By the Levin–Schnorr theorem, a sequence is random when the complexity of its initial segments is as large as possible, namely at least . This course studies the other extreme: the sets for which is as small as possible. A computable set has (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, is the prefix-free complexity defined by an optimal prefix-free machine , is inequality up to an additive constant, and a number is identified with the string associated with it, so that is defined.
1.1 Definition
A set is K-trivial if there is a constant with for every . We then say that is K-trivial with constant .
The opposite inequality holds for every set, since is computed from . A K-trivial set is far from random: for , by Proposition 3.4 of “Prefix-free complexity” (2), whereas a random sequence satisfies by the Levin–Schnorr theorem.
- Every computable set is K-trivial.
- If is K-trivial, so are its complement and every finite variant of .
- This is Proposition 3.6 of “Prefix-free complexity”.
- Exchanging and is a computable map sending to . If is a finite variant of , then , where modifies the finitely many positions at which and differ. In both cases a computable function is applied, which increases by at most a constant.
1.2 Chaitin’s counting theorem
The number of strings of length with complexity close to is bounded independently of .
There is a constant such that for all and , fewer than strings of length satisfy .
Let be the prefix-free machine , with the same domain as . By the coding theorem (Coding theorem; Levin, Chaitin), there is with for every ; enlarging makes the inequality strict. Let be the number of strings of length with . A shortest description of each of them is a description of for , of length at most , and these descriptions are distinct. So , and .
For every , there are fewer than sets that are K-trivial with constant , with as in Theorem 1.3. In particular, there are countably many K-trivial sets, and every K-trivial set is .
If are distinct sets that are K-trivial with constant , their prefixes of some length are pairwise distinct, and they are strings of length with . So .
The function is computable in , since is a property of . So the set of strings with for every is a tree computable in , and its paths are the sets that are K-trivial with constant . The class is finite, so each of its members is isolated. By Proposition 2.3 of “Computable members” relativized to , each member of is computable in .
The same argument, applied to in place of , 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 no such argument exists, since non-computable K-trivial sets exist.
1.3 Closure under join
The counting theorem allows one to describe by a shortest description of followed by a bounded amount of information.
If and are K-trivial, then is K-trivial.
Let be a common constant for and , as in Theorem 1.3, and . For a string in the domain of with , let be the set of strings of length with , listed in the order in which they are found by a fixed enumeration; this list is c.e. uniformly in . If is a shortest description of , then , and and belong to .
Let be the machine that, on input with in the domain of and , reads and as numbers , waits for the -th and -th elements of the list , and outputs the interleaving of length . Its domain is prefix-free, by the argument of Proposition 3.4 of “Prefix-free complexity” (1). With a shortest description of , and the positions of and in the list, . Hence
For an arbitrary length , let . The string is if is even, and this string with its last bit removed if is odd; both operations are computable and do not require knowing , so . Since is computed from , . So .
The direct estimate only gives ; the proof avoids describing 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 is not computable, but some computable functions bound it from above and agree with it, up to a constant, infinitely often.
A Solovay function is a computable function such that for every , and for infinitely many .
Fix a computable bijection between and , with .
Let if and is the least stage with , and otherwise. Then is a Solovay function. Moreover, if is a shortest description of and is as in the first case, then .
The function is computable, since it is decidable whether converges for the first time at stage with output .
. In the second case, let be the length of the string associated with . By Proposition 3.4 of “Prefix-free complexity” (2), . In the first case, let be the machine that, on input , waits for the least stage with and outputs . It has the domain of , so it is prefix-free, and .
infinitely often. Let be a shortest description of , its stage of convergence and . Then , and since is computed from . There is one such for each , so infinitely many.
A Solovay function is a computable substitute for along infinitely many arguments. Bienvenu and Downey observed that it can replace in the definition of K-triviality.
Let be the Solovay function of Proposition 1.7. A set is K-trivial if and only if for every .
() .
() Let be such that for every . Given , let be a shortest description of , its stage of convergence, and . Then . The string is computed from by truncation to the length , and is computed from ; so , with a constant independent of .
Since is computable and is approximable from above, the strings with for every form a c.e. tree, whose paths are exactly the sets satisfying the bound of the proposition with constant ; 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
Show that if is K-trivial and is a computable strictly increasing function, then the set is K-trivial.
Solution
For , the string is computed from , by reading the bits at positions . Let and for , a computable strictly increasing function. Given the string , one computes its length , then as the unique number with this image under , then ; so . Hence , since is computed from .
Show that no K-trivial set is Martin-Löf random, and that if is K-trivial and is random, then is not K-trivial.
Solution
A random set satisfies , whereas a K-trivial set satisfies ; so no set is both. If were K-trivial, then would be K-trivial as well: , and the first exercise applies with . 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 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.