4 research outputs found
On Resource-bounded versions of the van Lambalgen theorem
The van Lambalgen theorem is a surprising result in algorithmic information
theory concerning the symmetry of relative randomness. It establishes that for
any pair of infinite sequences and , is Martin-L\"of random and
is Martin-L\"of random relative to if and only if the interleaved sequence
is Martin-L\"of random. This implies that is relative random
to if and only if is random relative to \cite{vanLambalgen},
\cite{Nies09}, \cite{HirschfeldtBook}. This paper studies the validity of this
phenomenon for different notions of time-bounded relative randomness.
We prove the classical van Lambalgen theorem using martingales and Kolmogorov
compressibility. We establish the failure of relative randomness in these
settings, for both time-bounded martingales and time-bounded Kolmogorov
complexity. We adapt our classical proofs when applicable to the time-bounded
setting, and construct counterexamples when they fail. The mode of failure of
the theorem may depend on the notion of time-bounded randomness
A Characterization of Constructive Dimension
In the context of Kolmogorov’s algorithmic approach to the foundations of probability, Martin-Löf defined the concept of an individual random sequence using the concept of a constructive measure 1 set. Alternate characterizations use constructive martingales and measures of impossibility. We prove a direct conversion of a constructive martingale into a measure of impossibility and vice versa, such that their success sets, for a suitably defined class of computable probability measures, are equal. The direct conversion is then generalized to give a new characterization of constructive dimensions, in particular, the constructive Hausdorff dimension and the constructive packing dimension, and their generalizations, the constructive scaled dimension and the constructive scaled strong dimension.