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Maroussia Slavtchova-Bojkova

Publications and source records attributed to Maroussia Slavtchova-Bojkova.

5 recordsLinked to original sources

Occupation-Time Fluctuations of an Age-Dependent Branching System Driven by Poisson Immigration

We study the occupation-time fluctuations of a critical age-dependent branching particle system with immigration in $\mathbb{R}^d$. Immigrants arrive according to a homogeneous Poisson random measure in space and time. Each particle moves independently according to a symmetric $α$-stable process and, at the end of its lifetime, either dies or splits into two offspring with equal probability. The lifetime distribution is allowed to have either finite mean or a heavy tail of index $γ\in(0,1]$. We investigate the asymptotic behavior of the centered occupation-time process under a suitable space-time scaling. Assuming $ α<d<(1+γ)α, $ we prove that the rescaled occupation-time fluctuations weakly converge as processes with values in the space of tempered distributions to a centered Gaussian process with an explicitly identified covariance structure. The normalization and the covariance depend on both the stability index $α$ and the tail exponent $γ$. The limiting process is self-similar, possesses long-range dependence, and is neither Markovian nor a semimartingale. In contrast with the corresponding age-dependent branching system without immigration, the contribution of the initial population vanishes in the limit, and the asymptotic fluctuations are entirely determined by the immigration mechanism. When $γ=1$, our results recover the covariance structure previously obtained for branching systems with immigration and finite-mean lifetimes. The proofs rely on the space-time random field approach, Fourier analytic techniques, and asymptotic properties of renewal functions associated with the lifetime distribution.

math.PR↗

Multi-type branching processes with immigration generated by point processes

Following the pivotal work of Sevastyanov, who considered branching processes with homogeneous Poisson immigration, much has been done to understand the behaviour of such processes under different types of branching and immigration mechanisms. Recently, the case where the times of immigration are generated by a non-homogeneous Poisson process was considered in depth. In this work, we try to demonstrate how one can use the framework of point processes in order to go beyond the Poisson process. As an illustration, we show how to transfer techniques from the case of Poisson immigration to the case where it is spanned by a determinantal point process.

math.PR↗

Transformation of the discrete stable process via branching reproduction environment

The current paper focuses on studying the impact of immigration with an infinite mean, driven by a discrete-stable compound Poisson process, when it is entering the branching environment with infinite variance of reproduction. Our goal is to determine the explicit form of the probability generating function and subsequently to analyze the probability of extinction, aiming to understand the long-term behavior of such processes.

math.PR↗

Computational modelling of cancer evolution by multi-type branching processes

Metastasis, the spread of cancer cells from a primary tumor to secondary location(s) in the human organism, is the ultimate cause of death for the majority of cancer patients. That is why, it is crucial to understand metastases evolution in order to successfully combat the disease. We consider a metastasized cancer cell population after medical treatment (e.g. chemotherapy). Arriving in a different environment the cancer cells may change their lifespan and reproduction, thus they may proliferate into different types. If the treatment is effective, in the context of branching processes it means, the reproduction of cancer cells is such that the mean offspring of each cell is less than one. However, it is possible mutations to occur during cell division cycle. These mutations can produce a new cancer cell type, which is resistant to the treatment. Cancer cells from this new type may lead to the rise of a non-extinction branching process. The above scenario leads us to the choice of a reducible multi-type age-dependent branching process as a relevant framework for studying the asymptotic behavior of such complex structures. Our previous theoretical results are related to the asymptotic behavior of the waiting time until the first occurrence of a mutant starting a non-extinction process and the modified hazard function as a measure of immediate recurrence of cancer disease. In the present paper these asymptotic results are used for developing numerical schemes and algorithms implemented in Python via the NumPy package for approximate calculation of the corresponding quantities. In conclusion, our conjecture is that this methodology can be advantageous in revealing the role of the lifespan distribution of the cancer cells in the context of cancer disease evolution and other complex cell population systems, in general.

q-bio.PE↗

Stochastic monotonicity and continuity properties of functions defined on Crump-Mode-Jagers branching processes, with application to vaccination in epidemic modelling

This paper is concerned with Crump-Mode-Jagers branching processes, describing spread of an epidemic depending on the proportion of the population that is vaccinated. Births in the branching process are aborted independently with a time-dependent probability given by the fraction of the population vaccinated. Stochastic monotonicity and continuity results for a wide class of functions (e.g., extinction time and total number of births over all time) defined on such a branching process are proved using coupling arguments, leading to optimal vaccination schemes to control corresponding functions (e.g., duration and final size) of epidemic outbreaks. The theory is illustrated by applications to the control of the duration of mumps outbreaks in Bulgaria.

math.ST↗