Mass Problems and Randomness
Stephen G. Simpson
Department of Mathematics
Draft: October 27, 2004
Pennsylvania State University
This research was partially supported by NSF grant
DMS-0070718. I would like to thank Stephen Binns for discussing these
topics with me.
AMS 2000 Subject Classifications: 03D30, 03D80, 03D25,
03F35, 03F15, 68Q30, 68Q15.
Bulletin of Symbolic Logic, 11, 2005, pp. 1-27.
Abstract:
A
mass problem is a set of Turing oracles. If

and

are mass problems, we say that

is
weakly reducible to

if every member of

Turing computes a member of

. We say that

is
strongly reducible to

if every member of

Turing computes a member of

via a fixed Turing functional. The
weak degrees and
strong degrees are the equivalence
classes of mass problems under weak and strong reducibility,
respectively. We focus on the countable distributive lattices

and

of weak and strong degrees of mass problems given by
nonempty

subsets of

. Using an abstract
Gödel/Rosser incompleteness property, we characterize the

subsets of

whose associated mass problems are
of top degree in

and

, respectively. Let

be the set
of Turing oracles which are
random in the sense of
Martin-Løf, and let

be the weak degree of

. We
show that

is a natural intermediate degree within

. Namely, we characterize

as the unique largest
weak degree of a

subset of

of positive measure.
Within

we show that

is meet irreducible, does not
join to

, and is incomparable with all weak degrees of
nonempty thin perfect

subsets of

. In addition,
we present other natural examples of intermediate degrees in

.
We relate these examples to reverse mathematics, computational
complexity, and Gentzen-style proof theory.
Introduction
Among the principal objects of study in recursion theory going back to
the seminal work of Turing [59] and Post [44] have
been the upper semilattice
of all Turing degrees, i.e.,
degrees of unsolvability, and its countable sub-semilattice
consisting of the recursively enumerable Turing degrees, i.e.,
the Turing degrees of recursively enumerable sets of positive
integers. See for instance Sacks [46], Rogers
[45], Lerman [36], Soare [56], Odifreddi
[42,43].
A major difficulty or obstacle in the study of
has been the lack
of natural examples. Although it has long been known that
is
infinite and structurally rich, to this day no specific, natural
examples of recursively enumerable Turing degrees are known, beyond
the two original examples noted by Turing:
the Turing
degree of the Halting Problem, and
the Turing degree of
solvable problems. Furthermore,
and
are
respectively the top and bottom elements of
. This lack of
natural examples, although well known and a major source of
frustration, has almost never been discussed in print, but see Rogers
[45, Section 9.6]. In any case, the paucity of examples in
is striking, because it is well known that most other branches
of mathematics are motivated and nurtured by a rich stock of natural
examples. Clearly it ought to be of interest to somehow overcome this
deficiency in the study of
.
In recent years it has emerged that there are some natural, important,
well-behaved degree structures, closely related to but different from
, which do not suffer from the above mentioned deficiency.
Simpson 1999
[50,51,54] called
attention to the countable distributive lattices
and
of
weak and strong degrees of mass problems given by nonempty
subsets of
, and noted the existence of specific, natural
degrees which are intermediate between the top and bottom elements of
and
. One of the natural intermediate degrees noted by
