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@misc{immunity-growth-computably-dominated,
  title = {{Computably dominated degrees}},
  howpublished = {Lesson 2 of \emph{Immunity and growth of functions}, Computability Theory course notes},
  url = {/courses/immunity-growth/computably-dominated},
  note = {Unreleased working version}
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Lesson 2 of 4

Computably dominated degrees

Sets all of whose functions are dominated by computable functions; a construction by computable function trees; truth-table reducibility, and the characterization of computably dominated sets by the coincidence of Turing and truth-table reducibility below them.

45 min4 questions
Before this lesson:Immune and hyperimmune sets · Basis theorems (Π⁰₁ classes)
Immunity and growth of functions · lesson 2 of 4
  1. Immune and hyperimmune sets
  2. Computably dominated degrees
  3. Diagonally non-computable functions
  4. Martin's domination theorem

A set is computably dominated (Definition 3.3 of “Basis theorems”), or hyperimmune-free, if every function it computes is dominated by a computable function. By Definition 1.4, these are exactly the sets that are not of hyperimmune degree. Computable sets are computably dominated, and no non-computable Δ20\Delta^0_2 set is (Martin–Miller). The computably dominated basis theorem (Computably dominated basis theorem) gave non-computable examples inside Π10\Pi^0_1 classes. This lesson gives a second construction, by function trees, which does not use Π10\Pi^0_1 classes, and then shows that below a computably dominated set, Turing reducibility coincides with the much more restrictive truth-table reducibility.

Being computably dominated is closed downward under Turing reducibility: if Y≤TXY \leq_T X, every YY-computable function is XX-computable.

2.1 Function trees

Definition 2.1.#

A function tree, or f-tree, is a total function T:2<N→2<NT : \bstr \to \bstr such that for all strings ρ,μ\rho, \mu,

ρ⪯μ  ⟺  T(ρ)⪯T(μ).\rho \preceq \mu \iff T(\rho) \preceq T(\mu).

The strings T(ρ)T(\rho) are the nodes of TT. A set XX is a path of TT if infinitely many prefixes of XX are nodes of TT; [T][T] denotes the class of paths. An f-tree SS is a subtree of TT if every node of SS is a node of TT.

For every ρ\rho, the nodes T(ρ0)T(\rho 0) and T(ρ1)T(\rho 1) strictly extend T(ρ)T(\rho) (they extend it since ρ⪯ρi\rho \preceq \rho i, and differ from it since ρi⪯̸ρ\rho i \not\preceq \rho) and are incompatible: neither ρ0⪯ρ1\rho 0 \preceq \rho 1 nor ρ1⪯ρ0\rho 1 \preceq \rho 0, so neither node extends the other. If SS is a subtree of TT, then [S]⊆[T][S] \subseteq [T], directly from the definition of paths. For every ρ\rho, the function μ↦T(ρμ)\mu \mapsto T(\rho \mu) is a subtree of TT, computable if TT is, whose nodes all extend T(ρ)T(\rho); we call it the full subtree above T(ρ)T(\rho).

If X∈[T]X \in [T] and T(ρ1)≺T(ρ2)≺⋯T(\rho_1) \prec T(\rho_2) \prec \cdots are the nodes of TT that are prefixes of XX, then ρ1≺ρ2≺⋯\rho_1 \prec \rho_2 \prec \cdots by the definition (the inclusions are strict since TT is injective: T(ρ)=T(μ)T(\rho) = T(\mu) gives ρ⪯μ\rho \preceq \mu and μ⪯ρ\mu \preceq \rho). So for every nn, if ρi\rho_i has length at least nn and ρ\rho is its prefix of length nn, then T(ρ)⪯T(ρi)≺XT(\rho) \preceq T(\rho_i) \prec X. The identity T(ρ)=ρT(\rho) = \rho is a computable f-tree whose paths are all sets.

Lemma 2.2.#

Let TT be a computable f-tree and e∈Ne \in \nat. There is a computable subtree SS of TT such that Φe≠X\Phi_e \neq X for every X∈[S]X \in [S].

Proof of Lemma 2.2.

