arXiv subjects

Andreas E. Kyprianou

Publications and source records attributed to Andreas E. Kyprianou.

At least 19 recordsLinked to original sources

arXiv2026

Critical non-local spatial branching processes with infinite variance conditioned on survival

We consider the setting of either a general non-local branching particle process or a general non-local superprocess. Under the assumption that the mean semigroup has a Perron-Frobenious type behaviour in combination with a regularly varying assumption on the reproductive point process, which permits infinite second moments, we consider sufficient conditions that ensure limiting distributional stability when conditioned on survival at criticality. We offer two main results. Under the aforesaid conditions, our first main contribution establishes the polynomial decay in time of the survival probability in the spirit of a classical Kolmogorov limit. The second main contribution pertains to the stability, when conditioning on survival, in the spirit of a Yaglom limit. In both cases our proofs work equally well for the analogous setting of superprocesses with non-local branching. Our results complete a series of articles for various families of non spatial branching processes from the 1950s-1970s as well complementing a recent result of this type for spatial branching processes of Ren, Song and Sun (2020). The generality of our results improve on older work of Hering and Hoppe (1981) and Asmussen and Hering (1983) who dealt with a similar context for branching particle systems, as well as providing a general framework for non-local superprocesses.

math.PR↗

arXiv2026

SDE-based Monte Carlo dose calculation for proton therapy validated against Geant4

Objective: To assess the accuracy and computational performance of a stochastic differential equation (SDE)--based model for proton beam dose calculation by benchmarking against Geant4 in simplified phantom geometries. Approach: Building on Crossley et al. (2025), we implemented the SDE model using standard approximations to interaction cross sections and mean excitation energies, enabling straightforward adaptation to new materials and configurations. The model was benchmarked against Geant4 in homogeneous, longitudinally heterogeneous and laterally heterogeneous phantoms to assess depth--dose behaviour, lateral transport and material heterogeneities. Main results: Across all phantoms and beam energies, the SDE model reproduced the main depth--dose characteristics predicted by Geant4, with proton range agreement within 0.2 mm for 100 MeV beams and 0.6 mm for 150 MeV beams. Voxel--wise comparisons yielded gamma pass rates exceeding 95% under 2%/0.5 mm criteria with a 1% dose threshold. Differences were localised to steep dose gradients or material interfaces, while overall lateral beam dispersion was well reproduced. The SDE model achieved speed-up factors of about 2.5--3 relative to single-threaded Geant4. Significance: The SDE approach reproduces key dosimetric features with good accuracy at lower computational cost and is amenable to parallel and GPU implementations, supporting fast proton therapy dose calculations.

physics.med-ph↗

arXiv2025

A Unified Framework from Boltzmann Transport to Proton Treatment Planning

This work develops a rigorous mathematical formulation of proton transport by integrating both deterministic and stochastic perspectives. The deterministic framework is based on the Boltzmann-Fokker-Planck equation, formulated as an operator equation in a suitable functional setting. The stochastic approach models proton evolution via a track-length parameterised diffusion process, whose infinitesimal generator provides an alternative description of transport. A key result is the duality between the stochastic and deterministic formulations, established through the adjoint relationship between the transport operator and the stochastic generator. We prove that the resolvent of the stochastic process corresponds to the Green's function of the deterministic equation, providing a natural link between fluence-based and particle-based transport descriptions. The theory is applied to dose computation, where we show that the classical relation: dose = (fluence * mass stopping power) arises consistently in both approaches. Building on this foundation, we formulate a hybrid optimisation framework for treatment planning, in which dose is computed using a stochastic model while optimisation proceeds via adjoint-based PDE methods. We prove existence and differentiability of the objective functional and derive the first-order optimality system. This framework bridges stochastic simulation with deterministic control theory and provides a foundation for future work in constrained, adaptive and uncertainty-aware optimisation in proton therapy.

math.PR↗

arXiv2025

Norm-dependent Lamperti-type MAP representations of stable processes and Brownian motions in the orthant

We start by remarking a one-to-one correspondence between self-similar Markov processes (ssMps) on a Banach space and Markov additive processes (MAPs) that is analogous to the well-known one between positive ssMps and Lévy processes through the renowned Lamperti-transform, with the main difference that ours is norm-dependent. We then consider multidimensional self-similar Markov processes obtained by killing or by reflecting a stable process or Brownian motion in the orthant and we then fully describe the MAPs associated to them using the $L_1$-norm. Namely, we describe the MAP underlying the ssMp obtained by killing a $d$-dimensional $α$-stable process when it leaves the orthant and the one obtained by reflecting it back in the orthant continuously (or by a jump); finally, we also describe the MAP underlying $d$-dimensional Brownian motion reflected in the orthant. The first three of the aforementioned examples are pure-jump, and the last is a diffusion, so their characterization is given through their Lévy system, generator and/or through the modulated SDE that defines them, respectively.

