In the mathematical modeling of many processes and phenomena in the Sciences and Technology one employs systems with many random particles and interactions; see the Application Theme Particlebased modelling in the Sciences. Here we mean many different types of such systems, which, depending on the application, contain moving or static particles, have interactions with each other or with a (possibly random) surrounding medium, have attracting or repelling forces, etc. Also the mathematical questions that we have about the system are quite diverse, e.g., for an emerging cluster structure, for regularities within the clusters, for properties like percolation, crystallization or condensation, for temporal development of the contacts of the particles with each other, for dependencies of the global behavior on parameters, to the point of phase transitions, and more.
In most of the models considered there is one or more order parameters, in terms of which one well expresses the macroscopic behavior, like the average size of a cluster, the occupation probabilities of the particles at a given site at a given time, the empirical mean of all the particles, etc. In some cases, these order parameters satisfy deterministic equations (e.g. differential equations) in the limit considered (often large number of particles or late times), which can afterwards be studied with the help of analytic or numeric methods. In other cases, formulae are derived for the limiting free energy or for laws of large numbers or for ergodic theorems.
For answering these questions and for finding and derivation of formulae, at WIAS mathematical tools and concepts are usually employed and (if not yet available) developed. Stochastic and analytic methods are combined, and in the best case a mathematical solution is derived. Accompanying simulations give visualizations and produce explicit data. Examples of mathematical theories employed are, depending on the model, Gibbs measures, percolation, stochastic (partial) differential equations, Markov processes, and large deviations on the stochastic side, and weak convergence, calculus of variations, convex analysis and partial differential equations on the analytic side.
Contribution of the Institute
Here is a selection of some of the mathematical achievements of the WIAS, see also the Application Theme Particlebased modelling in the Sciences.
A (static) interacting manybody system is given if a large number of points are randomly distributed in a large box, such that they do not accumulate and such that a certain energy is given to the configuration as an exponential probability weight. In this way, a probability measure on configurations is given. The energy term carries a prefactor, the inverse temperature. In the FG5, the thermodynamic limit at low temperatures in particularly large boxes was studied, such that the entropy (the part of the probability that comes from the spatial distribution of the particle cloud) has a particular relation with the energy and the free energy depends on just one parameter. Interesting phase transitions could be obtained. In the future, however, the usual thermodynamic limit will be studied, where the box volume has a fixed relation to the particle number. For a system in which each particle also carries a kinetic energy and the cloud is subject to some symmetry condition, an ansatz with large deviations for a meanfield version of the entire particle system was developed and was used for expressing the free energy in terms of a variational formula. However, the desired effect of a condensation could not be proved in this way, and future investigations will be made.
In telecommunication, the locations of many users are usually modeled as the points of a spatial Poisson point process, see the Application Theme Mobile Communication Networks. Each two of these points interact if their distance is small enough. The question of the probability with which many messages, which are sent through the system via a system of relays, actually reach their intended receiver was studied. That is, a global connectivity property for the system was studied.
The connectivity property was studied in the limit of a high spatial density of the users per volume, in which case the probabilities decay exponentially. With the help of the theory of large deviations for highly dense point processes, the decay rate was expressed in term of an entropy. Afterwards, those configurations were analyzed that minimize the entropy, as these carry the interpretation of the (random) situations of best connectivity under the assumptions made. Similar investigations were made for interference and capacity properties. Further research currently concerns optimal trajectories of the messages, subject to interference and under avoidance of congestion of the relays, as well as the implementation of realistic movement schemes for the users.
A key task in the case of dynamic models is the establishment of a hydrodynamic limit. Such limits are typically first proved for complete applications in order to find an evolution equation for the macroscopic model properties. For examples see the application oriented themes "Coagulation" and Particlebased modelling in the Sciences. A fundamental part of these proofs is the demonstration of compactness in distribution of the Markov Processes that make up the model. In a number of works, properties of application specific problems have been abstracted and the results generalised so that they can be used in further applications.
