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11institutetext: University of Hawai‘i at Mānoa, Honolulu HI 96822, U.S.A.,
11email: [email protected], [email protected],
WWW home page: http://math.hawaii.edu/wordpress/bjoern/

KL-randomness and effective dimension under strong reducibility

Bjørn Kjos-Hanssen This work was partially supported by a grant from the Simons Foundation (#704836 to Bjørn Kjos-Hanssen).11 0000-0002-1825-0097    David J. Webb 11 0000-0002-5031-7669
(January 2021)
Abstract

We show that the (truth-table) Medvedev degree KLR of Kolmogorov–Loveland randomness coincides with that of Martin-Löf randomness, MLR, answering a question of Miyabe. Next, an analogue of complex packing dimension is studied which gives rise to a set of weak truth-table Medvedev degrees isomorphic to the Turing degrees.

Keywords:
algorithmic randomness, effective dimension, Medvedev reducibility

1 Introduction

Computability theory is concerned with the relative computability of reals, and of collections of reals. The latter can be compared by various means, including Medvedev and Muchnik reducibility. Among the central collections considered are those of completions of Peano Arithmetic, Turing complete reals, Cohen generic reals, random reals, and various weakenings of randomness such as reals of positive effective Hausdorff dimension.

Perhaps the most famous open problem in algorithmic randomness [2, 9] is whether Kolmogorov–Loveland randomness is equal to Martin-Löf randomness. Here we show that at least they are Medvedev equivalent.

Randomness extraction in computability theory concerns whether reals that are close (in some metric) to randoms can compute random reals. A recent example is [4]. That paper does for Hausdorff dimension what was done for a notion intermediate between packing dimension and Hausdorff dimension in [3]. That intermediate notion, complex packing dimension, has a natural dual which we introduce in this article. Whereas our result on KL-randomness is positive, we establish some negative (non-reduction) results for our new inescapable dimension and for relativized complex packing dimension (in particular Theorem 3.11). These results are summarized in Figure 1.

XMLR\textstyle{X\in\mathrm{MLR}\ignorespaces\ignorespaces\ignorespaces\ignorespaces}XKLR\textstyle{X\in\mathrm{KLR}\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces}Theorem 1.2dimH(X)=1\textstyle{\dim_{H}(X)=1\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces}dimisΔ10(X)=1\textstyle{\dim_{is\Delta^{0}_{1}}(X)=1\ignorespaces\ignorespaces\ignorespaces\ignorespaces}dimsiΔ10(X)=1\textstyle{\dim_{si\Delta^{0}_{1}}(X)=1\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces}dimsiΔ10(A)(X)=1\textstyle{\dim_{si\Delta^{0}_{1}(A)}(X)=1\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces\ignorespaces}Theorem 3.11dimsiΔ10(B)(X)=1\textstyle{\dim_{si\Delta^{0}_{1}(B)}(X)=1\ignorespaces\ignorespaces\ignorespaces\ignorespaces}dimp(X)=1\textstyle{\dim_{p}(X)=1}
Figure 1: Truth-table Medvedev degrees of mass problems associated with randomness and dimension. Here 𝒞𝒟\mathcal{C}\to\mathcal{D} means 𝒞s𝒟\mathcal{C}\geq_{s}\mathcal{D}, dotted arrow means 𝒞s𝒟\mathcal{C}\not\geq_{s}\mathcal{D} and we assume ATBA\not\leq_{T}B.

Let CR, SR, KLR, and MLR be the classes of computably random, Schnorr random, Kolmogorov-Loveland random, and Martin-Löf random reals, respectively. For basic definitions from algorithmic randoness, the reader may consult two recent monographs [2, 9]. Let s\leq_{s} denote the uniform (strong) reducibility of mass problems known as Medvedev reducibility, and let w\leq_{w} denote the non-uniform (weak) version known as Muchnik reducibility. It was shown by Nies, Stephan and Terwijn [10] that CRwSR\mathrm{CR}\leq_{w}\mathrm{SR}. Miyabe [8] obtains an interesting counterpoint by showing as his main theorem that CRsSR\mathrm{CR}\not\leq_{s}\mathrm{SR}.

Theorem 1.1 ([7])

Given a KL-random set A=A0A1A=A_{0}\oplus A_{1}, at least one of A0A_{0}, A1A_{1} is ML-random.

As a corollary, MLRwKLR\mathrm{MLR}\leq_{w}\mathrm{KLR}. Miyabe [8] posed one open problem — is MLRsKLR\mathrm{MLR}\leq_{s}\mathrm{KLR}? — which we answer in Theorem 1.2.

Let K(σ)K(\sigma) denote the prefix-free Kolmogorov complexity of a string σ2<ω\sigma\in 2^{<\omega}, and let Ks(σ)K_{s}(\sigma) be a computable nonincreasing approximation of K(σ)K(\sigma) in stages sωs\in\omega. The prefix of AA of length nn is denoted AnA\upharpoonright n.

Theorem 1.2

MLRsKLR\mathrm{MLR}\leq_{s}\mathrm{KLR}.

Proof

Given a KL-random set A=A0A1A=A_{0}\oplus A_{1}, we output bits of either A0A_{0} or A1A_{1}, switching whenever we notice that the smallest possible randomness deficiency (cc such that n(K(Ain)nc)\forall n\,(K(A_{i}\upharpoonright n)\geq n-c)) increases.

This constant cc depends on ss and changes at stage s+1s+1 if

(ns+1)Ks+1(Ain)<ncs.(\exists n\leq s+1)\quad K_{s+1}(A_{i}\upharpoonright n)<n-c_{s}.

By Theorem 1.1, one of A0A_{0}, A1A_{1} is ML-random, hence switching will occur only finitely often. Thus our output will have an infinite tail that is ML-random, and hence be itself ML-random.∎

Inspection of the proof of Theorem 1.2 shows that we do not need the full power of Turing reductions, but have a truth-table reduction with use φ(n)2n\varphi(n)\leq 2n.

