You need to know: Basic probability theory, notation for probability, random variable, distribution of a random variable, independent identically distributed (i.i.d.) random variables, polynomial, degree of a polynomial, monic polynomial. You also need Lebesgue measure and Hausdorff dimension to understand the context.
Background: Let be real numbers, and let
be a sequence of i.i.d. random variables with
and
for all n. By Bernoulli convolution we mean the random variable
.
is called absolutely continuous if there exists function
such that
whenever
. The Mahler measure of any polynomial
is
. A real number
is called algebraic if
for some polynomial P with rational coefficients. The (unique) monic polynomial
of smallest degree with this property is called the minimal polynomial of r. The Mahler measure of r is
.
The Theorem: On 31st January 2016, Péter Varjú submitted to arxiv a paper in which he proved that for every and
, there is a constant
such that for any algebraic number
satisfying
, the Bernoulli convolution
is absolutely continuous.
Short context: Bernoulli convolutions has been introduced by Jessen and Wintner in 1935, and studied by Erdős and many others since that. The main research question is for which values of and
the Bernoulli convolution is absolutely continuous. In 1939, Erdős noticed that
is not absolutely continuous for
, and also for
for some non-empty set
. However, Solomyak proved in 1995 that set E has Lebesgue measure
. Moreover, Shmerkin, building on this theorem, proved in 2014 that E has Hausdorff dimension
. Despite on this, it was known very few explicit examples of
-s for which
is absolutely continuous, and none such examples was known for
. The Theorem (with explicit
) provides a lot of such examples. For example, it implies that
is absolutely continuous for
and
.
Links: Free arxiv version of the original paper is here, journal version is here.
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