1,592,822 research outputs found
Lipschitz extension constants equal projection constants
For a Banach space we define its Lipschitz extension constant,
\cL\cE(V), to be the infimum of the constants such that for every metric
space , every , and every , there is an
extension, , of to such that , where denotes the
Lipschitz constant. The basic theorem is that when is finite-dimensional we
have \cL\cE(V) = \cP\cC(V) where \cP\cC(V) is the well-known projection
constant of . We obtain some direct consequences of this theorem, especially
when V = M_n(\bC). We then apply techniques for calculating projection
constants, involving averaging projections, to calculate
\cL\cE((M_n(\bC))^{sa}). We also discuss what happens if we also require that
.Comment: 16 pages. Three very minor mathematical typos corrected. Intended for
the proceedings of GPOTS0
Universal constants and natural systems of units in a spacetime of arbitrary dimension
We study the properties of fundamental physical constants using the threefold
classification of dimensional constants proposed by J.-M. L{\'e}vy-Leblond:
constants of objects (masses, etc.), constants of phenomena (coupling
constants), and "universal constants" (such as and ). We show that
all of the known "natural" systems of units contain at least one non-universal
constant. We discuss the possible consequences of such non-universality, e.g.,
the dependence of some of these systems on the number of spatial dimensions. In
the search for a "fully universal" system of units, we propose a set of
constants that consists of , , and a length parameter and discuss its
origins and the connection to the possible kinematic groups discovered by
L{\'e}vy-Leblond and Bacry. Finally, we give some comments about the
interpretation of these constants.Comment: 18 pages, pedagogical article. v3: small corrections and extensions,
some references added. This version matches the published on
Diffusion constants and martingales for senile random walks
We derive diffusion constants and martingales for senile random walks with
the help of a time-change. We provide direct computations of the diffusion
constants for the time-changed walks. Alternatively, the values of these
constants can be derived from martingales associated with the time-changed
walks. Using an inverse time-change, the diffusion constants for senile random
walks are then obtained via these martingales. When the walks are diffusive,
weak convergence to Brownian motion can be shown using a martingale functional
limit theorem.Comment: 17 pages, LaTeX; the proof of Proposition 2.3 has been simplified,
and an error in the proof of Theorem 2.4 has been correcte
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