2 Complex packing dimension and its analogue

Let K(σ)K(\sigma) denote the prefix-free Kolmogorov complexity of a string σ2<ω\sigma\in 2^{<\omega}. The prefix of AA of length nn is denoted AnA\upharpoonright n.

Viewed in terms of complexity [1, 6], the Hausdorff and packing dimensions are dual to one another:

Definition 1

Let A2ωA\in 2^{\omega}. The effective Hausdorff dimension of AA is defined by

dimH(A)=supminfnmK(An)n.\dim_{H}(A)=\sup_{m\in\mathbb{N}}\inf_{n\geq m}\dfrac{K(A\upharpoonright n)}{n}.

The effective packing dimension of AA is

dimp(A)=infmsupnmK(An)n.\dim_{p}(A)=\inf_{m\in\mathbb{N}}\sup_{n\geq m}\dfrac{K(A\upharpoonright n)}{n}.

Another notion of dimension was defined in previous work by Kjos-Hanssen and Freer [3], which we review here. Let 𝔇\mathfrak{D} denote the collection of all infinite Δ10\Delta^{0}_{1} elements of 2ω2^{\omega}. The complex packing dimension is defined as

Definition 2

dimcp(A)=supN𝔇infnNK(An)n\displaystyle\dim_{cp}(A)=\sup_{N\in\mathfrak{D}}\inf_{n\in N}\dfrac{K(A\upharpoonright n)}{n}.

This leads naturally to a new notion, the dual of complex packing dimension:

Definition 3

dimi(A)=infN𝔇supnNK(An)n.\displaystyle\dim_{i}(A)=\inf_{N\in\mathfrak{D}}\sup_{n\in N}\dfrac{K(A\upharpoonright n)}{n}.

This is the inescapable dimension of AA, so named because if dimi(A)=α\dim_{i}(A)=\alpha, every infinite computable collection of prefixes of AA must contain prefixes with relative complexity arbitrarily close to α\alpha. For such a real, there is no (computable) escape from high complexity prefixes.

As Freer and Kjos-Hanssen show in [3], for any A2ωA\in 2^{\omega},

0dimH(A)dimcp(A)dimp(A)1.0\leq\dim_{H}(A)\leq\dim_{cp}(A)\leq\dim_{p}(A)\leq 1.

The expected analogous result also holds:

Theorem 2.1

For any A2ωA\in 2^{\omega}, 0dimH(A)dimi(A)dimp(A)10\leq\dim_{H}(A)\leq\dim_{i}(A)\leq\dim_{p}(A)\leq 1.

Proof

As the sets [n,)[n,\infty) are computable subsets of \mathbb{N}, dimi(A)dimp(A)\dim_{i}(A)\leq\dim_{p}(A). For the second inequality, notice that for all mm\in\mathbb{N} and all NΔ10N\in\Delta^{0}_{1},

infn[m,)K(An)n\displaystyle\inf_{n\in[m,\infty)}\dfrac{K(A\upharpoonright n)}{n} \displaystyle\leq infnN[m,)K(An)n\displaystyle\inf_{n\in N\cap[m,\infty)}\dfrac{K(A\upharpoonright n)}{n}
\displaystyle\leq supnN[m,)K(An)nsupnNK(An)n.\displaystyle\sup_{n\in N\cap[m,\infty)}\dfrac{K(A\upharpoonright n)}{n}\leq\sup_{n\in N}\dfrac{K(A\upharpoonright n)}{n}.\ \squareforqed

Unexpectedly, this is the best one can do. As we will see in the next section, while the Hausdorff dimension of a real is always lower than its packing dimension, any permutation is possible for the complex packing and inescapable dimensions of a real.

3 Incomparability for inescapable dimension

We begin with a proof that the inescapable and complex packing dimensions are incomparable in the following sense: dimcp(A)dimcp(B)\dim_{cp}(A)\leq\dim_{cp}(B) does not imply dimi(A)dimi(B)\dim_{i}(A)\leq\dim_{i}(B), nor vice versa. In fact we show a stronger statement:

Theorem 3.1

There exist AA and BB in 2ω2^{\omega} such that dimcp(A)<dimcp(B)\dim_{cp}(A)<\dim_{cp}(B), but dimi(B)<dimi(A)\dim_{i}(B)<\dim_{i}(A).

Recall that a real AA meets a set of strings SS if there is some σS\sigma\in S such that σ\sigma is a prefix of AA. Moreover, AA is weakly 2-generic if for each dense Σ20\Sigma^{0}_{2} set of strings SS, AA meets SS [5].

For a real AA, let us write A[m,n]A[m,n] to denote the string A(m)A(m+1)A(n1)A(m)A(m+1)\dots A(n-1). For two functions f(n),g(n)f(n),g(n) we write f(n)+g(n)f(n)\leq^{+}g(n) to denote cnf(n)g(n)+c\exists c\forall n\,f(n)\leq g(n)+c. We write f(n)=𝒪(g(n))f(n)=\mathcal{O}(g(n)) to denote Mn0n>n0f(n)Mg(n)\exists M\exists n_{0}\forall n>n_{0}\,f(n)\leq Mg(n). It will also be useful to have the following theorem of Schnorr at our disposal:

Theorem 3.2

AA is Martin-Löf random iff n+K(An)n\leq^{+}K(A\upharpoonright n).

Finally, for a real AA and nωn\in\omega we use the indicator function 1A1_{A} defined by

1A(n)={1if nA,0otherwise.1_{A}(n)=\begin{cases}1&\text{if }n\in A,\\ 0&\text{otherwise.}\end{cases}
Proof (of Theorem 3.1)

Let AA be a weakly 2-generic real, and let RR be a Martin-Löf random real. Let sk=2k2s_{k}=2^{k^{2}}, kn=max{kskn}k_{n}=\max\{k\mid s_{k}\leq n\}, C=(01)ωC=(01)^{\omega}. Define

B(n)=R(nskn)1C(kn).B(n)=R\left(n-s_{k_{n}}\right)\cdot 1_{C}(k_{n}).

