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@misc{k-trivials-k-trivial-sets,
  title = {{K-trivial sets}},
  howpublished = {Lesson 1 of \emph{K-trivial sets}, Computability Theory course notes},
  url = {/courses/k-trivials/k-trivial-sets},
  note = {Unreleased working version}
}

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Lesson 1 of 3

K-trivial sets

Sets whose initial segments are as simple as their lengths; Chaitin's counting theorem shows that there are countably many K-trivial sets, all of them Δ⁰₂; closure under join; Solovay functions and a characterization of K-triviality by a computable bound.

40 min4 questions
Before this lesson:The Levin–Schnorr theorem (Martin-Löf randomness) · The KC theorem and the coding theorem (Kolmogorov complexity) · Computable members (Π⁰₁ classes)
K-trivial sets · lesson 1 of 3
  1. K-trivial sets
  2. Cost functions and Solovay's construction
  3. Lowness for randomness

By the Levin–Schnorr theorem, a sequence is random when the complexity K(X ⁣↾n)K(X \uh n) of its initial segments is as large as possible, namely at least n−O(1)n - O(1). This course studies the other extreme: the sets AA for which K(A ⁣↾n)K(A \uh n) is as small as possible. A computable set has K(A ⁣↾n)=+K(n)K(A \uh n) =^+ K(n) (Proposition 3.6 of “Prefix-free complexity”): its initial segments contain no more information than their lengths. For plain complexity, the analogous condition characterizes the computable sets (Chaitin). For prefix-free complexity it does not: the next lesson builds non-computable sets with the same complexity as computable ones. These K-trivial sets coincide with several notions of computational weakness relative to randomness, which is the subject of the last lesson.

Throughout, KK is the prefix-free complexity defined by an optimal prefix-free machine UU, ≤+\leq^+ is inequality up to an additive constant, and a number nn is identified with the string associated with it, so that K(n)K(n) is defined.

1.1 Definition

Definition 1.1.#

A set AA is K-trivial if there is a constant bb with K(A ⁣↾n)≤K(n)+bK(A \uh n) \leq K(n) + b for every nn. We then say that AA is K-trivial with constant bb.

The opposite inequality K(n)≤+K(A ⁣↾n)K(n) \leq^+ K(A \uh n) holds for every set, since n=∣A ⁣↾n∣n = |A \uh n| is computed from A ⁣↾nA \uh n. A K-trivial set is far from random: K(A ⁣↾n)≤+K(n)≤+2log⁡nK(A \uh n) \leq^+ K(n) \leq^+ 2 \log n for n≥2n \geq 2, by Proposition 3.4 of “Prefix-free complexity” (2), whereas a random sequence XX satisfies K(X ⁣↾n)≥n−O(1)K(X \uh n) \geq n - O(1) by the Levin–Schnorr theorem.

Proposition 1.2.#
  1. Every computable set is K-trivial.
  2. If AA is K-trivial, so are its complement and every finite variant of AA.
Proof of Proposition 1.2.
  1. This is Proposition 3.6 of “Prefix-free complexity”.
  2. Exchanging 00 and 11 is a computable map sending A ⁣↾nA \uh n to A‾ ⁣↾n\overline{A} \uh n. If BB is a finite variant of AA, then B ⁣↾n=h(A ⁣↾n)B \uh n = h(A \uh n), where hh modifies the finitely many positions at which AA and BB differ. In both cases a computable function is applied, which increases KK by at most a constant.

1.2 Chaitin’s counting theorem

The number of strings of length nn with complexity close to K(n)K(n) is bounded independently of nn.

Theorem 1.3 (Chaitin).#

There is a constant cc such that for all nn and bb, fewer than 2b+c2^{b+c} strings σ\sigma of length nn satisfy K(σ)≤K(n)+bK(\sigma) \leq K(n) + b.

Proof of Theorem 1.3.

Let MM be the prefix-free machine τ↦∣U(τ)∣\tau \mapsto |U(\tau)|, with the same domain as UU. By the coding theorem (Coding theorem; Levin, Chaitin), there is cc with PM(n)<2c−K(n)P_M(n) < 2^{c - K(n)} for every nn; enlarging cc makes the inequality strict. Let NN be the number of strings σ\sigma of length nn with K(σ)≤K(n)+bK(\sigma) \leq K(n) + b. A shortest description of each of them is a description of nn for MM, of length at most K(n)+bK(n) + b, and these descriptions are distinct. So N 2−K(n)−b≤PM(n)<2c−K(n)N\, 2^{-K(n) - b} \leq P_M(n) < 2^{c - K(n)}, and N<2b+cN < 2^{b + c}.

