206 research outputs found
On the Distribution of Complex Roots of Random Polynomials with Heavy-tailed Coefficients
Consider a random polynomial with i.i.d.
complex-valued coefficients. Suppose that the distribution of
has a slowly varying tail. Then the distribution of
the complex roots of concentrates in probability, as , to two
centered circles and is uniform in the argument as . The radii of
the circles are and
, where denotes the coefficient with
the maximum modulus.Comment: 8 page
Roots of random polynomials whose coefficients have logarithmic tails
It has been shown by Ibragimov and Zaporozhets [In Prokhorov and Contemporary
Probability Theory (2013) Springer] that the complex roots of a random
polynomial with i.i.d. coefficients
concentrate a.s. near the unit circle as if
and only if . We study the transition from
concentration to deconcentration of roots by considering coefficients with
tails behaving like as , where
, and is a slowly varying function. Under this assumption, the
structure of complex and real roots of is described in terms of the least
concave majorant of the Poisson point process on with
intensity .Comment: Published in at http://dx.doi.org/10.1214/12-AOP764 the Annals of
Probability (http://www.imstat.org/aop/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Universality for zeros of random analytic functions
Let be independent identically distributed (i.i.d.) random
variables such that \E \log (1+|\xi_0|)<\infty. We consider random analytic
functions of the form where
are deterministic complex coefficients. Let be the random
measure assigning the same weight to each complex zero of . Assuming
essentially that as , where
is some function, we show that the measure converges weakly to
some deterministic measure which is characterized in terms of the
Legendre--Fenchel transform of . The limiting measure is universal, that is
it does not depend on the distribution of the 's. This result is applied
to several ensembles of random analytic functions including the ensembles
corresponding to the three two-dimensional geometries of constant curvature. As
another application, we prove a random polynomial analogue of the circular law
for random matrices.Comment: 26 pages, 8 figures, 1 tabl
Random determinants, mixed volumes of ellipsoids, and zeros of Gaussian random fields
Consider a matrix whose rows are independent centered
non-degenerate Gaussian vectors with covariance matrices
. Denote by the location-dispersion
ellipsoid of . We show that where
denotes the {\it mixed volume}. We also generalize this
result to the case of rectangular matrices. As a direct corollary we get an
analytic expression for the mixed volume of arbitrary ellipsoids in
.
As another application, we consider a smooth centered non-degenerate Gaussian
random field . Using Kac-Rice
formula, we obtain the geometric interpretation of the intensity of zeros of
in terms of the mixed volume of location-dispersion ellipsoids of the
gradients of . This relates zero sets of equations
to mixed volumes in a way which is reminiscent of the well-known Bernstein
theorem about the number of solutions of the typical system of algebraic
equations
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