Unpacking this slightly, this is

B(n)={R(nsk)if skn<sk+1 for some even k,0otherwise.B(n)=\begin{cases}R\left(n-s_{k}\right)&\text{if }\ s_{k}\leq n<s_{k+1}\text{ for some even }k,\\ 0&\text{otherwise.}\end{cases}

In this proof, let us say that an RR-segment is a string of the form B[s2m,s2m+1)B\upharpoonright[s_{2m},s_{2m+1}) for some mm, and say that a 0-segment is a string of the form B[s2m+1,s2m+2)B\upharpoonright[s_{2m+1},s_{2m+2}) for some mm. These are named so that a 0-segment consists of zeros, and an RR-segment consists of random bits. Notice that by construction, each such segment is much longer than the combined length of all previous segments. This guarantees certain complexity bounds at the segments’ right endpoints. For instance, BB has high complexity at the end of RR-segments: for any even kk\in\mathbb{N},

sk+1sk\displaystyle s_{k+1}-s_{k} +\displaystyle\leq^{+} K(B[sk,sk+1])\displaystyle K\left(B\left[s_{k},s_{k+1}\right]\right)
+\displaystyle\leq^{+} K(Bsk)+K(Bsk+1)+2sk+K(Bsk+1).\displaystyle K(B\upharpoonright s_{k})+K(B\upharpoonright s_{k+1})\leq^{+}2s_{k}+K(B\upharpoonright s_{k+1}).

The first inequality holds by Theorem 3.2 because B[sk,sk+1]=R(sk+1sk)B\left[s_{k},s_{k+1}\right]=R\upharpoonright(s_{k+1}-s_{k}). The second (rather weak) inequality holds because from descriptions of BskB\upharpoonright s_{k} and Bsk+1B\upharpoonright s_{k+1} we can recover B[sk,sk+1]B[s_{k},s_{k+1}]. Finally, K(σ)+2|σ|K(\sigma)\leq^{+}2\lvert\sigma\rvert is a property of prefix-free Kolmogorov complexity KK. Combining and dividing by sk+1s_{k+1} gives

sk+13sk\displaystyle s_{k+1}-3s_{k} +K(Bsk+1)\displaystyle\leq^{+}K(B\upharpoonright s_{k+1})
132(2k+1)\displaystyle 1-3\cdot 2^{-(2k+1)} K(Bsk+1)sk+1+𝒪(2(k+1)2)as k.\displaystyle\leq\dfrac{K(B\upharpoonright s_{k+1})}{s_{k+1}}+\mathcal{O}\left(2^{-(k+1)^{2}}\right)\quad\text{as $k\to\infty$.} (1)

Dually, the right endpoints of 0-segments have low complexity: for odd kk\in\mathbb{N},

K(Bsk+1)\displaystyle K(B\upharpoonright s_{k+1}) +K(Bsk)+K(B[sk,sk+1])+2sk+2log(sk+1sk).\displaystyle\leq^{+}K(B\upharpoonright s_{k})+K(B[s_{k},s_{k+1}])\leq^{+}2s_{k}+2\log(s_{k+1}-s_{k}).

The first inequality is again the weak bound that Bsk+1B\upharpoonright s_{k+1} can be recovered from descriptions of BskB\upharpoonright s_{k} and B[sk,sk+1]B[s_{k},s_{k+1}]. For the second, we apply the 2|σ|2\lvert\sigma\rvert prefix-free complexity bound to BskB\upharpoonright s_{k}, but also notice that since B[sk,sk+1]=0sk+1skB[s_{k},s_{k+1}]=0^{s_{k+1}-s_{k}}, it can be recovered effectively from a code for its length. Combining and dividing by sk+1s_{k+1}, we have

K(Bsk+1)\displaystyle K(B\upharpoonright s_{k+1}) +2sk+2(k+1)2\displaystyle\leq^{+}2s_{k}+2(k+1)^{2}
K(Bsk+1)sk+1\displaystyle\dfrac{K(B\upharpoonright s_{k+1})}{s_{k+1}} 2(2k+1)+𝒪(2(k+1)2)as k.\displaystyle\leq 2^{-(2k+1)}+\mathcal{O}\left(2^{-(k+1)^{2}}\right)\quad\text{as $k\to\infty$.} (2)

Now we can examine the dimensions of AA and BB.

Claim 1: dimcp(B)=1\dim_{cp}(B)=1.
Let RnR_{n} be the set of right endpoints of RR-segments of BB, except for the first nn of them — that is, Rn={s2k+1}k=nR_{n}=\{s_{2k+1}\}_{k=n}^{\infty}. Then the collection of these RnR_{n} is a subfamily of 𝔇\mathfrak{D}, so that a supremum over 𝔇\mathfrak{D} will be at least the supremum over this family.

supN𝔇infnNK(Bn)n\displaystyle\sup_{N\in\mathfrak{D}}\inf_{n\in N}\dfrac{K(B\upharpoonright n)}{n} \displaystyle\geq supninfsRnK(Bs)s\displaystyle\sup_{n\in\mathbb{N}}\inf_{s\in R_{n}}\dfrac{K(B\upharpoonright s)}{s}
supninfsRn132(2s+1)\displaystyle\geq\sup_{n\in\mathbb{N}}\inf_{s\in R_{n}}1-3\cdot 2^{-(2s+1)} =\displaystyle= supm132(2m+1)=1\displaystyle\sup_{m\in\mathbb{N}}1-3\cdot 2^{-(2m+1)}=1

by (3).

Claim 2: dimi(B)=0\dim_{i}(B)=0.
Let ZnZ_{n} be the set of right endpoints of 0-segments of BB, except for the first nn of them: Zn={s2k}k=nZ_{n}=\{s_{2k}\}_{k=n}^{\infty}. Similarly to Claim 1, we obtain

infN𝔇supnNK(Bn)n\displaystyle\inf_{N\in\mathfrak{D}}\sup_{n\in N}\dfrac{K(B\upharpoonright n)}{n} \displaystyle\leq infnsupsZnK(Bs)s\displaystyle\inf_{n\in\mathbb{N}}\sup_{s\in Z_{n}}\dfrac{K(B\upharpoonright s)}{s}
infnsupsZn2(2s+1)\displaystyle\leq\inf_{n\in\mathbb{N}}\sup_{s\in Z_{n}}2^{-(2s+1)} =\displaystyle= infm2(2m+1)=0\displaystyle\inf_{m\in\mathbb{N}}2^{-(2m+1)}=0

by (3).

