The similarity metric

A new class of distances appropriate for measuring similarity relations between sequences, say one type of similarity per distance, is studied. We propose a new ``normalized information distance'', based on the noncomputable notion of Kolmogorov complexity, and show that it is in this class and it minorizes every computable distance in the class (that is, it is universal in that it discovers all computable similarities). We demonstrate that it is a metric and call it the {\em similarity metric}. This theory forms the foundation for a new practical tool. To evidence generality and robustness we give two distinctive applications in widely divergent areas using standard compression programs like gzip and GenCompress. First, we compare whole mitochondrial genomes and infer their evolutionary history. This results in a first completely automatic computed whole mitochondrial phylogeny tree. Secondly, we fully automatically compute the language tree of 52 different languages.Comment: 13 pages, LaTex, 5 figures, Part of this work appeared in Proc. 14th ACM-SIAM Symp. Discrete Algorithms, 2003. This is the final, corrected, version to appear in IEEE Trans Inform. T

Flavor Asymmetry of Nucleon Sea from Detailed Balance

In this study, the proton is taken as an ensemble of quark-gluon Fock states. Using the principle of detailed balance, we find $\bar{d}-\bar{u} \approx 0.124$, which is in surprisingly agreement with the experimental observation.Comment: 4 pages and no figures. Talk presented at the Third Circum-Pan-Pacific Symposium on "High Energy Spin Physics", Oct. 8-13, 2001, Beijing, Chin