Towards Hyperbolic SIRGs - Refining Exhausting Subspaces
2026-08-30
These notes detail an exploration into the first steps that are necessary to extend the framework developed in my bachelor thesis to allow it to handle spatial inhomogeneous random graphs (SIRGs) on Hyperbolic spaces natively, specifically focusing on the immediate changes that must be made to the exhaustive subspaces approach to accommodate hyperbolic spaces. They have been designed with care but I do not claim full formal correctness of each and every detail. This document should be seen as a sketch into a possible direction that could be formally pursued at a later point.
Brief Overview of the Subspaces Approach
I will briefly recall the classical torus SIRG setting of this paper. Focusing on the one dimensional case, the authors place
This produces finite random graphs
Equivalently, increasingly large observation windows approximate the infinite model: the graph seen from a uniformly chosen finite vertex converges in distribution to the graph seen from the Palm root at the origin. If instead one places
My thesis replaces boxes by homogeneous compact approximants, such as tori, because these interact cleanly with Palm theory. In the Euclidean case the box and torus constructions should be asymptotically equivalent, since boundary-wrapping effects become negligible as the volume grows (since it is a Følner style exhaustion of
The thesis then generalizes this construction through what I call a
exhausts set-wise. - The inclusions
are measurable. - Each
is compact and homogeneous under a transitive isometric group action. - The metrics on
converge suitably to the ambient metric, together with a radial compactness condition.
Under these assumptions, Section 6 establishes local weak convergence of suitable SIRGs on
This extends the torus construction to non-Euclidean examples such as
A Cleaner Group-Theoretic Formulation
In the thesis, a distinction was made between
Given an unbounded1 proper metric space
- For all compact
, eventually in ; - For all
, , and these groups are nice2 enough to ensure that is a compact metric quotient of ; - It holds that
.
By injectivity radius here we mean the smallest scale at which the quotient identifications become visible, i.e. the radius before one encounters the nearest non-trivial "wraparound''. More precisely, for
with
Effectively, this is the type of procedure that generates us a sequence of "torus-like" quotients on which to place our finite approximating graphs. To recover the case of the tori in
and to recover the case of the
For hyperbolic space, we just need to find a sufficiently nice sequence of isometry subgroups. In
where
These are discrete, cocompact, properly discontinuous subgroups of the isometry group of
is a compact quotient exhaustion of
Notes on the Conditions
This will not be an enumerative list of every role the conditions play, but a quick collection of insights. Let's go one by one. The first condition (in combination with unboundedness of the space) ensures that the
The third condition ensures that, asymptotically, balls of any given radius around any point in the quotient space are indistinguishable from balls in the ambient space of the same radius. This is what ensures that quotients can be compared with vertex processes that live in
However it should be noted hyperbolic space has no Følner exhaustion, so we cannot asymptotically equate hyperbolic compact quotient exhaustions with their corresponding Dirichlet fundamental domains in the same way we did in
But Wait! Not Yet!
There is still one large glaring issue. This reformulation does not give us hyperbolic SIRGs. Not even close. The issue is that there is no compact quotient exhaustion of
I think it is important to view this as something that shortens our work in the other cases. If we instead consider a compact homogeneous quotient exhaustion, essentially adding the condition that every
It is likely that the next steps are thus to find a way to transfer uniform root selection from the quotients to the ambient space. Because injectivity radius tends to infinity, our boundary effects diminish, and thus it is possible that some averaged Palm distribution against the intensity of point occurrences or other approach could still give us a fixed base root in the ambient space.
Alternatively, perhaps some sort of kernel-level convergence of the Palm laws
would suffice (under some identification of points
Even still, it is clear that this formulation naturally fits hyperbolic spaces better than the original. I am not guaranteeing that it is the correct formulation until I have done the proof work, but it is a better direction to work from.