Claim 3: dimcp(A)=0\dim_{cp}(A)=0.
For each natural kk and NN in 𝔇\mathfrak{D}, the following sets are dense Σ10\Sigma^{0}_{1}:

{σ2<ω:|σ|N and (s)Ks(σ)<|σ|/k]}.\left\{\sigma\in 2^{<\omega}:\lvert\sigma\rvert\in N\text{ and }(\exists s)\ K_{s}(\sigma)<\lvert\sigma\rvert/k]\right\}.

As AA is weakly 2-generic, it meets all of them. Hence

supN𝔇infmNK(σm)m=0.\sup_{N\in\mathfrak{D}}\inf_{m\in N}\dfrac{K(\sigma\upharpoonright m)}{m}=0.

Claim 4: dimi(A)=1\dim_{i}(A)=1.
For each natural kk and NN in 𝔇\mathfrak{D},

{σ2<ω:|σ|N and (s)Ks(σ)>|σ|(11/k)}\left\{\sigma\in 2^{<\omega}:\lvert\sigma\rvert\in N\text{ and }(\forall s)\ K_{s}(\sigma)>\lvert\sigma\rvert(1-1/k)\right\}

is a dense Σ20\Sigma^{0}_{2} set. As AA is weakly 2-generic, it meets all of these sets. Hence

infN𝔇supmNK(Am)m=1.\inf_{N\in\mathfrak{D}}\sup_{m\in N}\dfrac{K(A\upharpoonright m)}{m}=1.\ \squareforqed

We say that AA is finite-to-one reducible to BB if there is a total computable function f:ωωf:\omega\to\omega such that the preimage of each nωn\in\omega is finite and for all nn, nAf(n)Bn\in A\iff f(n)\in B.

Definition 4

Let 𝔅\mathfrak{B} be a class of infinite sets downward closed under finite-to-one reducibility. For A2ωA\in 2^{\omega}, we define

dimis𝔅(A)=infN𝔅supnNK(An)nanddimsi𝔅(A)=supN𝔅infnNK(An)n.\dim_{is\mathfrak{B}}(A)=\inf_{N\in\mathfrak{B}}\sup_{n\in N}\dfrac{K(A\upharpoonright n)}{n}\quad\text{and}\quad\dim_{si\mathfrak{B}}(A)=\sup_{N\in\mathfrak{B}}\inf_{n\in N}\dfrac{K(A\upharpoonright n)}{n}.

Notice that for any oracle XX, the classes of infinite sets that are Δn0(X),Σn0(X)\Delta^{0}_{n}(X),\Sigma^{0}_{n}(X) or Πn0(X)\Pi^{0}_{n}(X) are downward closed under finite-to-one reducibility, and so give rise to notions of dimension of this form. We will label these 𝔇n(X)\mathfrak{D}_{n}(X), 𝔖n(X)\mathfrak{S}_{n}(X), and 𝔓n(X)\mathfrak{P}_{n}(X) respectively, leaving off XX when XX is computable. Interestingly, for fixed nn, the first two give the same notion of dimension.

Theorem 3.3

For all A2ωA\in 2^{\omega} and nn\in\mathbb{N}, dimisΣn0(A)=dimisΔn0(A)\dim_{is\Sigma^{0}_{n}}(A)=\dim_{is\Delta^{0}_{n}}(A).

Proof

We prove the unrelativized version of the statement, n=1n=1.
[\leq] As Δ10Σ10\Delta^{0}_{1}\subseteq\Sigma^{0}_{1}, this direction is trivial.
[\geq] As every infinite Σ10\Sigma^{0}_{1} set NN contains an infinite Δ10\Delta^{0}_{1} set NN^{\prime}, we have

dimisΣ10(A)=infN𝔖1supnNK(An)n\displaystyle\dim_{is\Sigma^{0}_{1}}(A)=\inf_{N\in\mathfrak{S}_{1}}\sup_{n\in N}\dfrac{K(A\upharpoonright n)}{n} infN𝔖1supnNK(An)n\displaystyle\geq\inf_{N\in\mathfrak{S}_{1}}\sup_{n\in N^{\prime}}\dfrac{K(A\upharpoonright n)}{n}
infN𝔇1supnNK(An)n=dimisΔ10(A).\displaystyle\geq\inf_{N\in\mathfrak{D}_{1}}\sup_{n\in N}\dfrac{K(A\upharpoonright n)}{n}=\dim_{is\Delta^{0}_{1}}(A).\squareforqed

By a similar analysis, the analogous result for sisi dimensions is also true.

Theorem 3.4

For all A2ωA\in 2^{\omega} and nn\in\mathbb{N}, dimsiΣn0(A)=dimsiΔn0(A)\dim_{si\Sigma^{0}_{n}}(A)=\dim_{si\Delta^{0}_{n}}(A).

What about the Πn0\Pi^{0}_{n} dimensions? Unlike the Σ10\Sigma^{0}_{1} case, these do not collapse to any other dimension. Two lemmas will be useful in proving this. The first (which was implicit in Claims 1 and 2 of Theorem 2.1) will allow us to show that an sisi-dimension of a real is high by demonstrating a sequence that witnesses this. The second is a generalization of the segment technique, forcing a dimension to be 0 by alternating 0- and RR-segments in a more intricate way, according to the prescriptions of a certain real. The constructions below proceed by selecting a real that will guarantee that one dimension is 0 while leaving room to find a witnessing sequence for another.

Lemma 1 (Sequence Lemma)

Let 𝔅\mathfrak{B} be a class of infinite sets downward closed under finite-to-one reducibility, and let N={nkkω}𝔅N=\{n_{k}\mid k\in\omega\}\in\mathfrak{B}.