In Biology the definition of useful stochastic models is an active topic of research that is far from complete. Established models for populations and their movements include spatial branching processes with random motions, which the WIAS studies in random environments; see the mathematical theme Spectral theory of random operators.
Publications
Monographs

B. Jahnel, W. König, Probabilistic Methods in Telecommunications, D. Mazlum, ed., Compact Textbooks in Mathematics, Birkhäuser Basel, 2020, XI, 200 pages, (Monograph Published), DOI 10.1007/9783030360900 .
Abstract
This textbook series presents concise introductions to current topics in mathematics and mainly addresses advanced undergraduates and master students. The concept is to offer small books covering subject matter equivalent to 2 or 3hour lectures or seminars which are also suitable for selfstudy. The books provide students and teachers with new perspectives and novel approaches. They may feature examples and exercises to illustrate key concepts and applications of the theoretical contents. The series also includes textbooks specifically speaking to the needs of students from other disciplines such as physics, computer science, engineering, life sciences, finance. 
W. König, Große Abweichungen, Techniken und Anwendungen, M. Brokate, A. Heinze , K.H. Hoffmann , M. Kang , G. Götz , M. Kerz , S. Otmar, eds., Mathematik Kompakt, Birkhäuser Basel, 2020, VIII, 167 pages, (Monograph Published), DOI 10.1007/9783030527785 .
Abstract
Die Lehrbuchreihe Mathematik Kompakt ist eine Reaktion auf die Umstellung der Diplomstudiengänge in Mathematik zu Bachelor und Masterabschlüssen. Inhaltlich werden unter Berücksichtigung der neuen Studienstrukturen die aktuellen Entwicklungen des Faches aufgegriffen und kompakt dargestellt. Die modular aufgebaute Reihe richtet sich an Dozenten und ihre Studierenden in Bachelor und Masterstudiengängen und alle, die einen kompakten Einstieg in aktuelle Themenfelder der Mathematik suchen. Zahlreiche Beispiele und Übungsaufgaben stehen zur Verfügung, um die Anwendung der Inhalte zu veranschaulichen. Kompakt: relevantes Wissen auf 150 Seiten Lernen leicht gemacht: Beispiele und Übungsaufgaben veranschaulichen die Anwendung der Inhalte Praktisch für Dozenten: jeder Band dient als Vorlage für eine 2stündige Lehrveranstaltung
Articles in Refereed Journals

L. Andreis, W. König, H. Langhammer, R.I.A. Patterson, A largedeviations principle for all the components in a sparse inhomogeneous random graph, Probability Theory and Related Fields, published online on 11.01.2023, DOI 10.1007/s00440022011807 .
Abstract
We study an inhomogeneous sparse random graph, G_{N}, on [N] = { 1,...,N } as introduced in a seminal paper [BJR07] by Bollobás, Janson and Riordan (2007): vertices have a type (here in a compact metric space S), and edges between different vertices occur randomly and independently over all vertex pairs, with a probability depending on the two vertex types. In the limit N → ∞ , we consider the sparse regime, where the average degree is O(1). We prove a largedeviations principle with explicit rate function for the statistics of the collection of all the connected components, registered according to their vertex type sets, and distinguished according to being microscopic (of finite size) or macroscopic (of size ≈ N). In doing so, we derive explicit logarithmic asymptotics for the probability that G_{N} is connected. We present a full analysis of the rate function including its minimizers. From this analysis we deduce a number of limit laws, conditional and unconditional, which provide comprehensive information about all the microscopic and macroscopic components of G_{N}. In particular, we recover the criterion for the existence of the phase transition given in [BJR07]. 
N. Djurdjevac Conrad, J. Köppl, A. Djurdjevac, Feedback loops in opinion dynamics of agentbased models with multiplicative noise, Entropy. An International and Interdisciplinary Journal of Entropy and Information Studies, 24 (2022), pp. 1352/11352/23, DOI 10.3390/e24101352 .