Simpson was the weak degree
of the set of Turing oracles
which are random in the sense of Martin-Løf [39]. The
study of
and
has been continued by Simpson
[53,49],
Cenzer/Hinman [9], Simpson/Slaman [55], Binns
[3,4,5], Binns/Simpson
[6], Terwijn [58].
The purpose of the present paper is to elucidate additional properties
of previously noted natural degrees in
and
, and to present
some additional natural degrees in
. Along the way we give a
somewhat leisurely introduction to mass problems in general, and to
and
in particular, and we review other known results
concerning
and
.
In a later paper [48] we shall exhibit a natural embedding of
the countable upper semilattice
into the countable distributive
lattice
. This embedding will be one-to-one and will preserve
the top and bottom elements as well as the partial order relation and
least upper bound operation from
. In this way we shall see that
provides a satisfactory solution to several of the well known
difficulties concerning
.
In this section we establish notation concerning recursive functionals
and Turing degrees.
Throughout this paper we use standard recursion-theoretic notation and
concepts from Rogers [45] and Soare [56]. We write
for the set of natural numbers. We write
for the space of total functions from
into
. We write
for the subspace of
consisting of the total functions from
into
. We
sometimes identify a set
with its characteristic
function
given by
if
,
if
. For
and
we write
to mean that the Turing machine with Gödel number
and oracle
and input
eventually halts with output
.
Furthermore,
means that
is
defined, i.e.,
, and
means that
is undefined,
i.e.,
. In the absence of an oracle
, we write simply
, etc. For
we consider recursive functionals
given by
for some
and all
and
. In particular, a function
is
said to be recursive or computable if there exists
such that
for all
. (The
terms ``recursive'' and ``computable'' are synonymous.) A set
is said to be recursively enumerable if it
is the image of a recursive function, i.e.,
for some recursive
.
For
we write
to mean that
is
Turing reducible to
, i.e.,
. The Turing degree of
, denoted
, is the set of all
such that
, i.e.,
and
. The set
of all Turing degrees is
partially ordered by putting
if and only if
. Under this partial ordering, the bottom element of
is
is recursive
. It is
known that
has no top element. Within
, the least upper
bound of
and
is given as
where
and
for all
. The standard, natural example of a Turing degree
is given by the Turing jump operator,
, where
is (the
characteristic function of) the Halting Problem relative to
,
. A Turing degree is said to
be recursively enumerable if it is
where
is the characteristic function of a recursively enumerable set
. The set of all recursively enumerable Turing
degrees is denoted
. Clearly
is countable, because there
are only countably many recursively enumerable sets. It is known that
is closed under the least upper bound operation inherited from
, and that
and
are the top and bottom
elements of
. Thus
is a countable upper semilattice with a
top and bottom element.
Mass problems
A mass problem is a subset of
. The underlying
idea here is to view a set
as a ``problem''
with a ``solution'' that does not necessarily exist and is not
necessarily unique. The ``solutions'' of
are simply the members
of
. In the special case when
is a singleton set, the
``solution'' exists and is unique, and the mass problem corresponds to
a Turing degree.
In accordance with the conceptual scheme which was explained in the
previous paragraph, one makes the following definitions.
Definition 3.1
Let