  1. 1.

    If limkK(Xnk)nk=1\displaystyle\lim_{k\rightarrow\infty}\dfrac{K(X\upharpoonright n_{k})}{n_{k}}=1, then dimsi𝔅(X)=1\dim_{si\mathfrak{B}}(X)=1.

  2. 2.

    If limkK(Xnk)nk=0\displaystyle\lim_{k\rightarrow\infty}\dfrac{K(X\upharpoonright n_{k})}{n_{k}}=0, then dimis𝔅(X)=0\dim_{is\mathfrak{B}}(X)=0.

Proof

We prove (1); (2) is similar.

Form the infinite family of sets {Nm}\{N_{m}\} defined by Nm={nkkm}N_{m}=\{n_{k}\mid k\geq m\}. From the definition of the limit, for any ε>0\varepsilon>0 there is an ll such that

infNlK(Xnk)nk>1ε.\inf_{N_{l}}\dfrac{K(X\upharpoonright n_{k})}{n_{k}}>1-\varepsilon.

As ε\varepsilon was arbitrary,

supminfNmK(Xnm)nm=1.\sup_{m}\inf_{N_{m}}\dfrac{K(X\upharpoonright n_{m})}{n_{m}}=1.

Thus as 𝔅\mathfrak{B} is closed under finite-to-one reduction, the NmN_{m} form a subfamily of 𝔅\mathfrak{B}, so that supN𝔅infnNK(Xn)/n=1\sup_{N\in\mathfrak{B}}\inf_{n\in N}K(X\upharpoonright n)/n=1.∎

Recall that an infinite real AA is said to be immune to a class 𝔅\mathfrak{B} if there is no infinite member B𝔅B\in\mathfrak{B} such that BAB\subseteq A as sets, or co-immune to a class 𝔅\mathfrak{B} if its complement is immune to 𝔅\mathfrak{B}. We will sometimes refer to these properties as 𝔅\mathfrak{B}-immunity or 𝔅\mathfrak{B}-co-immunity, respectively.

Lemma 2 (Double Segment Lemma)

Let X02ωX_{0}\in 2^{\omega} be such that X0X_{0} is 𝔅\mathfrak{B}-immune for a class 𝔅\mathfrak{B} of infinite sets downward closed under finite-to-one reducibility. Set X=X0X0X=X_{0}\oplus X_{0}. Let sk=2k2s_{k}=2^{k^{2}}, and kn=max{odd kskn}k_{n}=\max\{\text{odd }k\mid s_{k}\leq n\}. Let AA be an arbitrary real and let RR be Martin-Löf random.

  1. 1.

    If B=A(nskn)1X(kn)B=A\left(n-s_{k_{n}}\right)\cdot 1_{X}(k_{n}), then dimsi𝔅(B)=0\dim_{si\mathfrak{B}}(B)=0.

  2. 2.

    If B=R(nskn)1X¯(kn)B=R\left(n-s_{k_{n}}\right)\cdot 1_{\overline{X}}(k_{n}), then dimis𝔅(B)=1\dim_{is\mathfrak{B}}(B)=1.

Again, we will give a detailed proof of only the dimsi𝔅\dim_{si\mathfrak{B}} result (though the necessary changes for dimis𝔅\dim_{is\mathfrak{B}} are detailed below). Unpacking the definition of BB,

B(n)={A(nsk)if knX0otherwise.B(n)=\begin{cases}A\left(n-s_{k}\right)&\text{if $k_{n}\in X$}\\ 0&\text{otherwise.}\end{cases}

BB is here built out of segments of the form B[skn,skn+2]B\left[s_{k_{n}},s_{k_{n}+2}\right] for odd kk. Here a segment is a 0-segment if knXk_{n}\not\in X, or an AA-segment if knXk_{n}\in X, which by definition is a prefix of AA. These segments are now placed in a more intricate order according to XX, with a value nn being contained in a 0-segment if X(kn)=0X(k_{n})=0, and in an AA-segment if X(kn)=1X(k_{n})=1. With some care, this will allow us to leverage the 𝔅\mathfrak{B}-immunity of X0X_{0} to perform the desired complexity calculations.

Specifically, we want to show that for any N𝔅N\in\mathfrak{B}, infNK(Bn)/n=0\inf_{N}K(B\upharpoonright n)/n=0. It is tempting to place the segments according to X0X_{0} and invoke its 𝔅\mathfrak{B}-immunity to show that for any N𝔅N\in\mathfrak{B}, there are infinitely many nNn\in N such that nn is in a 0-segment, and argue that complexity will be low there. The problem is that we have no control over where in the 0-segment nn falls. Consider in this case the start of any segment following an AA-segment: n=sknn=s_{k_{n}} for kn1X0k_{n}-1\in X_{0} and knX0k_{n}\in X_{0}. We can break AA and BB into sections to compute

K(An)\displaystyle K(A\upharpoonright n) +K(A(nskn1))+K(A[nskn1,n])\displaystyle\leq^{+}K(A\upharpoonright(n-s_{k_{n}-1}))+K(A[n-s_{k_{n}-1},n])
=K(B[skn1,n])+K(A[nskn1,n])\displaystyle=K(B[s_{k_{n}-1},n])+K(A[n-s_{k_{n}-1},n]) (kn1X0k_{n}-1\in X_{0})
+K(Bn)+K(Bskn1)+K(A[nskn1,n])\displaystyle\leq^{+}K(B\upharpoonright n)+K(B\upharpoonright s_{k_{n}-1})+K(A[n-s_{k_{n}-1},n])
K(An)\displaystyle K(A\upharpoonright n) +K(Bn)+4skn1\displaystyle\leq^{+}K(B\upharpoonright n)+4s_{k_{n}-1} (K(σ)+2|σ|K(\sigma)\leq^{+}2|\sigma|)

Even if nn is the start of a 0-segment, if K(An)K(A\upharpoonright n) is high, K(Bn)K(B\upharpoonright n) may not be as low as needed for the proof. Our definition of XX avoids this problem:

Proof (of Theorem 2)