Corollary 1.4 (Chaitin).#

For every bb, there are fewer than 2b+c2^{b+c} sets that are K-trivial with constant bb, with cc as in Theorem 1.3. In particular, there are countably many K-trivial sets, and every K-trivial set is Δ20\Delta^0_2.

Proof of Corollary 1.4.

If A0,…,AN−1A_0, \dots, A_{N-1} are distinct sets that are K-trivial with constant bb, their prefixes of some length nn are pairwise distinct, and they are NN strings of length nn with K(σ)≤K(n)+bK(\sigma) \leq K(n) + b. So N<2b+cN < 2^{b+c}.

The function KK is computable in ∅′\emptyset', since K(σ)≤kK(\sigma) \leq k is a Σ10\Sigma^0_1 property of (σ,k)(\sigma, k). So the set TbT_b of strings σ\sigma with K(σ ⁣↾m)≤K(m)+bK(\sigma \uh m) \leq K(m) + b for every m≤∣σ∣m \leq |\sigma| is a tree computable in ∅′\emptyset', and its paths are the sets that are K-trivial with constant bb. The class [Tb][T_b] is finite, so each of its members is isolated. By Proposition 2.3 of “Computable members” relativized to ∅′\emptyset', each member of [Tb][T_b] is computable in ∅′\emptyset'.

The same argument, applied to CC in place of KK, is the first step of the proof of Chaitin’s theorem on plain complexity; there, a further argument shows that the members of the corresponding tree are computable. For KK no such argument exists, since non-computable K-trivial sets exist.

1.3 Closure under join

The counting theorem allows one to describe A ⁣↾nA \uh n by a shortest description of nn followed by a bounded amount of information.

Proposition 1.5.#

If AA and BB are K-trivial, then A⊕BA \oplus B is K-trivial.

Proof of Proposition 1.5.

Let bb be a common constant for AA and BB, cc as in Theorem 1.3, and k=b+ck = b + c. For a string τ\tau in the domain of UU with U(τ)=nU(\tau) = n, let SτS_\tau be the set of strings σ\sigma of length nn with K(σ)≤∣τ∣+bK(\sigma) \leq |\tau| + b, listed in the order in which they are found by a fixed enumeration; this list is c.e. uniformly in τ\tau. If τ\tau is a shortest description of nn, then ∣Sτ∣<2k|S_\tau| < 2^k, and A ⁣↾nA \uh n and B ⁣↾nB \uh n belong to SτS_\tau.

Let MM be the machine that, on input τβγ\tau \beta \gamma with τ\tau in the domain of UU and ∣β∣=∣γ∣=k|\beta| = |\gamma| = k, reads β\beta and γ\gamma as numbers i,j<2ki, j < 2^k, waits for the ii-th and jj-th elements σ,σ′\sigma, \sigma' of the list SτS_\tau, and outputs the interleaving σ⊕σ′\sigma \oplus \sigma' of length 2n2n. Its domain is prefix-free, by the argument of Proposition 3.4 of “Prefix-free complexity” (1). With τ\tau a shortest description of nn, and β,γ\beta, \gamma the positions of A ⁣↾nA \uh n and B ⁣↾nB \uh n in the list, M(τβγ)=(A⊕B) ⁣↾2nM(\tau\beta\gamma) = (A \oplus B) \uh 2n. Hence

K((A⊕B) ⁣↾2n)≤+K(n)+2k.K((A \oplus B) \uh 2n) \leq^+ K(n) + 2k.

For an arbitrary length mm, let n=⌈m/2⌉n = \lceil m/2 \rceil. The string (A⊕B) ⁣↾m(A \oplus B) \uh m is (A⊕B) ⁣↾2n(A \oplus B) \uh 2n if mm is even, and this string with its last bit removed if mm is odd; both operations are computable and do not require knowing mm, so K((A⊕B) ⁣↾m)≤+K((A⊕B) ⁣↾2n)K((A \oplus B) \uh m) \leq^+ K((A \oplus B) \uh 2n). Since nn is computed from mm, K(n)≤+K(m)K(n) \leq^+ K(m). So K((A⊕B) ⁣↾m)≤+K(m)K((A \oplus B) \uh m) \leq^+ K(m).