math.PR↗

arXiv2025

The strong law of large numbers and a functional central limit theorem for general Markov additive processes

In this note we re-visit the fundamental question of the strong law of large numbers and central limit theorem for processes in continuous time with conditional stationary and independent increments. For convenience we refer to them as Markov additive processes, or MAPs for short. Historically used in the setting of queuing theory, MAPs have often been written about when the underlying modulating process is an ergodic Markov chain on a finite state space. Recent works have addressed the strong law of large numbers when the underlying modulating process is a general Markov processes. We add to the latter with a different approach based on an ergodic theorem for additive functionals and on the semi-martingale structure of the additive part. This approach also allows us to deal with the setting that the modulator of the MAP is either positive or null recurrent. The methodology additionally inspires a CLT-type result.

math.PR↗

arXiv2024

Jump stochastic differential equations for the characterisation of the Bragg peak in proton beam radiotherapy

Proton beam radiotherapy stands at the forefront of precision cancer treatment, leveraging the unique physical interactions of proton beams with human tissue to deliver minimal dose upon entry and deposit the therapeutic dose precisely at the so-called Bragg peak, with no residual dose beyond this point. The Bragg peak is the characteristic maximum that occurs when plotting the curve describing the rate of energy deposition along the length of the proton beam. Moreover, as a natural phenomenon, it is caused by an increase in the rate of nuclear interactions of protons as their energy decreases. From an analytical perspective, Bortfeld proposed a parametric family of curves that can be accurately calibrated to data replicating the Bragg peak in one dimension. We build, from first principles, the very first mathematical model describing the energy deposition of protons. Our approach uses stochastic differential equations and affords us the luxury of defining the natural analogue of the Bragg curve in two or three dimensions. This work is purely theoretical and provides a new mathematical framework which is capable of encompassing models built using Geant4 Monte Carlo, at one extreme, to pencil beam calculations with Bortfeld curves at the other.

physics.med-ph↗

arXiv2024

$α$-stable Lévy processes entering the half space or a slab

Recent fluctuation identities for $α$-stable Lévy processes have decomposed paths using generalised spherical polar coordinates revealing an underlying Markov Additive Process (MAP) for which a more advanced form of excursion theory can be exploited. Inspired by this approach, we give a different decomposition of the $d$-dimensional isotropic $α$-stable Lévy processes in terms of orthogonal coordinates. Accordingly we are able to develop a number of $n$-tuple laws for first entrance into a half-space. We also numerically construct the law of first entry of the process into a slab of the form $(-1, 1)\times \mathbb{R}^{d-1}$ using a walk-on-half-spaces Monte Carlo approach.

math.PR↗

arXiv2024

Stability of (sub)critical non-local spatial branching processes with and without immigration

We consider the setting of either a general non-local branching particle process or a general non-local superprocess, in both cases, with and without immigration. Under the assumption that the mean semigroup has a Perron-Frobenious type behaviour for the immigrated mass, as well as the existence of second moments, we consider necessary and sufficient conditions that ensure limiting distributional stability. More precisely, our first main contribution pertains to proving the asymptotic Kolmogorov survival probability and Yaglom limit for critical non-local branching particle systems and superprocesses under a second moment assumption on the offspring distribution. Our results improve on existing literature by removing the requirement of bounded offspring in the particle setting [21] and generalising [43] to allow for non-local branching mechanisms. Our second main contribution pertains to the stability of both critical and sub-critical non-local branching particle systems and superprocesses with immigration. At criticality, we show that the scaled process converges to a Gamma distribution under a necessary and sufficient integral test. At subcriticality we show stability of the process, also subject to an integral test. In these cases, our results complement classical results for (continuous-time) Galton-Watson processes with immigration and continuous-state branching processes with immigration; see [22,40,42,48,51], among others. In the setting of superprocesses, the only work we know of at this level of generality is summarised in [34]. The proofs of our results, both with and without immigration, appeal to similar technical approaches and accordingly, we include the results together in this paper.