Suppose for the sake of contradiction that for some N𝔅N\in\mathfrak{B}, there are only finitely many nNn\in N with kn,kn1X¯k_{n},k_{n}-1\in\overline{X}, i.e., that are in a 0-segment immediately following another 0-segment. Removing these finitely many counterexamples we are left with a set N𝔅N^{\prime}\in\mathfrak{B} such that for all nNn\in N^{\prime}, ¬[(knX)(kn1X)].\lnot[(k_{n}\not\in X)\land(k_{n}-1\not\in X)]. As knk_{n} is odd, the definition of XX gives that kn/2X0\lfloor k_{n}/2\rfloor\in X_{0}. By a finite-to-one reduction from NN^{\prime}, the infinite set {kn/2}nN\{\lfloor k_{n}/2\rfloor\}_{n\in N^{\prime}} is a member of 𝔅\mathfrak{B} and is contained in X0X_{0} - but X0¯\overline{X_{0}} is immune to such sets.

Instead it must be the case that there are infinitely many nNn\in N in a 0-segment following a 0-segment, where the complexity is

K(Bn)\displaystyle K(B\upharpoonright n) +K(Bsnk1)+K(B[snk1,n])\displaystyle\leq^{+}K\left(B\upharpoonright s_{n_{k-1}}\right)+K\left(B\left[s_{n_{k-1}},n\right]\right)
+2snk1+2log(nsnk1).\displaystyle\leq^{+}2\cdot s_{n_{k-1}}+2\log\left(n-s_{n_{k-1}}\right).

Here the second inequality follows from the usual 2|σ|2\lvert\sigma\rvert bound and the fact that B[snk1,n]B\left[s_{n_{k-1}},n\right] contains only 0s. As 2kn2n2^{k_{n}^{2}}\leq n, we can divide by nn to get

K(Bn)n+2kn22kn2kn2+2log(n)n=22kn+2log(n)n.\displaystyle\dfrac{K(B\upharpoonright n)}{n}\leq^{+}\dfrac{2^{k_{n}^{2}-2k_{n}}}{2^{k_{n}^{2}}}+\dfrac{2\log(n)}{n}=2^{-2k_{n}}+\dfrac{2\log(n)}{n}.

As there are infinitely many of these nn, it must be that infnNK(Bn)/n=0\inf_{n\in N}K(B\upharpoonright n)/n=0. This holds for every real NN with property 𝔅\mathfrak{B}, so taking a supremum gives the result.

The dimis𝔅\dim_{is\mathfrak{B}} version concerns reals BB constructed in a slightly different way. Here, the same argument now shows there are infinitely many nNn\in N in an RR-segment following an RR-segment. At these locations, the complexity K(Bn)K(B\upharpoonright n) can be shown to be high enough that supNK(Bn)/n=1\sup_{N}K(B\upharpoonright n)/n=1, as desired. ∎

With these lemmas in hand, we are ready to prove the following theorem:

Theorem 3.5

For all natural nn there is a set AA with dimsiΠn0(A)=1\dim_{si\Pi^{0}_{n}}(A)=1 and dimsiΔn0(A)=0\dim_{si\Delta^{0}_{n}}(A)=0.

Proof

We prove the n=1n=1 case, as the proofs for higher nn are analogous.

Let S0S_{0} be a co-c.e. immune set, and let RR be Martin-Löf random. Set S=S0S0S=S_{0}\oplus S_{0}, and define kn=max{odd k2k2n}k_{n}=\max\{\text{odd }k\mid 2^{k^{2}}\leq n\}. To build AA out of 0-segments and RR-segments, define A(n)=R(n2kn2)1S(kn)A(n)=R\left(n-2^{k_{n}^{2}}\right)\cdot 1_{S}(k_{n}).

As S0S_{0} is Π10\Pi^{0}_{1}, so is SS. Thus the set of right endpoints of RR-segments,M={2k2k is odd and k1S}M=\left\{2^{k^{2}}\mid k\text{ is odd and }k-1\in S\right\} is also Π10\Pi^{0}_{1}. By construction limmMK(Am)/m=1\lim_{m\in M}K(A\upharpoonright m)/m=1 and thus the Sequence Lemma 1 gives that dimsiΠ10(A)=1\dim_{si\Pi^{0}_{1}}(A)=1.

As the complement of a simple set is immune, the Double Segment Lemma 2 shows that dimsiΔ10(A)=0\dim_{si\Delta^{0}_{1}}(A)=0.∎

The proof of analogous result for the isis-dimensions is similar, using the same S0S_{0} and SS, and the real defined by B(n)=R(n2kn2)1S¯(kn)B(n)=R\left(n-2^{k_{n}^{2}}\right)\cdot 1_{\overline{S}}(k_{n}).

Theorem 3.6

For all n1n\geq 1 there exists a set BB with dimisΠn0(B)=1\dim_{is\Pi^{0}_{n}}(B)=1 and dimisΔn0(B)=0\dim_{is\Delta^{0}_{n}}(B)=0.

It remains to show that the Δn+10\Delta^{0}_{n+1} and Πn0\Pi^{0}_{n} dimensions are all distinct. We can use the above lemmas for this, so the only difficulty is finding sets of the appropriate arithmetic complexity with the relevant immunity properties.

Lemma 3

For all n1n\geq 1, there is an infinite Δn+10\Delta^{0}_{n+1} set SS that is Πn0\Pi^{0}_{n}-immune.

Proof

We prove the unrelativized version, n=1n=1. Let CC be a Δ20\Delta^{0}_{2} cohesive set that is not co-c.e, i.e., for all ee either WeCW_{e}\cap C or We¯C\overline{W_{e}}\cap C is finite. As C¯\overline{C} is not c.e. it cannot finitely differ from any WeW_{e}, so for all ee, WeC¯=WeCW_{e}\setminus\overline{C}=W_{e}\cap C is infinite. Hence if We¯C\overline{W_{e}}\subseteq C, then by cohesiveness, We¯C=We¯\overline{W_{e}}\cap C=\overline{W_{e}} is finite.∎

Theorem 3.7

For all n1n\geq 1 there exists a set AA with dimsiΔn+10(A)=1\dim_{si\Delta^{0}_{n+1}}(A)=1 and dimsiΠn0(A)=0\dim_{si\Pi^{0}_{n}}(A)=0.