The direct estimate K(⟨σ,σ′⟩)≤+K(σ)+K(σ′)K(\langle \sigma, \sigma' \rangle) \leq^+ K(\sigma) + K(\sigma') only gives 2K(n)2K(n); the proof avoids describing nn twice. Closure under Turing reducibility, the other half of the statement that the K-trivial sets form an ideal, is much harder; it is a consequence of the main theorem of the last lesson.

1.4 Solovay functions

The function KK is not computable, but some computable functions bound it from above and agree with it, up to a constant, infinitely often.

Definition 1.6.#

A Solovay function is a computable function g:N→Ng : \nat \to \nat such that K(m)≤+g(m)K(m) \leq^+ g(m) for every mm, and g(m)≤+K(m)g(m) \leq^+ K(m) for infinitely many mm.

Fix a computable bijection ⟨τ,n,t⟩\langle \tau, n, t \rangle between 2<N×N×N\bstr \times \nat \times \nat and N\nat, with ⟨τ,n,t⟩≥n\langle \tau, n, t \rangle \geq n.

Proposition 1.7 (Solovay).#

Let g(m)=∣τ∣g(m) = |\tau| if m=⟨τ,n,t⟩m = \langle \tau, n, t \rangle and tt is the least stage with U(τ)[t] ⁣ ⁣↓=nU(\tau)[t]\converge = n, and g(m)=2⌊log⁡(m+1)⌋+2g(m) = 2\lfloor \log(m+1) \rfloor + 2 otherwise. Then gg is a Solovay function. Moreover, if τ\tau is a shortest description of nn and m=⟨τ,n,t⟩m = \langle \tau, n, t \rangle is as in the first case, then g(m)=K(n)g(m) = K(n).

Proof of Proposition 1.7.

The function gg is computable, since it is decidable whether U(τ)U(\tau) converges for the first time at stage tt with output nn.

K≤+gK \leq^+ g. In the second case, let ℓ=⌊log⁡(m+1)⌋\ell = \lfloor \log(m+1) \rfloor be the length of the string associated with mm. By Proposition 3.4 of “Prefix-free complexity” (2), K(m)≤+ℓ+2log⁡ℓ≤+2ℓ+2=g(m)K(m) \leq^+ \ell + 2 \log \ell \leq^+ 2\ell + 2 = g(m). In the first case, let MM be the machine that, on input τ\tau, waits for the least stage tt with U(τ)[t] ⁣ ⁣↓U(\tau)[t]\converge and outputs ⟨τ,U(τ),t⟩\langle \tau, U(\tau), t \rangle. It has the domain of UU, so it is prefix-free, and K(m)≤+∣τ∣=g(m)K(m) \leq^+ |\tau| = g(m).

g≤+Kg \leq^+ K infinitely often. Let τ\tau be a shortest description of nn, tt its stage of convergence and m=⟨τ,n,t⟩m = \langle \tau, n, t \rangle. Then g(m)=∣τ∣=K(n)g(m) = |\tau| = K(n), and K(n)≤+K(m)K(n) \leq^+ K(m) since nn is computed from mm. There is one such mm for each nn, so infinitely many.

A Solovay function is a computable substitute for KK along infinitely many arguments. Bienvenu and Downey observed that it can replace K(n)K(n) in the definition of K-triviality.

Proposition 1.8 (Bienvenu, Downey).#

Let gg be the Solovay function of Proposition 1.7. A set AA is K-trivial if and only if K(A ⁣↾m)≤+g(m)K(A \uh m) \leq^+ g(m) for every mm.

Proof of Proposition 1.8.

(⇒\Rightarrow) K(A ⁣↾m)≤+K(m)≤+g(m)K(A \uh m) \leq^+ K(m) \leq^+ g(m).