and

be subsets of

. We say that

is
weakly reducible to

, written

, if for all

there exists

such that

. Conceptually this
means that, given any ``solution'' of the mass problem

, we can
use it as an oracle to compute a ``solution'' of the mass problem

. The
weak degree of

, written

, is the set
of all

such that

, i.e.,

and

.
The set

of all weak degrees is partially ordered by putting

if and only if

.
Remark 3.2
The concept of weak reducibility goes back to Muchnik
[
41] and has sometimes been called
Muchnik
reducibility.
Definition 3.3
We say that

is
strongly reducible to

, written

, if there exists

such that for all

there
exists

such that

for all

.
In other words,

if and only if there exists a recursive
functional

. Note that strong reducibility is the
uniform variant of weak reducibility. Just as for weak degrees, the
strong degree of

, written

, is the set of all

such that

, i.e.,

and

. The set

of all strong degrees is partially ordered by putting

if and only if

.
Remark 3.4
The concept of strong reducibility goes back to Medvedev [
40]
and has sometimes been called
Medvedev reducibility.
Remark 3.5
Given

, a
recursive homeomorphism
of

onto

is a recursive functional

mapping

one-to-one onto

such that the inverse functional

is also recursive. In this case we say that

and

are
recursively homeomorphic. In addition, let us say that

is
Turing degree isomorphic to

if

. Clearly recursive homeomorphism of

and

implies strong equivalence and Turing degree
isomorphism, either of which implies weak equivalence. No other
implications hold.
Theorem 3.6
and
are distributive lattices. They have a bottom
element, denoted
, and a top element, denoted
.
Remark 3.7
There are obvious, natural embeddings of

into

and

given by

and

respectively. Here

is the
singleton set whose only member is

. These
embeddings are one-to-one and preserve

and the partial
order relation and least upper bound operation from

.
Remark 3.8
There is an obvious lattice homomorphism of

onto

given
by

.
Remark 3.9

is canonically isomorphic to the lattice of upward closed
subsets of

under the set-theoretic operations of intersection
and union. Namely, for each

, the weak
degree

gets mapped to the upward closure of

within

. It follows that

is a
complete distributive lattice. We do not know of an analogous
set-theoretic representation of

.
Remark 3.10
For a survey of general mass problems, see Sorbi
[
57].
Recursively bounded
sets
In this section we present some well known generalities concerning
recursively bounded
sets and almost recursive functions.
The reader is advised to skip most of this section now, and refer to
it later as needed.
Definition 4.1
A predicate

is said to be
recursive if

if

, and

if

.
A set

is said to be

if there
exists a recursive predicate

such that

.
Definition 4.2
A finite sequence of natural numbers

is called a
string of length

. We write

. The set of
all strings is denoted

. If

are
strings of length

respectively, then the
concatenation
is a string of length

. Note that

if and
only if

for some

, and this implies

. If

is a string of length

,
then for all

we have

defined by

for

,

for

. Note that

if and
only if

for some

. A
tree is a set

such that, for all

,

. A
path through

is an

such that

. The set of all paths through

is denoted
![$[T]$](img128.png)
. We sometimes identify a string

with its Gödel
number

. A tree

is said to be
recursive if

is recursive,
and

if

is

.
Theorem 4.3
is
if and only if
for
some recursive tree
.
Theorem 4.4
If
are
and
is a recursive functional, then the
preimage
is
.
Definition 4.5
A set

is said to be
recursively
bounded if there exists a recursive function

such that

for all

and

.
Remark 4.6
Any subset of a recursively bounded set is recursively bounded. We
shall be concerned with subsets of

which are
recursively bounded and

. In particular,

is
recursively bounded and

, and we are especially interested
in

subsets of

. As in Theorem
4.3,

is a

subset of

if and only if
![$P=[T]$](img131.png)
for
some recursive tree

. Here

denotes the set of all strings of

's and

's. See also Theorem
4.10 and Corollary
4.11 below.
Theorem 4.7
Assume that
is recursively bounded
, and assume that
is a recursive
functional. Then the image
is recursively
bounded
. Moreover, there exists a total recursive
functional
such that
extends
, i.e.,
for
all
.
Definition 4.8
In general, suppose that to each

we have effectively
associated a finite sequence of ordered pairs

where

and

for each

. Define a recursive functional

by putting

where

is minimal such that

, or

if no such

exists. Then

is called a
truth table functional. For

we say
that

is
truth table reducible to

, written

, if there exists a truth table functional

such
that

. Rogers [
45, Chapter 8 and Section 9.6]
provides general background on truth table reducibility.
Corollary 4.9
Assume that
is recursively bounded
, and assume that
is a recursive
functional. Then
can be extended to a truth table
functional. In particular,
for all
.
Theorem 4.10
Let
be a recursively bounded
set. Then
is
recursively homeomorphic to a
subset of
.
Corollary 4.11
The weak (strong) degrees of nonempty recursively bounded
sets are the same as the weak (strong) degrees of nonempty
subsets of
.
Definition 4.12
Given

, put
the set of
extendible nodes of

. Note that

is a
tree, and
![$[\mathrm{Ext}(P)]$](img163.png)
is the topological closure of

in

. In particular, if

is

, then
![$P=[\mathrm{Ext}(P)]$](img164.png)
.
Lemma 4.13
Let
be a recursively bounded
set. Then
is
.
Definition 4.14
For

