,x \rangle }$
is satisfied.
Proof. Fix numbers
$e, x$
. If
$\Phi ^{K}_{e}(x)$
is defined, then there is a least stage s such that the
$\Phi ^{K}_{e}(x)[s]$
is defined with use
$ \phi ^{K}_{e}(x)[s]$
and the computation is not changed later; that is, at any stage
$t\geq s$
, the computation
$\Phi ^{K}_{e}(x)[t]$
is defined with use
$\phi ^{K}_{e}(x)[t]$
the same as
$ \phi ^{K}_{e}(x)[s]$
. Let
$s_{e,x}$
be such a least stage bigger than
$ e, x $
. Then at any stage
$s> s_{e,x}$
, we always defined
$F(e,x,2s)=F(e,x,2s+1)=0$
. So
$F(e,x,y)=0$
for all
$y>2s_{e,x}$
and we have
$\lim _{s}F(e,x,s)=0$
.
If
$\Phi ^{K}_{e}(x)$
is undefined, then there are infinitely many stages
$s>e,x$
such that either the computation
$\Phi ^{K}_{e}(x)[s]$
is undefined or it is defined with use strictly bigger than that of the last convergent computation. At such a stage s, we defined
$F(e,x,2s)=0$
, but
$F(e,x,2s+1)=1$
. So
$\lim _{s}F(e,x,s)$
does not exist.
For a number e, there are two situations:
-
• If
$e\in {\mathrm {Tot}}^{K}$
, then
$\Phi ^{K}_{e}(x)$
is defined for all x. By Lemma 5,
$\lim _{s}F(e,x,s)=0$
for all x. In this case,
$F_{e}=F(e,\cdot ,\cdot )$
approximates the
$\Delta ^{0}_{2}$
set
$\{x: \lim _{s}F(e,x,s)\downarrow =1\}$
, which is exactly the empty set
$\emptyset $
. -
• If
$e\notin {\mathrm {Tot}}^{K}$
, then
$\Phi ^{K}_{e}(x)$
is undefined for some x. By Lemma 5,
$\lim _{s}F(e,x,s)$
does not exist for this x. In this case,
$F_{e}=F(e,\cdot ,\cdot )$
cannot approximate any
$\Delta ^{0}_{2}$
set.
We have constructed a uniform sequence of computable binary functions
$\langle F_{e}=F(e,\cdot ,\cdot ): e\in \mathbb {N}\rangle $
such that for all e,
$\Phi ^{K}_{e}$
is total if and only if
$\lim _{s}F_{e}(x,s)$
exists with limit 0 for all x. So the index set
$\mathcal {I}$
of
$\Delta ^{0}_{2}$
sets is
$\Pi ^{0}_{3}$
-complete.
This completes the proof of Theorem 2.
Acknowledgments
The author sincerely thanks the referees for the supportive comments and useful suggestions, which have improved the quality of the original paper.
Funding
This work was supported by the National Natural Science Foundation of China (Grant No. 12301001).