Abstract
We introduce an agentbased model for coevolving opinion and social dynamics, under the influence of multiplicative noise. In this model, every agent is characterized by a position in a social space and a continuous opinion state variable. Agents? movements are governed by positions and opinions of other agents and similarly, the opinion dynamics is influenced by agents? spatial proximity and their opinion similarity. Using numerical simulations and formal analysis, we study this feedback loop between opinion dynamics and mobility of agents in a social space. We investigate the behavior of this ABM in different regimes and explore the influence of various factors on appearance of emerging phenomena such as group formation and opinion consensus. We study the empirical distribution and in the limit of infinite number of agents we derive a corresponding reduced model given by a partial differential equation (PDE). Finally, using numerical examples we show that a resulting PDE model is a good approximation of the original ABM. 
N. Engler, B. Jahnel, Ch. Külske, Gibbsianness of locally thinned random fields, Markov Processes and Related Fields, 28 (2022), pp. 185214, DOI 10.48550/arXiv.2201.02651 .
Abstract
We consider the locally thinned Bernoulli field on ℤ ^{d}, which is the lattice version of the TypeI Matérn hardcore process in Euclidean space. It is given as the lattice field of occupation variables, obtained as image of an i.i.d. Bernoulli lattice field with occupation probability p, under the map which removes all particles with neighbors, while keeping the isolated particles. We prove that the thinned measure has a Gibbsian representation and provide control on its quasilocal dependence, both in the regime of small p, but also in the regime of large p, where the thinning transformation changes the Bernoulli measure drastically. Our methods rely on Dobrushin uniqueness criteria, disagreement percolation arguments [46], and cluster expansions 
N. Fountoulakis, T. Iyer, C. Mailler, H. Sulzbach, Dynamical models for random simplicial complexes, The Annals of Applied Probability, 32 (2022), pp. 28602913, DOI 10.1214/21AAP1752 .
Abstract
We study a general model of random dynamical simplicial complexes and derive a formula for the asymptotic degree distribution. This asymptotic formula encompasses results for a number of existing models, including random Apollonian networks and the weighted random recursive tree. It also confirms results on the scalefree nature of Complex Quantum Network Manifolds in dimensions d>2, and special types of Network Geometry with Flavour models studied in the physics literature by Bianconi, Rahmede [Sci.Rep.5, 13979 (2015) and Phys.Rev.E93, 032315 (2016)]. 
N. Fountoulakis, T. Iyer, Condensation phenomena in preferential attachment trees with neighbourhood influence, Electronic Journal of Probability, 27 (2022), pp. 76/176/49, DOI 10.1214/22EJP787 .
Abstract
We introduce a model of evolving preferential attachment trees where vertices are assigned weights, and the evolution of a vertex depends not only on its own weight, but also on the weights of its neighbours. We study the distribution of edges with endpoints having certain weights, and the distribution of degrees of vertices having a given weight. We show that the former exhibits a condensation phenomenon under a certain critical condition, whereas the latter converges almost surely to a distribution that resembles a power law distribution. Moreover, in the absence of condensation, we prove almostsure setwise convergence of the related quantities. This generalises existing results on the BianconiBarabÃ¡si tree as well as on an evolving tree model introduced by the second author. 
B. Jahnel, Ch. Hirsch, E. Cali, Percolation and connection times in multiscale dynamic networks, Stochastic Processes and their Applications, 151 (2022), pp. 490518, DOI 10.1016/j.spa.2022.06.008 .
Abstract
We study the effects of mobility on two crucial characteristics in multiscale dynamic networks: percolation and connection times. Our analysis provides insights into the question, to what extent longtime averages are wellapproximated by the expected values of the corresponding quantities, i.e., the percolation and connection probabilities. In particular, we show that in multiscale models, strong random effects may persist in the limit. Depending on the precise model choice, these may take the form of a spatial birthdeath process or a Brownian motion. Despite the variety of structures that appear in the limit, we show that they can be tackled in a common framework with the potential to be applicable more generally in order to identify limits in dynamic spatial network models going beyond the examples considered in the present work. 