, an
isolated point of

is an

such that, for some string

,

is the unique

such that

. We say that

is
perfect if

has no isolated points.
Theorem 4.15
Let
be a recursively bounded
set. If
is an
isolated point of
, then
is recursive.
Corollary 4.16
Let
be a recursively bounded
set. If the weak or
strong degree of
is
, then
is perfect.
Definition 4.17
We say that

is
almost recursive if for
all

there exists

such that

and

is recursive. (Turing degrees which contain
almost recursive functions have been known in the literature as
hyperimmune-free Turing degrees.)
Theorem 4.18
Suppose
is almost recursive. Then for all
we have
, i.e.,
is truth table reducible to
. In
particular,
for some total recursive functional
.
We end this section with the Almost Recursive Basis Theorem.
Theorem 4.19
If
is nonempty, recursively bounded, and
, then there exists
such that
is almost
recursive.
The lattices
and
In this section we introduce the lattices
and
which are
the focus of this paper.
Remark 5.1
There is a large recursion-theoretic literature concerning Turing
degrees of members of

subsets of

, and
especially Turing degrees of members of recursively bounded

subsets of

. See for instance the classic
paper of Jockusch and Soare [
26] and the survey article by
Cenzer and Remmel [
10]. Mindful of this
literature, we find it natural to view nonempty recursively bounded

sets as mass problems.
By Theorem 4.10 and Corollary 4.11, it suffices to
consider
subsets of
.
Definition 5.2

(

) is the set of weak (strong) degrees of nonempty
recursively bounded

sets. By Corollary
4.11,

(

) is the same as the set of weak (strong) degrees of
nonempty

subsets of

.
Theorem 5.3
and
are countable distributive lattices with a top and
bottom element, denoted
and
respectively.
Remark 5.4
There is an obvious lattice homomorphism of

onto

given
by

. Simpson and Slaman [
55]
have shown that every nonzero weak degree in

contains
infinitely many strong degrees in

.
Remark 5.5
In the context of recursively bounded

sets, there is
reason to view weak reducibility as the mass problem analog of
Turing reducibility, while strong reducibility is the mass problem
analog of truth table reducibility. See Rogers [
45, Sections 8.3
and 9.6] and Simpson [
54, Remark 3.12]. Namely,
if

is recursively bounded

and

, then by
Corollary
4.9 the recursive functional

is
given by truth tables, hence for each

there exists

such that

, i.e.,

is truth table
reducible to

. Thus we see that

is analogous to

, the
recursively enumerable Turing degrees, while

is more closely
analogous to

, the recursively enumerable truth table degrees.
Remark 5.6
It is known that the countable distributive lattices

and

are structurally rich. Binns/Simpson [
3,
6]
have shown that every countable distributive lattice is lattice
embeddable in every nontrivial initial segment of

. A similar
conjecture for

remains open, although partial results in this
direction are known. Binns [
3,
4] has
obtained the

and

analogs of the Sacks Splitting Theorem.
Namely, for all

in

there exist

in

such that

, and similarly for

. Cenzer/Hinman [
9] have obtained the

analog of
the Sacks Density Theorem. Namely, for all

in

there exists

in

such that

. A similar conjecture for

remains open. Binns [
3,
4] has improved
the result of Cenzer/Hinman [
9] by showing that for all

in

there exist

in

such that

. These structural
results for

and

are proved by means of priority
arguments. They invite comparison with the older, known results for
recursively enumerable Turing degrees, which were also proved by
priority arguments.
Weak and strong completeness
In this section we obtain additional information concerning sets which
are of weak or strong degree
in
or
,
respectively. We show that, if
is a nonempty recursively bounded
set, then
if and only if
is
Turing degree isomorphic to
, and
if and
only if
is recursively homeomorphic to
.
By Theorem 4.10 and Corollary 4.11, it suffices to
consider
subsets of
.
Definition 6.1
Let

be a nonempty recursively bounded

set.

is
weakly complete if

, i.e.,

for all nonempty

sets

.

