12 research outputs found
Algorithmic statistics revisited
The mission of statistics is to provide adequate statistical hypotheses
(models) for observed data. But what is an "adequate" model? To answer this
question, one needs to use the notions of algorithmic information theory. It
turns out that for every data string one can naturally define
"stochasticity profile", a curve that represents a trade-off between complexity
of a model and its adequacy. This curve has four different equivalent
definitions in terms of (1)~randomness deficiency, (2)~minimal description
length, (3)~position in the lists of simple strings and (4)~Kolmogorov
complexity with decompression time bounded by busy beaver function. We present
a survey of the corresponding definitions and results relating them to each
other
Effective-Range Expansion of the Neutron-Deuteron Scattering Studied by a Quark-Model Nonlocal Gaussian Potential
The S-wave effective range parameters of the neutron-deuteron (nd) scattering
are derived in the Faddeev formalism, using a nonlocal Gaussian potential based
on the quark-model baryon-baryon interaction fss2. The spin-doublet low-energy
eigenphase shift is sufficiently attractive to reproduce predictions by the
AV18 plus Urbana three-nucleon force, yielding the observed value of the
doublet scattering length and the correct differential cross sections below the
deuteron breakup threshold. This conclusion is consistent with the previous
result for the triton binding energy, which is nearly reproduced by fss2
without reinforcing it with the three-nucleon force.Comment: 21 pages, 6 figures and 6 tables, submitted to Prog. Theor. Phy
On randomness and infinity
In this paper, we investigate refined definitions of random sequences. Classical definitions have always the shortcome of making use of the notion of algorithm. We discuss the nature of randomness and different ways of obtaining satisfactory definitions of randomness after reviewing previous attempts at producing a non-algorithmical definition. We present alternative definitions based on infinite time machines and set theory and explain how and why randomness is strongly linked toDans ce papier, nous étudions différentes définitions de la notion de suite aléatoire. Les définitions classiques ont le défaut d'utiliser la notion d'algorithme. Après la présentation des tentatives passées de trouver une définition non-algorithmique, nous discutons de la notion d'aléatoire et envisageons différentes façons d'obtenir des définitions satisfaisantes. Nous donnons plusieurs définitions basées sur les machines à temps infini et la théorie des ensembles et nous expliquons en quoi l’aléatoire est fortement lié aux axiomes forts de l'infin