B. Jahnel, A. Tóbiás, E. Cali, Phase transitions for the Boolean model of continuum percolation for Cox point processes, Brazilian Journal of Probability and Statistics, 3 (2022), pp. 2044, DOI 10.1214/21BJPS514 .
Abstract
We consider the Boolean model with random radii based on Cox point processes. Under a condition of stabilization for the random environment, we establish existence and nonexistence of subcritical regimes for the size of the cluster at the origin in terms of volume, diameter and number of points. Further, we prove uniqueness of the infinite cluster for sufficiently connected environments. 
B. Jahnel, A. Tóbiás, SINR percolation for Cox point processes with random powers, Adv. Appl. Math., 54 (2022), pp. 227253, DOI 10.1017/apr.2021.25 .
Abstract
Signaltointerference plus noise ratio (SINR) percolation is an infiniterange dependent variant of continuum percolation modeling connections in a telecommunication network. Unlike in earlier works, in the present paper the transmitted signal powers of the devices of the network are assumed random, i.i.d. and possibly unbounded. Additionally, we assume that the devices form a stationary Cox point process, i.e., a Poisson point process with stationary random intensity measure, in two or higher dimensions. We present the following main results. First, under suitable moment conditions on the signal powers and the intensity measure, there is percolation in the SINR graph given that the device density is high and interferences are sufficiently reduced, but not vanishing. Second, if the interference cancellation factor γ and the SINR threshold τ satisfy γ ≥ 1/(2τ), then there is no percolation for any intensity parameter. Third, in the case of a Poisson point process with constant powers, for any intensity parameter that is supercritical for the underlying Gilbert graph, the SINR graph also percolates with some small but positive interference cancellation factor. 
A. Stephan, EDPconvergence for a linear reactiondiffusion system with fast reversible reaction, Calculus of Variations and Partial Differential Equations, 60 (2021), pp. 226/1226/35, DOI 10.1007/s00526021020890 .
Abstract
We perform a fastreaction limit for a linear reactiondiffusion system consisting of two diffusion equations coupled by a linear reaction. We understand the linear reactiondiffusion system as a gradient flow of the free energy in the space of probability measures equipped with a geometric structure, which contains the Wasserstein metric for the diffusion part and coshtype functions for the reaction part. The fastreaction limit is done on the level of the gradient structure by proving EDPconvergence with tilting. The limit gradient system induces a diffusion system with Lagrange multipliers on the linear slowmanifold. Moreover, the limit gradient system can be equivalently described by a coarsegrained gradient system, which induces a diffusion equation with a mixed diffusion constant for the coarsegrained slow variable. 
S. Jansen, W. König, B. Schmidt, F. Theil, Distribution of cracks in a chain of atoms at low temperature, Annales Henri Poincare. A Journal of Theoretical and Mathematical Physics, 22 (2021), pp. 41314172, DOI 10.1007/s00023021010767 .
Abstract
We consider a onedimensional classical manybody system with interaction potential of LennardJones type in the thermodynamic limit at low temperature 1/β ∈ (0, ∞). The ground state is a periodic lattice. We show that when the density is strictly smaller than the density of the ground state lattice, the system with N particles fills space by alternating approximately crystalline domains (clusters) with empty domains (voids) due to cracked bonds. The number of domains is of the order of N exp(β e _{surf} /2) with e _{surf} > 0 a surface energy. 
L. Andreis, W. König, R.I.A. Patterson, A largedeviations principle for all the cluster sizes of a sparse ErdősRényi random graph, Random Structures and Algorithms, 59 (2021), pp. 522553, DOI 10.1002/rsa.21007 .
Abstract
A largedeviations principle (LDP) is derived for the state, at fixed time, of the multiplicative coalescent in the large particle number limit. The rate function is explicit and describes each of the three parts of the state: microscopic, mesoscopic and macroscopic. In particular, it clearly captures the well known gelation phase transition given by the formation of a particle containing a positive fraction of the system mass at time t=1. Via a standard map of the multiplicative coalescent onto a timedependent version of the ErdősRényi random graph, our results can also be rephrased as an LDP for the component sizes in that graph. Our proofs rely on estimates and asymptotics for the probability that smaller ErdősRényi graphs are connected. 
A. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Phase transitions for chaseescape models on PoissonGilbert graphs, Electronic Communications in Probability, 25 (2020), pp. 25/125/14, DOI 10.1214/20ECP306 .
Abstract
We present results on phase transitions of local and global survival in a twospecies model on Gilbert graphs. At initial time there is an infection at the origin that propagates on the Gilbert graph according to a continuoustime nearestneighbor interacting particle system. The Gilbert graph consists of susceptible nodes and nodes of a second type, which we call white knights. The infection can spread on susceptible nodes without restriction. If the infection reaches a white knight, this white knight starts to spread on the set of infected nodes according to the same mechanism, with a potentially different rate, giving rise to a competition of chase and escape. We show welldefinedness of the model, isolate regimes of global survival and extinction of the infection and present estimates on local survival. The proofs rest on comparisons to the process on trees, percolation arguments and finitedegree approximations of the underlying random graphs. 
S. Jansen, W. König, B. Schmidt, F. Theil, Surface energy and boundary layers for a chain of atoms at low temperature, Archive for Rational Mechanics and Analysis, 239 (2021), pp. 915980 (published online on 21.12.2020), DOI 10.1007/s00205020015873 .
Abstract
We analyze the surface energy and boundary layers for a chain of atoms at low temperature for an interaction potential of LennardJones type. The pressure (stress) is assumed small but positive and bounded away from zero, while the temperature goes to zero. Our main results are: (1) As the temperature goes to zero and at fixed positive pressure, the Gibbs measures for infinite chains and semiinfinite chains satisfy path large deviations principles. The rate functions are bulk and surface energy functionals. The minimizer of the surface functional corresponds to zero temperature boundary layers. (2) The surface correction to the Gibbs free energy converges to the zero temperature surface energy, characterized with the help of the minimum of the surface energy functional. (3) The bulk Gibbs measure and Gibbs free energy can be approximated by their Gaussian counterparts. (4) Bounds on the decay of correlations are provided, some of them uniform in the inverse temperature. 
J.D. Deuschel, T. Orenshtein, Scaling limit of wetting models in 1+1 dimensions pinned to a shrinking strip, Stochastic Processes and their Applications, 130 (2020), pp. 27782807, DOI 10.1016/j.spa.2019.08.001 .

CH. Hirsch, B. Jahnel, A. Tóbiás, Lower large deviations for geometric functionals, Electronic Communications in Probability, 25 (2020), pp. 41/141/12, DOI 10.1214/20ECP322 .
Abstract
This work develops a methodology for analyzing largedeviation lower tails associated with geometric functionals computed on a homogeneous Poisson point process. The technique applies to characteristics expressed in terms of stabilizing score functions exhibiting suitable monotonicity properties. We apply our results to clique counts in the random geometric graph, intrinsic volumes of PoissonVoronoi cells, as well as powerweighted edge lengths in the random geometric, κnearest neighbor and relative neighborhood graph. 
J. Maas, A. Mielke, Modeling of chemical reaction systems with detailed balance using gradient structures, Journal of Statistical Physics, 181 (2020), pp. 22572303, DOI 10.1007/s10955020026634 .
Abstract
We consider various modeling levels for spatially homogeneous chemical reaction systems, namely the chemical master equation, the chemical Langevin dynamics, and the reactionrate equation. Throughout we restrict our study to the case where the microscopic system satisfies the detailedbalance condition. The latter allows us to enrich the systems with a gradient structure, i.e. the evolution is given by a gradientflow equation. We present the arising links between the associated gradient structures that are driven by the relative entropy of the detailedbalance steady state. The limit of large volumes is studied in the sense of evolutionary Γconvergence of gradient flows. Moreover, we use the gradient structures to derive hybrid models for coupling different modeling levels. 
A. Tóbiás, B. Jahnel, Exponential moments for planar tessellations, Journal of Statistical Physics, 179 (2020), pp. 90109, DOI 10.1007/s10955020025213 .
