3 research outputs found
Areas of areas generate the shuffle algebra
We consider the anti-symmetrization of the half-shuffle on words, which we
call the 'area' operator, since it corresponds to taking the signed area of
elements of the iterated-integral signature. The tensor algebra is a so-called
Tortkara algebra under this operator. We show that the iterated application of
the area operator is sufficient to recover the iterated-integral signature of a
path. Just as the "information" the second level adds to the first one is known
to be equivalent to the area between components of the path, this means that
all the information added by subsequent levels is equivalent to iterated areas.
On the way to this main result, we characterize (homogeneous) generating sets
of the shuffle algebra. We finally discuss compatibility between the area
operator and discrete integration and stochastic integration and conclude with
some results on the linear span of the areas of areas.Comment: added examples and remarks, corrected semimartingale/martingale par
The Magnus expansion and some of its applications
Approximate resolution of linear systems of differential equations with
varying coefficients is a recurrent problem shared by a number of scientific
and engineering areas, ranging from Quantum Mechanics to Control Theory. When
formulated in operator or matrix form, the Magnus expansion furnishes an
elegant setting to built up approximate exponential representations of the
solution of the system. It provides a power series expansion for the
corresponding exponent and is sometimes referred to as Time-Dependent
Exponential Perturbation Theory. Every Magnus approximant corresponds in
Perturbation Theory to a partial re-summation of infinite terms with the
important additional property of preserving at any order certain symmetries of
the exact solution. The goal of this review is threefold. First, to collect a
number of developments scattered through half a century of scientific
literature on Magnus expansion. They concern the methods for the generation of
terms in the expansion, estimates of the radius of convergence of the series,
generalizations and related non-perturbative expansions. Second, to provide a
bridge with its implementation as generator of especial purpose numerical
integration methods, a field of intense activity during the last decade. Third,
to illustrate with examples the kind of results one can expect from Magnus
expansion in comparison with those from both perturbative schemes and standard
numerical integrators. We buttress this issue with a revision of the wide range
of physical applications found by Magnus expansion in the literature.Comment: Report on the Magnus expansion for differential equations and its
applications to several physical problem