Proof

This is exactly like the proof of Theorem 3.5, but S0S_{0} is now the Π10\Pi^{0}_{1}-immune set guaranteed by Lemma 3.∎

Again, the analogous result for isis-dimensions is similar:

Theorem 3.8

For all n1n\geq 1 there exists a set BB with dimisΠn0(B)=1\dim_{is\Pi^{0}_{n}}(B)=1 and dimisΔn+10(B)=0\dim_{is\Delta^{0}_{n+1}}(B)=0.

After asking questions about the arithmetic hierarchy, it is natural to turn our attention to the Turing degrees. As the familiar notion of BB-immunity for an oracle is exactly Δ10(B)\Delta^{0}_{1}(B)-immunity for a class, we have access to the usual lemmas. We shall embed the Turing degrees into the sisi-Δ10(A)\Delta^{0}_{1}(A) dimensions (and dually, isis-Δ10(A)\Delta^{0}_{1}(A)). First, a helpful lemma:

Lemma 4 (Immunity Lemma)

If ATBA\nleq_{T}B, there is an STAS\leq_{T}A such that SS is BB-immune.

Proof

Let SS be the set of finite prefixes of AA. If SS contains a BB-computable infinite subset CC, then we can recover AA from CC, but then ATCTBA\leq_{T}C\leq_{T}B.∎

Theorem 3.9 (sisi-Δ10\Delta^{0}_{1} Embedding Theorem)

Let A,B2ωA,B\in 2^{\omega}. Then ATBA\leq_{T}B iff for all X2ω,dimsiΔ10(A)(X)dimsiΔ10(B)(X)X\in 2^{\omega},\dim_{si\Delta^{0}_{1}(A)}(X)\leq\dim_{si\Delta^{0}_{1}(B)}(X).

Proof

[\Rightarrow] Immediate, as Δ10(A)Δ10(B)\Delta^{0}_{1}(A)\subseteq\Delta^{0}_{1}(B).
[\Leftarrow] This is again exactly like the proof of Theorem 3.5, now using the set guaranteed by the Immunity Lemma 4 as S0S_{0}.∎

The result for isis-dimensions is again similar:

Theorem 3.10 (sisi-Δ10\Delta^{0}_{1} Embedding Theorem)

Let A,B2ωA,B\in 2^{\omega}. Then ATBA\leq_{T}B iff for all X2ω,dimisΔ10(A)(X)dimisΔ10(B)(X)X\in 2^{\omega},\dim_{is\Delta^{0}_{1}(A)}(X)\geq\dim_{is\Delta^{0}_{1}(B)}(X).

We can push this a little further by considering weak truth table reductions:

Definition 5

AA is weak truth table reducible to BB (AwttBA\leq_{wtt}B) if there exists a computable function ff and an oracle machine Φ\Phi such that ΦB=A\Phi^{B}=A, and the use of ΦX(n)\Phi^{X}(n) is bounded by f(n)f(n) for all nn (ΦX(n)\Phi^{X}(n) is not guaranteed to halt).

Theorem 3.11

If ATBA\not\leq_{T}B, then for all wtt-reductions Φ\Phi there exists an XX such that dimsiΔ10(A)(X)=1\dim_{si\Delta^{0}_{1}(A)}(X)=1 and, either ΦX\Phi^{X} is not total or dimsiΔ10(B)(ΦX)=0\dim_{si\Delta^{0}_{1}(B)}(\Phi^{X})=0.

Proof

Let ATBA\not\leq_{T}B, and let Φ\Phi be a wtt-reduction. Let ff be a computable bound on the use of Φ\Phi, and define g(n)=max{f(i)in}g(n)=\max\{f(i)\mid i\leq n\}, so that K(ΦXn)+K(Xg(n))+2log(n)K(\Phi^{X}\upharpoonright n)\leq^{+}K(X\upharpoonright g(n))+2\log(n). For notational clarity, for the rest of this proof we will denote inequalities that hold up to logarithmic (in nn) terms as log\leq^{\log}.

Next, we define two sequences k\ell_{k} and λk\lambda_{k} which play the role 2k22^{k^{2}} played in previous constructions:

0=λ0=1,\displaystyle\ell_{0}=\lambda_{0}=1, λk=λk1+k1,\displaystyle\lambda_{k}=\lambda_{k-1}+\ell_{k-1}, k=min{2n2g(λk)<2n2}.\displaystyle\ell_{k}=\min\left\{2^{n^{2}}\mid g(\lambda_{k})<2^{n^{2}}\right\}.

These definitions have the useful consequence that limkk1/k=0\lim_{k}\ell_{k-1}/\ell_{k}=0. To see this, suppose k1=2(n1)2\ell_{k-1}=2^{(n-1)^{2}}. As gg is an increasing function, the definitions give

k>g(λk)λk=λk1+k1k1=2(n1)2.\ell_{k}>g(\lambda_{k})\geq\lambda_{k}=\lambda_{k-1}+\ell_{k-1}\geq\ell_{k-1}=2^{(n-1)^{2}}.

Hence k2n2\ell_{k}\geq 2^{n^{2}}, so that k1/k22n+1\ell_{k-1}/\ell_{k}\leq 2^{-2n+1}. As k>k1\ell_{k}>\ell_{k-1} for all kk, this ratio can be made arbitrarily small, giving the limit.

A triple recursive join operation is defined by

i=02Ai={3k+jkAj,0j2},A0,A1,A2ω.\bigoplus_{i=0}^{2}A_{i}=\{3k+j\mid k\in A_{j},\quad 0\leq j\leq 2\},\quad A_{0},A_{1},A_{2}\subseteq\omega.