Abstract
In this paper we show existence of all exponential moments for the total edge length in a unit disc for a family of planar tessellations based on Poisson point processes. Apart from classical such tessellations like the PoissonVoronoi, PoissonDelaunay and Poisson line tessellation, we also treat the JohnsonMehl tessellation, Manhattan grids, nested versions and Palm versions. As part of our proofs, for some planar tessellations, we also derive existence of exponential moments for the number of cells and the number of edges intersecting the unit disk. 
A. Mielke, A. Stephan, Coarsegraining via EDPconvergence for linear fastslow reaction systems, Mathematical Models & Methods in Applied Sciences, 30 (2020), pp. 17651807, DOI 10.1142/S0218202520500360 .
Abstract
We consider linear reaction systems with slow and fast reactions, which can be interpreted as master equations or Kolmogorov forward equations for Markov processes on a finite state space. We investigate their limit behavior if the fast reaction rates tend to infinity, which leads to a coarsegrained model where the fast reactions create microscopically equilibrated clusters, while the exchange mass between the clusters occurs on the slow time scale. Assuming detailed balance the reaction system can be written as a gradient flow with respect to the relative entropy. Focusing on the physically relevant coshtype gradient structure we show how an effective limit gradient structure can be rigorously derived and that the coarsegrained equation again has a coshtype gradient structure. We obtain the strongest version of convergence in the sense of the EnergyDissipation Principle (EDP), namely EDPconvergence with tilting. 
CH. Hirsch, B. Jahnel, Large deviations for the capacity in dynamic spatial relay networks, Markov Processes and Related Fields, 25 (2019), pp. 3373.
Abstract
We derive a large deviation principle for the spacetime evolution of users in a relay network that are unable to connect due to capacity constraints. The users are distributed according to a Poisson point process with increasing intensity in a bounded domain, whereas the relays are positioned deterministically with given limiting density. The preceding work on capacity for relay networks by the authors describes the highly simplified setting where users can only enter but not leave the system. In the present manuscript we study the more realistic situation where users leave the system after a random transmission time. For this we extend the point process techniques developed in the preceding work thereby showing that they are not limited to settings with strong monotonicity properties. 
L. Andreis, A. Asselah, P. Dai Pra , Ergodicity of a system of interacting random walks with asymmetric interaction, Annales de l'Institut Henri Poincare. Probabilites et Statistiques, 55 (2019), pp. 590606.
Abstract
We study N interacting random walks on the positive integers. Each particle has drift delta towards infinity, a reflection at the origin, and a drift towards particles with lower positions. This inhomogeneous mean field system is shown to be ergodic only when the interaction is strong enough. We focus on this latter regime, and point out the effect of piles of particles, a phenomenon absent in models of interacting diffusion in continuous space. 
L. Andreis, P. Dai Pra, M. Fischer, McKeanVlasov limit for interacting systems with simultaneous jumps, Stochastic Analysis and Applications, 36 (2018), pp. 960995, DOI 10.1080/07362994.2018.1486202 .
Abstract
Motivated by several applications, including neuronal models, we consider the McKeanVlasov limit for meanfield systems of interacting diffusions with simultaneous jumps. We prove propagation of chaos via a coupling technique that involves an intermediate process and that gives a rate of convergence for the W1 Wasserstein distance between the empirical measures of the two systems on the space of trajectories D([0,T],R^d). 
O. Gün, A. Yilmaz, The stochastic encountermating model, Acta Applicandae Mathematicae. An International Survey Journal on Applying Mathematics and Mathematical Applications, 148 (2017), pp. 71102.

A. Mielke, R.I.A. Patterson, M.A. Peletier, D.R.M. Renger, Nonequilibrium thermodynamical principles for chemical reactions with massaction kinetics, SIAM Journal on Applied Mathematics, 77 (2017), pp. 15621585, DOI 10.1137/16M1102240 .