The nodes T(0)T(0) and T(1)T(1) are incompatible, so they differ at some position ii. If Φe(i) ⁣ ⁣↓=T(0)(i)\Phi_e(i)\converge = T(0)(i), let SS be the full subtree above T(1)T(1); otherwise, the full subtree above T(0)T(0). In the first case, every X∈[S]X \in [S] extends T(1)T(1), so X(i)=T(1)(i)≠Φe(i)X(i) = T(1)(i) \neq \Phi_e(i). In the second case, every X∈[S]X \in [S] has X(i)=T(0)(i)X(i) = T(0)(i), which differs from Φe(i)\Phi_e(i) or Φe(i)\Phi_e(i) diverges.

The subtree is computable, but the choice between the two cases is not effective: the lemma asserts existence, not a uniform procedure.

Lemma 2.3.#

Let TT be a computable f-tree and e∈Ne \in \nat. There is a computable subtree SS of TT such that either ΦeX\Phi^X_e is partial for every X∈[S]X \in [S], or there is a computable function gg that dominates ΦeX\Phi^X_e for every X∈[S]X \in [S].

Proof of Lemma 2.3.

Case 1: there are a node σ=T(ρ)\sigma = T(\rho) and an input xx such that Φeτ(x) ⁣ ⁣↑\Phi^\tau_e(x)\diverge for every node τ⪰σ\tau \succeq \sigma of TT. Let SS be the full subtree above σ\sigma. If X∈[S]X \in [S] had ΦeX(x) ⁣ ⁣↓\Phi^X_e(x)\converge, with use uu, then a node τ\tau of SS that is a prefix of XX of length at least uu would satisfy Φeτ(x) ⁣ ⁣↓\Phi^\tau_e(x)\converge, and τ⪰σ\tau \succeq \sigma is a node of TT. So ΦeX(x) ⁣ ⁣↑\Phi^X_e(x)\diverge for all X∈[S]X \in [S].

Case 2: for every node σ\sigma of TT and every input xx, there is a node τ⪰σ\tau \succeq \sigma of TT with Φeτ(x) ⁣ ⁣↓\Phi^\tau_e(x)\converge. Define S(ρ)=T(μρ)S(\rho) = T(\mu_\rho) by induction on ρ\rho. Let με\mu_\varepsilon be the first string found, in a computable search, with ΦeT(με)(0) ⁣ ⁣↓\Phi^{T(\mu_\varepsilon)}_e(0)\converge. Given μρ\mu_\rho, for i∈{0,1}i \in \{0, 1\}, let μρi\mu_{\rho i} be the first string μ⪰μρ i\mu \succeq \mu_\rho\, i found with ΦeT(μ)(∣ρ∣+1) ⁣ ⁣↓\Phi^{T(\mu)}_e(|\rho| + 1)\converge. The searches terminate by the hypothesis of Case 2, applied to the nodes T(ε)T(\varepsilon) and T(μρ i)T(\mu_\rho\, i), and the nodes τ⪰T(μρ i)\tau \succeq T(\mu_\rho\, i) of TT are of the form T(μ)T(\mu) with μ⪰μρ i\mu \succeq \mu_\rho\, i. So SS is computable. Since μρi⪰μρ i\mu_{\rho i} \succeq \mu_\rho\, i, the map ρ↦μρ\rho \mapsto \mu_\rho preserves both the prefix relation and incompatibility, so SS is an f-tree, and it is a subtree of TT.

By construction, ΦeS(ρ)(∣ρ∣) ⁣ ⁣↓\Phi^{S(\rho)}_e(|\rho|)\converge for every ρ\rho. Let g(n)=max⁡{ΦeS(ρ)(n):∣ρ∣=n}g(n) = \max \{ \Phi^{S(\rho)}_e(n) : |\rho| = n \}, a computable function. Let X∈[S]X \in [S] and n∈Nn \in \nat. Some ρ\rho of length nn has S(ρ)≺XS(\rho) \prec X, so ΦeX(n)=ΦeS(ρ)(n)≤g(n)\Phi^X_e(n) = \Phi^{S(\rho)}_e(n) \leq g(n). Hence ΦeX\Phi^X_e is total and dominated by gg.