Let S0TAS_{0}\leq_{T}A be as guaranteed by Lemma 4, and define S=i=02S0S=\bigoplus_{i=0}^{2}S_{0}. Let RR be Martin-Löf random, and define X(n)=R(nkn)1S(kn)X(n)=R\left(n-\ell_{k_{n}}\right)\cdot 1_{S}(k_{n}), where kn=max{k=2(mod3)kn}k_{n}=\max\{k=2\pmod{3}\mid\ell_{k}\leq n\}. This definition takes an unusual form compared to the previous ones we have seen in order to handle the interplay between λk\lambda_{k} and k\ell_{k} - specifically the growth rate of g(n)g(n). We are effectively “tripling up” bits of S0S_{0} (rather than doubling them as before) to account for the possibility that g(n)g(n) grows superexponentially, with the condition that k=2(mod3)k=2\pmod{3} replacing the condition that kk is odd.

Claim 1: dimsiΔ10(A)(X)=1\dim_{si\Delta^{0}_{1}(A)}(X)=1.
Proof: As N={k}kSN=\left\{\ell_{k}\right\}_{k\in S} is an AA-computable set, by the Sequence Lemma 1 it suffices to show that limkSK(Xk)/k=1.\lim_{k\in S}K(X\upharpoonright\ell_{k})/\ell_{k}=1. For kN\ell_{k}\in N,

K(Xk)\displaystyle K(X\upharpoonright\ell_{k}) logK(X[k1,k])K(Xk1)\displaystyle\geq^{\log}K(X[\ell_{k-1},\ell_{k}])-K(X\upharpoonright\ell_{k-1})
K(R(kk1))2k1\displaystyle\geq\ \ K(R\upharpoonright(\ell_{k}-\ell_{k-1}))-2\ell_{k-1} (as kSk\in S)
logkk12k1\displaystyle\geq^{\log}\ell_{k}-\ell_{k-1}-2\ell_{k-1} (as RR is Martin-Löf random)
K(Xk)k\displaystyle\dfrac{K(X\upharpoonright\ell_{k})}{\ell_{k}} logk3k1k=13k1k.\displaystyle\geq^{\log}\dfrac{\ell_{k}-3\ell_{k-1}}{\ell_{k}}=1-3\dfrac{\ell_{k-1}}{\ell_{k}}.

which gives the desired limit by the above.

Claim 2: dimsiΔ10(B)(ΦX)=0\dim_{si\Delta^{0}_{1}(B)}(\Phi^{X})=0.
Proof: Suppose NTBN\leq_{T}B. For notation, define a=kg(n)a=k_{g(n)}. By mimicking the proof of Lemma 2, we can use the BB-immunity of SS to show that there are infinitely many nNn\in N such that g(n)g(n) is in a 0-segment following two 0-segments, i.e., a2,a1,aSa-2,a-1,a\not\in S. By the definition of XX,

X[a2,a+1]=0a+1a2.X[\ell_{a-2},\ell_{a+1}]=0^{\ell_{a+1}-\ell_{a-2}}.

Suppose the value X(m)X(m) is queried in the course of computing ΦXn\Phi^{X}\upharpoonright n. By the definitions of gg, aa, and k\ell_{k}, mg(n)<a+1.m\leq g(n)<\ell_{a+1}. Hence either m<a2m<\ell_{a-2} or m[a2,a+1]m\in[\ell_{a-2},\ell_{a+1}], so that X(m)=0X(m)=0. Thus to compute ΦXn\Phi^{X}\upharpoonright n, up to a constant it suffices to know Xa2X\upharpoonright\ell_{a-2}. Thus

K(ΦXn)+K(Xa2)+2a2K(\Phi^{X}\upharpoonright n)\leq^{+}K(X\upharpoonright\ell_{a-2})\leq^{+}2\ell_{a-2}

As g(n)>ag(n)>\ell_{a} it must be that n>λan>\lambda_{a}. Dividing by nn, we find that

K(ΦXn)n+2a2λa<2a2λa1+a1<2a2a1.\displaystyle\dfrac{K(\Phi^{X}\upharpoonright n)}{n}\leq^{+}\dfrac{2\ell_{a-2}}{\lambda_{a}}<\dfrac{2\ell_{a-2}}{\lambda_{a-1}+\ell_{a-1}}<\dfrac{2\ell_{a-2}}{\ell_{a-1}}.

As there are infinitely many of these nn, it must be that infnNK(ΦXn)/n=0\inf_{n\in N}K(\Phi^{X}\upharpoonright n)/n=0. This holds for every NTBN\leq_{T}B, so taking a supremum gives the result.∎

Remark. We only consider sisi-dimensions for this theorem, as it is not clear what an appropriate analogue for isis-dimensions would be. The natural dual statement for isis-dimensions would be that for all reductions Φ\Phi there is an XX such that dimisΔ10(A)(X)=0\dim_{is\Delta^{0}_{1}(A)}(X)=0, and either ΦX\Phi^{X} is not total or dimisΔ10(B)(ΦX)=1\dim_{is\Delta^{0}_{1}(B)}(\Phi^{X})=1. But many reductions use only computably much of their oracle, so that ΦX\Phi^{X} is a computable set. This degenerate case is not a problem for the sisi theorem, as its conclusion requires dimΔ10(B)(ΦX)=0\dim_{\Delta^{0}_{1}(B)}(\Phi^{X})=0. But for an isis version, it is not even enough to require that ΦX\Phi^{X} is not computable - consider the reduction that repeats the nnth bit of XX 2n12n-1 times, so that nn bits of XX suffice to compute n2n^{2} bits of ΦX\Phi^{X}. Certainly ΦXwttX\Phi^{X}\equiv_{wtt}X, so that ΦX\Phi^{X} is non-computable iff XX is. But

K(ΦXn)n+K(Xn)n+2nn\displaystyle\dfrac{K(\Phi^{X}\upharpoonright n)}{n}\leq^{+}\dfrac{K(X\upharpoonright\sqrt{n})}{n}\leq^{+}\dfrac{2\sqrt{n}}{n}

for all nn, so that dimp(ΦX)=0\dim_{p}(\Phi^{X})=0, and hence all other dimensions are 0 as well.

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