The cut norm is invariant under measure-preserving pullback #
If f : Ω' → Ω pushes a probability measure ν forward to μ, then a symmetric kernel K on
(Ω, μ) and its pullback K.comap f on (Ω', ν) have the same cut norm.
One inequality is elementary and already available: a measurable rectangle downstairs pulls back to
one upstairs with the same integral, so cutNorm μ K ≤ cutNorm ν (K.comap f)
(cutNorm_le_cutNorm_comap). The reverse inequality is the substance of this file, and it is not
elementary: a rectangle S × T upstairs need not be the preimage of anything, so its integral must
be pushed down rather than transported. The push is by conditional density: the part of ν
carried by S pushes forward to a measure below μ, whose Radon–Nikodym derivative
mapRestrictDensity f ν μ S is a [0, 1]-valued function on Ω, and the rectangle integral
upstairs
equals the pairing of K against the two densities (rectIntegral_comap_eq_testIntegral). Since
the cut norm already dominates every [0, 1]-test integral with no loss of constant
(abs_testIntegral_le_cutNorm), the bound follows.
Why the [0, 1]-test form is the right input. Replacing it by the signed cut norm would cost a
factor of 4 (cutNormSigned_le_four_mul_cutNorm) and give only a comparison, not an equality;
the sharp abs_testIntegral_le_cutNorm is what makes the invariance exact.
This is the analytic gate in front of the arbitrary-carrier triangle inequality for the cut distance (Janson, Lemma 6.5). There a coupling of three carriers is built over the middle one, and the two outer cut norms have to be compared with cut norms computed on the glued space along its coordinate projections; those projections are measure preserving, and the comparison needed is exactly the direction proved here. The triangle inequality itself is not proved in this file.
Main results #
TauCeti.DenseGraphLimits.SymmKernel.rectIntegral_comap_eq_testIntegral— a rectangle integral of a pullback is a[0, 1]-test integral of the original kernel.TauCeti.DenseGraphLimits.cutNorm_comap_le— the cut norm does not increase under measure-preserving pullback.TauCeti.DenseGraphLimits.cutNorm_comap— hence it is invariant.
References #
- S. Janson, Graphons, cut norm and distance, couplings and rearrangements, NYJM Monographs 4 (2013), §4 and Lemma 6.5.
- L. Lovász, Large Networks and Graph Limits, AMS Colloquium Publications 60 (2012), §8.2.
- Roadmap:
TauCetiRoadmap/DenseGraphLimits/README.md, Layer 1 — the cut norm and its full basic API, as the prerequisite named there for the arbitrary-carrier triangle inequality.
A rectangle integral upstairs is a [0, 1]-test integral downstairs. Integrating a
pullback over S × T weights each point of the base by the conditional density of S, resp. T,
above it.
This is the transport that replaces rectIntegral_comap_preimage when the rectangle upstairs is
not a preimage: instead of moving the rectangle, it moves the two indicators, which become the
[0, 1]-valued densities mapRestrictDensity f ν μ S and mapRestrictDensity f ν μ T. Neither set
needs to be
measurable.
The cut norm does not increase under measure-preserving pullback. This is the direction that a change of variables cannot give, since a rectangle upstairs need not come from one downstairs.
Every rectangle integral upstairs is a [0, 1]-test integral of K downstairs
(rectIntegral_comap_eq_testIntegral), and the cut norm dominates those with no loss of constant
(abs_testIntegral_le_cutNorm).
The cut norm is invariant under measure-preserving pullback. Pulling a kernel back along a map from any carrier that maps measure preservingly onto the kernel's own carrier leaves its cut norm unchanged.
The two inequalities have different characters: cutNorm_le_cutNorm_comap transports rectangles
along the map, while cutNorm_comap_le pushes them down by conditional density.