Theorem 2.4 (Martin–Miller).#

There is a non-computable computably dominated set. Moreover, it can be taken computable in ∅′′\emptyset''.

Proof of Theorem 2.4.

Build computable f-trees T0,T1,…T_0, T_1, \dots, each a subtree of the previous one. Let T0T_0 be the identity. Given T2eT_{2e}, let T2e+1T_{2e+1} be given by Lemma 2.2 for T2eT_{2e} and ee. Given T2e+1T_{2e+1}, let T′T' be given by Lemma 2.3 for T2e+1T_{2e+1} and ee, and let T2e+2T_{2e+2} be the full subtree of T′T' above T′(0)T'(0). Each step replaces the tree by a subtree whose root Tk+1(ε)T_{k+1}(\varepsilon) strictly extends Tk(ε)T_k(\varepsilon): this holds for the full subtrees used at the odd steps, and is enforced at the even steps by passing to T′(0)T'(0).

The roots form a chain T0(ε)≺T1(ε)≺⋯T_0(\varepsilon) \prec T_1(\varepsilon) \prec \cdots of increasing lengths; let XX be their union. For each kk, the roots Tj(ε)T_j(\varepsilon), j≥kj \geq k, are nodes of TkT_k and prefixes of XX, so X∈[Tk]X \in [T_k]. Since X∈[T2e+1]X \in [T_{2e+1}], X≠ΦeX \neq \Phi_e; so XX is not computable. Since X∈[T2e+2]⊆[T′]X \in [T_{2e+2}] \subseteq [T'], either ΦeX\Phi^X_e is partial or it is dominated by a computable function. So XX is computably dominated.

For the bound, the construction makes two kinds of choices. At odd steps, it asks whether Φe(i) ⁣ ⁣↓=T(0)(i)\Phi_e(i)\converge = T(0)(i), a Σ10\Sigma^0_1 question. At even steps, it asks whether Case 1 holds, a Σ20\Sigma^0_2 question about an index of the computable tree; if so, a witness (ρ,x)(\rho, x) is found with ∅′′\emptyset'' by asking, for each candidate, the Π10\Pi^0_1 question that defines Case 1. Each new tree is then computable from these answers, uniformly. So the sequence of indices of the trees, and XX, are computable in ∅′′\emptyset''.

The technique of f-trees is a forcing with perfect trees, due to Spector for the construction of minimal degrees; it is used again in the study of the structure of the Turing degrees. The bound ∅′′\emptyset'' is optimal: no non-computable Δ20\Delta^0_2 set is computably dominated.

2.2 Truth-table reducibility

In a Turing reduction ΦX=Y\Phi^X = Y, the procedure may diverge with oracles other than XX, and the amount of the oracle it reads is not known in advance. A truth-table reduction fixes in advance, for each input, which bits of the oracle are read and how the answer depends on them.

Definition 2.5.#

A set YY is truth-table reducible to XX, written Y≤ttXY \leq_{tt} X, if there are total computable functions ℓ\ell and θ\theta, where θ(n)\theta(n) is (a code of) a function from {0,1}ℓ(n)\{0, 1\}^{\ell(n)} to {0,1}\{0, 1\}, such that Y(n)=θ(n)(X ⁣↾ℓ(n))Y(n) = \theta(n)(X \uh \ell(n)) for every nn.

The function θ(n)\theta(n) is the truth table for the input nn. Clearly Y≤ttXY \leq_{tt} X implies Y≤TXY \leq_T X. If Y≤mXY \leq_m X via ff, then Y≤ttXY \leq_{tt} X with ℓ(n)=f(n)+1\ell(n) = f(n) + 1 and the table that reads the last bit.

Proposition 2.6.#

Y≤ttXY \leq_{tt} X if and only if there is a functional Φe\Phi_e such that ΦeZ\Phi^Z_e is total for every oracle ZZ, and ΦeX=Y\Phi^X_e = Y.

Proof of Proposition 2.6.

