Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 22 min ago
PreprintCC BY-SA 4.0arXiv

Distinguishing sets and measures from their planar Brownian images

Abstract

Motivated by a question of Hochman, we investigate whether two deterministic time measures or time sets can be distinguished almost surely from a single planar Brownian image. Using rescaled correlation integrals, we give a criterion for mutual singularity of the laws of the image measures, even when the time measures have the same dimension. For self-similar time sets satisfying the open set condition, we also recover the natural occupation measure from the compact image. Together, these results allow us to distinguish lattice and non-lattice self-similar sets and their natural measures within this class. For a naturally parametrised family with two contractions, with fixed dimension, each parameter can be distinguished from all but finitely many others. If the dimension is sufficiently small, every distinct parameter can be distinguished. The results are formalised in Lean.

Related

  1. A threshold for full packing dimension of Hölder images of sets and measures
    Nicolas Angelini
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsProbabilityarXiv
  2. PERSISTENCE OF THE WIENER SAUSAGE: SAMPLING STABILITY AND LIMIT THEOREMS FOR BETTI-CURVE FUNCTIONALS OF DRIFTED PLANAR BROWNIAN MOTION
    Tristan Guillaume
    HALPreprintPublisher termsFull textProbabilityHAL
  3. Coverage probability of the planar Brownian convex hull
    Zakhar Kabluchko
    arXivPreprintarXiv licenceFull textProbabilityarXiv
  4. Generalized Images for Brownian First Passage to Monomial Boundaries
    Gerardo Hernández-del-Valle
    arXivPreprintCC BY-NC-ND 4.0Full textProbabilityarXiv
  5. Hearing the heat: a proof-of-concept study of nonlinear sound measures for distinguishing phases of rapid organic decomposition
    Jakob Eisenhauer
    EarthArXivPreprintCC BY 4.0Full textEnvironmental science & pollutionHydrology & soilsEarthArXiv
BibTeX
@misc{troscheit2026distinguishing,
  title = {{Distinguishing sets and measures from their planar Brownian images}},
  author = {Sascha Troscheit},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.16339},
  eprint = {2610.16339},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.16339},
  note = {CC BY-SA 4.0},
}
RIS
TY  - UNPB
TI  - Distinguishing sets and measures from their planar Brownian images
AU  - Sascha Troscheit
PY  - 2026
DA  - 2026/10/15
PB  - arXiv
DO  - 10.48550/arxiv.2610.16339
UR  - https://arxiv.org/abs/2610.16339
AB  - Motivated by a question of Hochman, we investigate whether two deterministic time measures or time sets can be distinguished almost surely from a single planar Brownian image. Using rescaled correlation integrals, we give a criterion for mutual singularity of the laws of the image measures, even when the time measures have the same dimension. For self-similar time sets satisfying the open set condition, we also recover the natural occupation measure from the compact image. Together, these results allow us to distinguish lattice and non-lattice self-similar sets and their natural measures within this class. For a naturally parametrised family with two contractions, with fixed dimension, each parameter can be distinguished from all but finitely many others. If the dimension is sufficiently small, every distinct parameter can be distinguished. The results are formalised in Lean.
ER  -