algorithmic dimension
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Computability ◽  
2021 ◽  
pp. 1-28
Author(s):  
Neil Lutz ◽  
D.M. Stull

This paper investigates the algorithmic dimension spectra of lines in the Euclidean plane. Given any line L with slope a and vertical intercept b, the dimension spectrum sp ( L ) is the set of all effective Hausdorff dimensions of individual points on L. We draw on Kolmogorov complexity and geometrical arguments to show that if the effective Hausdorff dimension dim ( a , b ) is equal to the effective packing dimension Dim ( a , b ), then sp ( L ) contains a unit interval. We also show that, if the dimension dim ( a , b ) is at least one, then sp ( L ) is infinite. Together with previous work, this implies that the dimension spectrum of any line is infinite.


2021 ◽  
Vol 13 (3) ◽  
pp. 1-15
Author(s):  
Neil Lutz

Algorithmic fractal dimensions quantify the algorithmic information density of individual points and may be defined in terms of Kolmogorov complexity. This work uses these dimensions to bound the classical Hausdorff and packing dimensions of intersections and Cartesian products of fractals in Euclidean spaces. This approach shows that two prominent, fundamental results about the dimension of Borel or analytic sets also hold for arbitrary sets.


2000 ◽  
pp. 247-269
Author(s):  
Yuri L. Ershov ◽  
Sergei S. Goncharov

1992 ◽  
Vol 32 (3) ◽  
pp. 535-538
Author(s):  
V. D. Dzgoev

1989 ◽  
Vol 30 (2) ◽  
pp. 210-217 ◽  
Author(s):  
S. S. Goncharov ◽  
B. N. Drobotun

1989 ◽  
Vol 30 (1) ◽  
pp. 63-68 ◽  
Author(s):  
S. S. Goncharov ◽  
A. V. Molokov ◽  
N. S. Romanovskii

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