(⇒\Rightarrow) The functional that, on input nn and with any oracle ZZ, computes ℓ(n)\ell(n) and θ(n)\theta(n), reads Z ⁣↾ℓ(n)Z \uh \ell(n) and outputs θ(n)(Z ⁣↾ℓ(n))\theta(n)(Z \uh \ell(n)), is total on every oracle.

(⇐\Leftarrow) Fix nn. The set Tn={σ:Φeσ(n)[∣σ∣] ⁣ ⁣↑}T_n = \{ \sigma : \Phi^\sigma_e(n)[|\sigma|]\diverge \} is a computable tree. A path ZZ of TnT_n would satisfy ΦeZ(n) ⁣ ⁣↑\Phi^Z_e(n)\diverge by Proposition 1.5 of “Computation relative to an oracle”, which is excluded. By Weak König's lemma, TnT_n is finite, so there is a length ℓ\ell such that every string σ\sigma of length ℓ\ell has Φeσ(n)[ℓ] ⁣ ⁣↓\Phi^\sigma_e(n)[\ell]\converge. Let ℓ(n)\ell(n) be the least such ℓ\ell, found by a computable search, and let θ(n)(σ)=Φeσ(n)[ℓ(n)]\theta(n)(\sigma) = \Phi^\sigma_e(n)[\ell(n)] for ∣σ∣=ℓ(n)|\sigma| = \ell(n), with value replaced by 00 if it is not in {0,1}\{0, 1\}. Then Y(n)=ΦeX(n)=θ(n)(X ⁣↾ℓ(n))Y(n) = \Phi^X_e(n) = \theta(n)(X \uh \ell(n)).

The converse of the implications ≤m⇒≤tt⇒≤T\leq_m \Rightarrow \leq_{tt} \Rightarrow \leq_T fails. The complement of ∅′\emptyset' is truth-table reducible to ∅′\emptyset', with ℓ(n)=n+1\ell(n) = n + 1 and the table that negates the last bit; it is not many-one reducible to ∅′\emptyset', since a set many-one reducible to a c.e. set is c.e. (Definition 3.3 of “The halting problem”). The failure of the second converse follows from the next theorem, since ∅′\emptyset' is not computably dominated.

Theorem 2.7 (Jockusch, Martin).#

A set XX is computably dominated if and only if Y≤TXY \leq_T X implies Y≤ttXY \leq_{tt} X for every set YY.

Proof of Theorem 2.7.

(⇒\Rightarrow) Let Y=ΦeXY = \Phi^X_e, and let t(n)t(n) be the least ss such that ΦeX ⁣↾s(n)[s] ⁣ ⁣↓\Phi^{X \uh s}_e(n)[s]\converge. It is an XX-computable total function, so a computable function gg dominates it. Let ℓ=g\ell = g and let θ(n)(σ)=Φeσ(n)[g(n)]\theta(n)(\sigma) = \Phi^\sigma_e(n)[g(n)] for ∣σ∣=g(n)|\sigma| = g(n), replaced by 00 if it diverges or is not in {0,1}\{0, 1\}. Since t(n)≤g(n)t(n) \leq g(n), the computation with oracle X ⁣↾g(n)X \uh g(n) converges within g(n)g(n) steps to Y(n)Y(n), so Y(n)=θ(n)(X ⁣↾g(n))Y(n) = \theta(n)(X \uh g(n)).