is
strongly complete if

, i.e.,

for all nonempty

sets

. These notions
have sometimes been referred to as
Muchnik completeness and
Medvedev completeness, respectively.
Remark 6.2
We have seen in the proof of Theorem
5.3 that

is
strongly complete, hence weakly complete. In addition, there are
natural examples of recursively bounded

sets which are
weakly complete but not strongly complete. See Definition
7.9 and Remark
7.10 below.
Theorem 6.3
Let
and
be nonempty
subsets of
.
- If
and
are strongly complete, then
is recursively
homeomorphic to
.
- If
is strongly complete, then we can find a recursive
functional
which is onto
, i.e.,
.
is strongly complete if and only if
is
productive, i.e., given an index of a nonempty
set
we can effectively find a canonically indexed
clopen set
such that both
and
are nonempty.
Corollary 6.4
Let
be a nonempty recursively bounded
set. If
is
strongly complete, then the set of Turing degrees of members of
is upward closed.
Corollary 6.5
Let
be a nonempty recursively bounded
set. Then
is strongly complete if and only if
is recursively homeomorphic
to
.
The next corollary is originally due to Robert M. Solovay.
Corollary 6.6
The set of Turing degrees of members of
is upward closed.
Remark 6.7
Instead of Peano Arithmetic, we could have used any consistent
recursively axiomatizable theory

which is
effectively
essentially incomplete, i.e., has the property given by the
Gödel/Rosser Theorem. The required property of

is as follows.
Given a consistent recursively axiomatizable theory

extending

, we can effectively find a sentence

in the language of

which is
independent of 
, i.e.,

and

. Compare this with our notion of
productivity from part 3 of Theorem
6.3, which may be
viewed as an abstract Gödel/Rosser property for

subsets
of

.
Theorem 6.8
Let
be a nonempty recursively bounded
set. Then
is weakly complete if and only if
is Turing degree isomorphic to
.
Corollary 6.9
Let
and
be nonempty recursively bounded
sets. If
and
are weakly complete, then
is Turing degree
isomorphic to
.
We can now strengthen Corollary 6.4 as follows.
Corollary 6.10
Let
be a nonempty recursively bounded
set. If
is
weakly complete, then the set of Turing degrees of members of
is
upward closed.
sets of positive measure
Definition 7.1
The
fair coin probability measure on

is defined by
for all

and

. A set

is said to be
of positive measure if

.
In this section we prove a ``non-helping'' theorem for weak and strong
degrees of subsets of
which are of positive measure.
Lemma 7.2
Let
,
be a sequence of finite subsets of
of bounded cardinality. Put
.
Let
be of positive measure. Let
be arbitrary. If
, then
.
Lemma 7.3
Same as Lemma 7.2 with strong reducibility,
,
replaced by weak reducibility,
.
Definition 7.4
For

we say that
separates

if

for all

, and

for all

.
A nonempty

set

is said to be
separating if there exist recursively enumerable sets

such that

separates

. In this case we say that the weak degree

and
the strong degree

are
separating.
Theorem 7.5
Let
be
subsets of
. Assume that
is
separating and that
is of positive measure. Let
be the weak degrees of
respectively.
If
, then
. The same holds for strong degrees.
Corollary 7.6
Let
and
be nonempty
subsets of
. Assume
that
is of positive measure. Let
be the
weak degrees of
respectively. If
,
then
. The same holds for
strong degrees.
Corollary 7.7
Let
be a
subset of
of positive measure.
Let
be the weak degree of
. Then
. The same holds for strong degrees.
Remark 7.8
In [
48] we shall give an example of a

set

whose Turing upward closure

is of
positive measure yet does not contain any

set of positive
measure.
Definition 7.9
Following Jockusch [
25], for

we
define

and

.
Thus

is the set of

-bounded, diagonally nonrecursive
functions. Note that

is recursively bounded and

.
Remark 7.10
By Jockusch [
25, Theorem 5] each

is weakly
complete, i.e., of weak degree

. Let

be the strong degree of

. It is
well known (see also the proof of Corollary
7.6 above)
that

is strongly complete, i.e.,

in

. By Jockusch [
25, Theorem
6] we have

in

. See also Simpson [
54, Remark 3.21].
We have the following new result.
Corollary 7.11
Let
and
be
subsets of
. Assume that
is of positive measure. Let
be the strong
degrees of
respectively. For each
, if
, then
. In particular we have
.
Remark 7.12
In Corollary
7.11, we do not know whether it is
necessarily the case that