math.PR↗

arXiv2024

Limit theorems for the neutron transport equation

Over the last decade, ingenuous developments in Monte Carlo methods have enabled the unbiased estimation of adjoint-weighted reactor parameters expressed as bilinear forms, such as kinetics parameters and sensitivity coefficients. A prominent example is the Iterated Fission Probability method, which relies on the simulation of the fission chains descending from an ancestor neutron: the neutron population at an asymptotic fission generation yields an estimate of the importance function (and hence of the adjoint fundamental eigenmode) at the phase-space coordinates of the ancestor neutron. In this paper we first establish rigorous results concerning the moments of the asymptotic neutron population stemming from a single initial particle, with special focus on the average and the variance. Then, we propose a simple benchmark configuration where exact solutions are derived for these moments, which can be used for the verification of new functionalities of production Monte Carlo codes involving the Iterated Fission Probability method.

physics.comp-ph↗

arXiv2023

A Bayesian Inverse Approach to Proton Therapy Dose Delivery Verification

This study presents a proof-of-concept for a novel Bayesian inverse method in a one-dimensional setting, aimed at proton beam therapy treatment verification. Our methodology is predicated on a hypothetical scenario wherein strategically positioned sensors detect prompt-γ's emitted from a proton beam when it interacts with defined layers of tissue. Using this data, we employ a Bayesian framework to estimate the proton beam's energy deposition profile. We validate our Bayesian inverse estimations against a closed-form approximation of the Bragg Peak in a uniform medium and a layered lung tumour.

stat.AP↗

arXiv2022

Many-to-few for non-local branching Markov process

We provide a many-to-few formula in the general setting of non-local branching Markov processes. This formula allows one to compute expectations of k-fold sums over functions of the population at k different times. The result generalises [14] to the non-local setting, as introduced in [11] and [8]. As an application, we consider the case when the branching process is critical, and conditioned to survive for a large time. In this setting, we prove a general formula for the limiting law of the death time of the most recent common ancestor of two particles selected uniformly from the population at two different times, as t tends to infinity. Moreover, we describe the limiting law of the population sizes at two different times, in the same asymptotic regime.

math.PR↗

arXiv2022

Multitype $Λ$-coalescents

Consider a multitype coalescent process in which each block has a colour in $\{1,\ldots,d\}$. Individual blocks may change colour, and some number of blocks of various colours may merge to form a new block of some colour. We show that if the law of a multitype coalescent process is invariant under permutations of blocks of the same colour, has consistent Markovian projections, and has asychronous mergers, then it is a multitype $Λ$-coalescent: a process in which single blocks may change colour, two blocks of like colour may merge to form a single block of that colour, or large mergers across various colours happen at rates governed by a $d$-tuple of measures on the unit cube $[0,1]^d$. We go on to identify when such processes come down from infinity. Our framework generalises Pitman's celebrated classification theorem for singletype coalescent processes, and provides a unifying setting for numerous examples that have appeared in the literature including the seed-bank model, the island model and the coalescent structure of continuous-state branching processes.

math.PR↗

arXiv2022

Yaglom limit for critical neutron transport

We consider the classical Yaglom limit theorem for a branching Markov process $X = (X_t, t \ge 0)$, with non-local branching mechanism in the setting that the mean semigroup is critical, i.e. its leading eigenvalue is zero. In particular, we show that there exists a constant $c(f)$ such that \[ {\rm Law}\left(\frac{\langle f, X_t\rangle}{t} \bigg| \langle 1, X_t\rangle > 0 \right) \to {\mathbf e}_{c(f)}, \qquad t \to \infty, \] where ${\mathbf e}_{c(f)}$ is an exponential random variable with rate $c(f)$ and the convergence is in distribution. As part of the proof, we also show that the probability of survival decays inversely proportionally to time. Although Yaglom limit theorems have recently been handled in the setting of branching Brownian motion in a bounded domain and superprocesses, \cite{Ellen, Yanxia}, these results do not allow for non-local branching, which complicates the analysis. Our approach and the main novelty of this work is based around a precise result for the scaled asymptotics for the $k$-th martingale moments of $X$ (rather than the Yaglom limit itself). We then illustrate our results in the setting of neutron transport, for which the non-locality is essential, complementing recent developments in this domain \cite{SNTE, SNTEII, SNTEIII, MCNTE, MultiNTE}.