(⇐\Leftarrow) Suppose that XX is not computably dominated, and let f≤TXf \leq_T X be a function dominated by no computable function. Let F(n)=max⁡m≤nf(m)F(n) = \max_{m \leq n} f(m). Fix an enumeration of the pairs (ℓe,θe)(\ell_e, \theta_e) of partial computable functions. Define YY on inputs n=⟨e,k⟩n = \langle e, k \rangle as follows. If ℓe(n)\ell_e(n) and θe(n)\theta_e(n) converge within F(n)F(n) steps, and θe(n)\theta_e(n) codes a function on {0,1}ℓe(n)\{0, 1\}^{\ell_e(n)}, let Y(n)=1−θe(n)(X ⁣↾ℓe(n))Y(n) = 1 - \theta_e(n)(X \uh \ell_e(n)); otherwise let Y(n)=0Y(n) = 0. Then Y≤TXY \leq_T X. Suppose Y≤ttXY \leq_{tt} X via total (ℓe,θe)(\ell_e, \theta_e). Let c(n)c(n) be the number of steps after which both ℓe(n)\ell_e(n) and θe(n)\theta_e(n) have converged; cc is computable. If F(⟨e,k⟩)≥c(⟨e,k⟩)F(\langle e, k \rangle) \geq c(\langle e, k \rangle) for some kk, then Y(⟨e,k⟩)=1−θe(⟨e,k⟩)(X ⁣↾ℓe(⟨e,k⟩))Y(\langle e, k \rangle) = 1 - \theta_e(\langle e, k \rangle)(X \uh \ell_e(\langle e, k \rangle)), contradicting the reduction. So F(⟨e,k⟩)<c(⟨e,k⟩)F(\langle e, k \rangle) < c(\langle e, k \rangle) for every kk. For each mm, let k(m)k(m) be the least kk with ⟨e,k⟩≥m\langle e, k \rangle \geq m, and G(m)=c(⟨e,k(m)⟩)G(m) = c(\langle e, k(m) \rangle). Then GG is computable and G(m)>F(⟨e,k(m)⟩)≥f(m)G(m) > F(\langle e, k(m) \rangle) \geq f(m) for every mm, so GG dominates ff, a contradiction.

Below a computably dominated set, every Turing reduction can be replaced by a reduction that reads a computably bounded amount of the oracle within a computably bounded time. This makes computably dominated sets behave, for many purposes, like compact objects; for instance, a computably dominated set that computes a DNC function computes one bounded by a computable function, since the DNC function itself is dominated.

2.3 Exercises

Exercise 2.8 ★.

Show that a computably dominated set computable in ∅′\emptyset' is computable, and that a computably dominated set computes no non-computable c.e. set.

Solution

A non-computable Δ20\Delta^0_2 set computes its computation function, which no computable function dominates (Martin–Miller); so it is not computably dominated. If XX is computably dominated and Y≤TXY \leq_T X, then YY is computably dominated, by downward closure. A non-computable c.e. set YY is Δ20\Delta^0_2, hence not computably dominated; so XX computes none.

Exercise 2.9 ★★.

Show that there are continuum many non-computable computably dominated sets.

Solution

Fix, for each computable f-tree and each ee, the subtree given by the proofs of Lemma 2.2 and Lemma 2.3, choosing the least witness in Case 1, so that the subtree is determined by the tree and ee. Modify the construction of Theorem 2.4: for Z∈2NZ \in \cs, build the trees TkZT^Z_k as before, except that at each step kk, after applying the lemma, pass to the full subtree above the node T(Z(k))T(Z(k)) of the tree TT obtained, rather than above a fixed node. Let XZX_Z be the union of the roots. As before, XZX_Z is non-computable and computably dominated. If ZZ and Z′Z' first differ at position kk, then the trees coincide up to step kk, and XZX_Z, XZ′X_{Z'} extend the nodes T(0)T(0) and T(1)T(1) of the same tree TT, which are incompatible. So Z↦XZZ \mapsto X_Z is injective.

2.4 Notes and references

Computably dominated degrees were introduced by Miller and Martin (1968), who constructed them by forcing with computable perfect trees, a method due to Spector (1956). The characterization by truth-table reducibility is due to Jockusch (1969) and Martin. Truth-table reducibility was introduced by Post (1944).

  • W. Miller and D. A. Martin, The degrees of hyperimmune sets, Zeitschrift für mathematische Logik und Grundlagen der Mathematik 14 (1968), 159–166.
  • C. Spector, On degrees of recursive unsolvability, Annals of Mathematics 64 (1956), 581–592.
  • E. L. Post, Recursively enumerable sets of positive integers and their decision problems, Bulletin of the American Mathematical Society 50 (1944), 284–316.
  • C. G. Jockusch, Relationships between reducibilities, Transactions of the American Mathematical Society 142 (1969), 229–237.