, or

for all

.
sets of random reals
In this section we exhibit a particular degree
and
note some of its degree-theoretic properties.
As in Section 7, let
denote the fair coin
probability measure on
.
Definition 8.1
An
effective null 
is a set

of
the form

where

is
a recursive sequence of

subsets of

with

for all

. A point

is said to
be
random if

for all effective null

sets

.
Remark 8.2
The notion of randomness in Definition
8.1 is due to
Martin-Løf [
39] and has been studied extensively.
It appears to be the most general and natural notion of algorithmic
randomness for infinite sequences of

's and

's. It has also
been called
Martin-Løf randomness (Li/Vitányi
[
37, Section 2.5]),
1-randomness (Kurtz
[
28], Kautz [
27]), and
the NAP
property (Kucera
[
29,
30,
31,
32,
33,
34,
35]).
It is closely related to Kolmogorov complexity (see Li/Vitányi
[
37]).
The following theorem is well known. It says that the union of all
effective null
sets is an effective null
set.
Notation 8.5
We use the following notation for shifts:

. Note
that

is a mapping of

into

.
Lemma 8.6
For all
and
,
is random if and only
if
is random.
The next lemma is an effective version of the Zero-One Law of
probability theory.
Lemma 8.7
Let
be random. Let
be
with
. Then
.
Lemma 8.8
Let
be random. Then for all
sets
, if
then
.
Theorem 8.10
Let
where
is
random
. Then
can be characterized as the unique
largest weak degree of a
set
such
that
.
Remark 8.11
Theorem
8.10 tells us that, among all weak degrees of

sets of positive measure, there exists a unique largest
degree. Simpson/Slaman [
55] and independently Terwijn
[
58] have shown that, among all strong degrees of

sets of positive measure, there is no largest or even
maximal degree.
We end this section by noting some additional properties of the
particular weak degree
which was defined in Theorem
8.10.
Theorem 8.12
Let
be the weak degree of
is
random
. Then:
-
, and
.
- For all
, if
then
.
- For all
, if
then either
or
.
- There is no separating
such that
.
Corollary 8.13
The weak degree
is meet irreducible and does not
join to
in
.
Thin
subsets of
In this section we discuss an interesting class of degrees in
,
each of which is incomparable with the particular degree
of Section 8.
We begin with some generalities concerning thin
sets.
Definition 9.1
A

set

is said to be
thin
if, for all

sets

, the set-theoretic
difference

is

.
Lemma 9.2
Let
be a recursively bounded
set. Then
is thin if
and only if all
subsets of
are trivial, i.e.,
they are of the form
for some finite set of strings
.
Theorem 9.3
Let
be a nonempty thin recursively bounded
set. Then
is isolated if and only if
is recursive. In
particular,
is perfect if and only if and only if
has no
recursive members, i.e.,
.
Lemma 9.4
Let
be a thin recursively bounded
set. Then:
- Every
subset of
is thin and recursively bounded.
- Let
be the image of
under a
recursive functional
. Then
is a thin
recursively bounded
set.
Theorem 9.5
If
is a thin recursively bounded
set, then
is
recursively homeomorphic to a thin
set
. Moreover,
is perfect if and only if
is perfect.
Remark 9.6
There is a large literature on thin perfect

subsets of

going back to Martin/Pour-El [
38]. See
Downey/Jockusch/Stob [
15,
16]
and Cholak et al [
11]. Typically, thin perfect

subsets of

are constructed by means of priority
arguments. In this sense, thin perfect

subsets of

and their weak and strong degrees are artificial or
unnatural. In particular, thin perfect

subsets of

have been used by Binns/Simpson [
6] to
embed countable distributive lattices into

and

.
Remark 9.7
Let

where

is any nonempty thin perfect
recursively bounded

set. Obviously