(⇐\Leftarrow) Let cc be such that K(A ⁣↾m)≤g(m)+cK(A \uh m) \leq g(m) + c for every mm. Given nn, let τ\tau be a shortest description of nn, tt its stage of convergence, and m=⟨τ,n,t⟩≥nm = \langle \tau, n, t \rangle \geq n. Then K(A ⁣↾m)≤g(m)+c=K(n)+cK(A \uh m) \leq g(m) + c = K(n) + c. The string A ⁣↾nA \uh n is computed from A ⁣↾mA \uh m by truncation to the length nn, and nn is computed from mm; so K(A ⁣↾n)≤+K(A ⁣↾m)≤+K(n)K(A \uh n) \leq^+ K(A \uh m) \leq^+ K(n), with a constant independent of nn.

Since gg is computable and KK is approximable from above, the strings σ\sigma with K(σ ⁣↾m)≤g(m)+cK(\sigma \uh m) \leq g(m) + c for every m≤∣σ∣m \leq |\sigma| form a c.e. tree, whose paths are exactly the sets satisfying the bound of the proposition with constant cc; they are all K-trivial. Nies proved that every K-trivial set is computable from a c.e. K-trivial set, with the cost function method and the golden run construction mentioned in the last lesson; the c.e. trees above give another proof, based on the fact that a K-trivial set is an isolated path of such a tree. This theorem is admitted here (see Nies, Lowness properties and randomness, 2005, and Nies, Computability and Randomness, Chapter 5).

1.5 Exercises

Exercise 1.9 ★.

Show that if AA is K-trivial and ff is a computable strictly increasing function, then the set B={n:f(n)∈A}B = \{ n : f(n) \in A \} is K-trivial.

Solution

For n≥1n \geq 1, the string B ⁣↾nB \uh n is computed from A ⁣↾(f(n−1)+1)A \uh (f(n-1) + 1), by reading the bits at positions f(0),…,f(n−1)f(0), \dots, f(n-1). Let h(0)=0h(0) = 0 and h(n)=f(n−1)+1h(n) = f(n-1) + 1 for n≥1n \geq 1, a computable strictly increasing function. Given the string A ⁣↾h(n)A \uh h(n), one computes its length h(n)h(n), then nn as the unique number with this image under hh, then B ⁣↾nB \uh n; so K(B ⁣↾n)≤+K(A ⁣↾h(n))K(B \uh n) \leq^+ K(A \uh h(n)). Hence K(B ⁣↾n)≤+K(A ⁣↾h(n))≤+K(h(n))≤+K(n)K(B \uh n) \leq^+ K(A \uh h(n)) \leq^+ K(h(n)) \leq^+ K(n), since h(n)h(n) is computed from nn.

Exercise 1.10 ★.

Show that no K-trivial set is Martin-Löf random, and that if AA is K-trivial and ZZ is random, then A⊕ZA \oplus Z is not K-trivial.

Solution

A random set satisfies K(Z ⁣↾n)≥n−O(1)K(Z \uh n) \geq n - O(1), whereas a K-trivial set satisfies K(A ⁣↾n)≤+2log⁡nK(A \uh n) \leq^+ 2 \log n; so no set is both. If A⊕ZA \oplus Z were K-trivial, then ZZ would be K-trivial as well: Z={n:2n+1∈A⊕Z}Z = \{ n : 2n + 1 \in A \oplus Z \}, and the first exercise applies with f(n)=2n+1f(n) = 2n + 1. This contradicts the first statement.

1.6 Notes and references

K-trivial sets appear in the work of Chaitin (1977), who proved Corollary 1.4, and in Solovay’s unpublished manuscript (1975), which contains the construction of a non-computable K-trivial set given in the next lesson. The closure under join is due to Downey, Hirschfeldt, Nies and Stephan (2003). Solovay functions were studied by Bienvenu and Downey (2009), and Bienvenu, Merkle and Nies (2011) showed that every Solovay function can replace KK in the definition of K-triviality.

  • G. J. Chaitin, Algorithmic information theory, IBM Journal of Research and Development 21 (1977), 350–359.
  • R. G. Downey, D. R. Hirschfeldt, A. Nies and F. Stephan, Trivial reals, in: Proceedings of the 7th and 8th Asian Logic Conferences, 2003, 103–131.
  • L. Bienvenu and R. Downey, Kolmogorov complexity and Solovay functions, STACS 2009, 147–158.
  • L. Bienvenu, W. Merkle and A. Nies, Solovay functions and K-triviality, STACS 2011.
  • A. Nies, Lowness properties and randomness, Advances in Mathematics 197 (2005), 274–305.
  • A. Nies, Computability and Randomness, Oxford University Press, 2009.