Search arXiv⌕ Search

arXiv · 2609.36269

Exit problems for additive-increase and multiplicative-decrease Markov-modulated processes

Abstract

We study one-sided, two-sided and reflected exit problems for a finite-state Markov-modulated additive-increase and multiplicative-decrease process. For upward passage, a first-jump decomposition and a spatial Laplace transform lead to a recursion indexed by finite words of phases and to a convergent Green series. For downward passage, the first-jump operator is a strict contraction and the known contribution from $[p_i b,b]$ becomes an explicit boundary forcing term in the same spatial recursion. These allow to derive the corresponding Green representation of the first passage matrix and its finite-dimensional compatibility condition. The derivation of the two-sided exit identity is based on the Markov property, which in this context is equivalent to the cocycle property of the Laplace transform, together with the recursive equation at the upper level. For reflection at the running infimum, a finite $\bar p$-geometric method of steps realizes a certain Picard map that allows to find the exit matrix. As a result, we construct a Doob martingale related to the first passage time of the reflected Markov-modulated AIMD.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bernardo D'Auria, Zbigniew Palmowski. 2026-09-28. Exit problems for additive-increase and multiplicative-decrease Markov-modulated processes. https://arxiv.org/abs/2609.36269

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Pairwise Negative Correlation for Uniform Spanning Subgraphs of the Complete Graph

We study pairwise negative correlation for three families of uniform spanning-subgraph measures on the complete graph. In Part~I, we consider the uniform probability measure on connected spanning subgraphs and prove pairwise negative correlation for all sufficiently large complete graphs. In Part~II, we study the uniform measure on spanning forests with a prescribed number of connected components and prove pairwise negative correlation for every fixed number of components when the number of vertices is sufficiently large. In Part~III, we consider connected spanning subgraphs with prescribed excess and establish the analogous result for every fixed excess. The three parts are self-contained and are intended as separate manuscripts.

math.PR↗

Naturality characterizes product measures and relative product measures

We show that the formation of the product measure is the only natural way to assign to each tuple of probability measures on measurable spaces a probability measure on the product space. Here, naturality is meant in the sense of category theory and amounts to the condition that the assignment commutes with pushforward along measurable maps. In the standard Borel setting, we also prove an analogous result for relative products over a fixed base probability space. As a corollary, we conclude that the formation of relative products is a lax symmetric monoidal functor.

math.PR↗

A Dimension-Free Bound on the Poincaré Constant of Isotropic Log-Concave Measures

The Kannan--Lovász--Simonovits (KLS) conjecture asserts that isotropic log-concave probability measures have Poincaré constants bounded by a universal constant, independently of dimension. We give a deterministic variational proof with an explicit bound on the Poincaré constant $C_P(μ)\le25$, where $μ$ is any isotropic log-concave probability measure. Starting from elliptic moment estimates and a quadratic variance inequality, we establish geometric bounds on normalized Appell coefficient norms through \emph{joint} maximization over the measure and test function. Variation of the measure gives a maximum-principle inequality, while stationarity in the test function controls the highest-order cumulant terms. Two concave barriers constructed from quadratic and cubic polynomials close the induction. A weighted Helmholtz--Hodge decomposition then controls the curl correction of weighted divergence, yielding a curvature estimate for compatible symmetric tensor fields that is uniform in rank. Quadratic duality converts this estimate into an operator comparison for centered integration, linking the coefficient bounds to control of the inverse gradient. A spectral-radius estimate and a scalar growth inequality for adjoint iterates then yield the Poincaré bound. The final estimate is independent of the auxiliary positive curvature, allowing approximation to complete the proof for general isotropic log-concave measures.

math.PR↗