Inverse of the Gaussian multiplicative chaos: an integration by parts formula
Tomas Kojar
TL;DR
This paper explores an integration by parts formula related to Gaussian multiplicative chaos (GMC) and its inverse, extending previous work on Gaussian processes to new mathematical structures.
Contribution
It introduces a novel integration by parts formula for GMC and its inverse, advancing theoretical understanding of these stochastic processes.
Findings
Derived an integration by parts formula for GMC and its inverse
Extended classical Gaussian process results to multiplicative chaos context
Provides new tools for analyzing GMC-related stochastic models
Abstract
In this article, we study the analogue of the integration by parts formula from "Hitting times for Gaussian processes" in the context of GMC and its inverse.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · advanced mathematical theories · Quantum chaos and dynamical systems