If you’re interested in chatting with me about any of these topics, please email me or use the Contact page to get in touch! (Students, I use some specialized vocabulary but I’m happy to explain what any of it means!)
Planar Networks
A circular planar graph is a planar (undirected) graph embedded in a disc, with vertices embedded in the boundary circle called boundary vertices, numbered in circular order. A planar network is a circular planar graph with weighted edges; usually the weights are positive real numbers or formal indeterminates in a polynomial or power series ring.
- Imagining each edge weight to be a length, we can calculate the total lengths of the shortest paths between each pair of boundary vertices and put them in a symmetric matrix
. These matrix entries satisfy the triangle inequality (
for all
) as well as a “quadrangle inequality” (
for all
in circular order). Does every symmetric matrix with zero diagonal satisfying the triangle and quadrangle inequalities arise in this way?
- For which circular planar graphs is the edge weighting determined by the distance matrix
?
If we imagine each edge weight to be the resistance of an idealized resistor, and build the matrix of “effective resistances” between each pair of boundary vertices, then it is known which matrices arise in this way, and the matrix determines the edge weights iff the circular planar graph’s medial graph is lensless.
- If we instead build a matrix whose
th entry is the sum, over all walks from
to
, of the product of the weights of edges in the walk, then we again obtain a symmetric matrix. Which matrices arise in this way, and when does the matrix determine the original edge weights? (The “distance matrix” is a tropicalized version of this matrix.)
Polynomial laws
Given a ring (all rings and algebras on this page are commutative and unital unless otherwise noted), with modules
and
, a polynomial law
is a family of functions
that commute with base change. A polynomial law is called homogeneous of degree d if each function
satisfies
for all
. (Degree-
polynomial laws are constant; degree-
polynomial laws are module homomorphisms; degree-
polynomial laws are quadratic forms.) If
and
are
-algebras, then
is multiplicative if each function
is.
- Suppose
is a multiplicative degree-
polynomial law with
. Is it always possible to base change along an injective ring homomorphism
to make the polynomial law
factor as an
-algebra homomorphism times a multiplicative polynomial law of degree
?
If is flat, then multiplicative homogeneous degree-d polynomial laws
correspond to
-algebra homomorphisms
. Given an
-algebra
of rank
, the norm function
is a multiplicative degree-
polynomial law, and therefore corresponds to a canonical
-algebra homomorphism
, called the Ferrand homomorphism.
G-closures
Given an -algebra
of rank
, and any subgroup
, a homomorphism
extending the Ferrand homomorphism is called a
–closure datum for
, and the
-algebra
, defined on the left by inclusion and on the right by
, is called the
–closure algebra corresponding to
.
- For any quadratic
-algebra
, there is a canonical
-closure datum for
, and the corresponding
-closure algebra is isomorphic to
. Given a cubic
-algebra
, under what conditions on a
-closure datum for
is the corresponding
-closure algebra isomorphic to
?
- There is a canonical multiplication
on quadratic algebras that reduces to addition of
-torsors in the étale case. Is there a similar operation on cubic algebras equipped with a
-closure datum?
Discriminant Algebras
- Given an
-algebra
of rank
, define its discriminant algebra
to equal
, where the left-hand map is inclusion and the right-hand map is the Ferrand homomorphism. Is the assignment
the only functor, up to natural isomorphism, that preserves base change and comes with an isomorphism
that commutes with the discriminant bilinear forms?
- If
and
are
-algebras of ranks
and
, then it is known that
. Is it also the case that
?
- If
is an
-algebra of rank
, and
is a
-algebra of rank
, then is
?
Interval-valued probability measures
Half of all natural numbers are even. What this means, since there’s no uniform probability measure on the natural numbers, is that as , the fraction of natural numbers up to
that are even converges to
. This limiting fraction is called the density of the set of even numbers. However, not every subset
of the natural numbers has a well-defined density; the limit
might not exist. (Example: the set of natural numbers whose base-ten expansion starts with
.) However, we can always consider the set of all limits of convergent subsequences of
; this is always a closed interval
. This assignment
from subsets of
to closed intervals in
is an interval-valued probability measure in the sense that
- For all subsets
, we have
.
- For all disjoint subsets
, we have
.
.
(The fact that #2 doesn’t hold for countable disjoint unions makes only a finitely-additive interval-valued probability measure.) There’s a similar finitely-additive interval-valued probability measure for Lebesgue measurable subsets of the real line, and for any inductive limit of probability spaces.
- Given a nonempty set
, a collection of “measurable” subsets
closed under finite unions and complements, and a finitely-additive interval-valued probability measure
defined for each subset in
, must
be consistent? In other words, is there always an ordinary finitely-additive probability measure
such that for all
, we have
?
If are a sequence of random variables, then define the information proportion of a subset
to be
. Then the assignment
is an interval-valued probability measure on
.