math.PR↗

arXiv2021

Monte-Carlo Methods for the Neutron Transport Equation

This paper continues our treatment of the Neutron Transport Equation (NTE) building on the work in [arXiv:1809.00827v2], [arXiv:1810.01779v4] and [arXiv:1901.00220v3], which describes the flux of neutrons through inhomogeneous fissile medium. Our aim is to analyse existing and novel Monte Carlo (MC) algorithms, aimed at simulating the lead eigenvalue associated with the underlying model. This quantity is of principal importance in the nuclear regulatory industry for which the NTE must be solved on complicated inhomogenous domains corresponding to nuclear reactor cores, irradiative hospital equipment, food irradiation equipment and so on. We include a complexity analysis of such MC algorithms, noting that no such undertaking has previously appeared in the literature. The new MC algorithms offer a variety of advantages and disadvantages of accuracy vs cost, as well as the possibility of more convenient computational parallelisation.

math.PR↗

arXiv2021

An optimal stopping problem for spectrally negative Markov additive processes

Previous authors have considered optimal stopping problems driven by the running maximum of a spectrally negative Lévy process $X$, as well as of a one-dimensional diffusion. Many of the aforementioned results are either implicitly or explicitly dependent on Peskir's maximality principle. In this article, we are interested in understanding how some of the main ideas from these previous works can be brought into the setting of problems driven by the maximum of a class of Markov additive processes (more precisely Markov modulated Lévy processes). Similarly to previous works in the Lévy setting, the optimal stopping boundary is characterised by a system of ordinary first-order differential equations, one for each state of the modulating component of the Markov additive process. Moreover, whereas scale functions played an important role in the previously mentioned work, we work instead with scale matrices for Markov additive processes here. We exemplify our calculations in the setting of the Shepp-Shiryaev optimal stopping problem, as well as a family of capped maximum optimal stopping problems.

math.PR↗

arXiv2021

Attraction to and repulsion from a subset of the unit sphere for isotropic stable Lévy processes

Taking account of recent developments in the representation of $d$-dimensional isotropic stable Lévy processes as self-similar Markov processes, we consider a number of new ways to condition its path. Suppose that $Ω$ is a region of the unit sphere $\mathbb{S}^{d-1} = \{x\in \mathbb{R}^d: |x| =1\}$. We construct the aforesaid stable Lévy process conditioned to approach $\mathsf{S}$ continuously from either inside or outside of the sphere. Additionally, we show that %this these processes are in duality with the stable process conditioned to remain inside the sphere and absorb continuously at the origin and to remain outside of the sphere, respectively. Our results extend the recent contributions of Döring and Weissman (2018),, where similar conditioning is considered, albeit in one dimension. As is the case there, we appeal to recent fluctuation identities related to the deep factorisation of stable processes.

math.PR↗

arXiv2021

The Doob-McKean identity for stable Lévy processes

We re-examine the celebrated Doob--McKean identity that identifies a conditioned one-dimensional Brownian motion as the radial part of a 3-dimensional Brownian motion or, equivalently, a Bessel-3 process, albeit now in the analogous setting of isotropic $α$-stable processes. We find a natural analogue that matches the Brownian setting, with the role of the Brownian motion replaced by that of the isotropic $α$-stable process, providing one interprets the components of the original identity in the right way.

math.PR↗

arXiv2020

Oscillatory attraction and repulsion from a subset of the unit sphere or hyperplane for isotropic stable Lévy processes

Suppose that $\mathsf{S}$ is a closed set of the unit sphere $\mathbb{S}^{d-1} = \{x\in \mathbb{R}^d: |x| =1\}$ in dimension $d\geq2$, which has positive surface measure. We construct the law of absorption of an isotropic stable Lévy process in dimension $d\geq2$ conditioned to approach $\mathsf{S}$ continuously, allowing for the interior and exterior of $\mathbb{S}^{d-1}$ to be visited infinitely often. Additionally, we show that this process is in duality with the underlying stable Lévy process. We can replicate the aforementioned results by similar ones in the setting that $\mathsf{S}$ is replaced by $\mathsf{D}$, a closed bounded subset of the hyperplane $\{x\in\mathbb{R}^d : (x, v) = 0\}$ with positive surface measure, where $v$ is the unit orthogonal vector and where $(\cdot,\cdot )$ is the usual Euclidean inner product. Our results complement similar results of the authors Kyprianou, Palau and Saizmaa (2020) in which the stable process was further constrained to attract to and repel from $\mathsf{S}$ from either the exterior or the interior of the unit sphere.

math.PR↗