Abstract
We study stochastic interacting particle systems that model chemical reaction networks on the micro scale, converging to the macroscopic Reaction Rate Equation. One abstraction level higher, we study the ensemble of such particle systems, converging to the corresponding Liouville transport equation. For both systems, we calculate the corresponding large deviations and show that under the condition of detailed balance, the large deviations induce a nonlinear relation between thermodynamic fluxes and free energy driving force. 
R.I.A. Patterson, S. Simonella, W. Wagner, A kinetic equation for the distribution of interaction clusters in rarefied gases, Journal of Statistical Physics, 169 (2017), pp. 126167.

J. Blath, A. González Casanova Soberón, B. Eldon, N. Kurt, M. WilkeBerenguer, Genetic variability under the seedbank coalescent, Genetics, 200 (2015), pp. 921934.
Abstract
We analyze patterns of genetic variability of populations in the presence of a large seedbank with the help of a new coalescent structure called the seedbank coalescent. This ancestral process appears naturally as a scaling limit of the genealogy of large populations that sustain seedbanks, if the seedbank size and individual dormancy times are of the same order as those of the active population. Mutations appear as Poisson processes on the active lineages and potentially at reduced rate also on the dormant lineages. The presence of "dormant" lineages leads to qualitatively altered times to the most recent common ancestor and nonclassical patterns of genetic diversity. To illustrate this we provide a WrightFisher model with a seedbank component and mutation, motivated from recent models of microbial dormancy, whose genealogy can be described by the seedbank coalescent. Based on our coalescent model, we derive recursions for the expectation and variance of the time to most recent common ancestor, number of segregating sites, pairwise differences, and singletons. Estimates (obtained by simulations) of the distributions of commonly employed distance statistics, in the presence and absence of a seedbank, are compared. The effect of a seedbank on the expected sitefrequency spectrum is also investigated using simulations. Our results indicate that the presence of a large seedbank considerably alters the distribution of some distance statistics, as well as the sitefrequency spectrum. Thus, one should be able to detect from genetic data the presence of a large seedbank in natural populations.
Contributions to Collected Editions

W. König, Branching random walks in random environment, in: Probabilistic Structures in Evolution, E. Baake, A. Wakolbinger, eds., Probabilistic Structures in Evolution, EMS Series of Congress Reports, European Mathematical Society Publishing House, 2021, pp. 2341, DOI 10.4171/ECR/171/2 .

B. Jahnel, W. König, Probabilistic methods for spatial multihop communication systems, in: Topics in Applied Analysis and Optimisation, M. Hintermüller, J.F. Rodrigues, eds., CIM Series in Mathematical Sciences, Springer Nature Switzerland AG, Cham, 2019, pp. 239268.
Preprints, Reports, Technical Reports

B. Jahnel, L. Lüchtrath, Existence of subcritical percolation phases for generalised weightdependent random connection models, Preprint no. 2993, WIAS, Berlin, 2023, DOI 10.20347/WIAS.PREPRINT.2993 .
Abstract, PDF (299 kByte)
We derive a sufficient condition for the existence of a subcritical percolation phase for a wide range of continuum percolation models where each vertex is embedded into Euclidean space and carries an independent weight. In contrast to many established models, the presence of an edge is not only allowed to depend on the distance and weights of its end vertices but can also depend on the surrounding vertex set. Our result can be applied in particular to models combining heavytailed degree distributions and longrange effects, which are typically well connected. Moreover, we establish bounds on the taildistribution of the number of points and the diameter of the subcritical component of a typical point. The proofs rest on a multiscale argument. 
A. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Chaseescape in dynamic devicetodevice networks, Preprint no. 2969, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2969 .
Abstract, PDF (1550 kByte)
The present paper features results on global survival and extinction of an infection in a multilayer network of mobile agents. Expanding on a model first presented in CHJW22, we consider an urban environment, represented by linesegments in the plane, in which agents move according to a random waypoint model based on a Poisson point process. Whenever two agents are at sufficiently close proximity for a sufficiently long time the infection can be transmitted and then propagates into the system according to the same rule starting from a typical device. Inspired by wireless network architectures, the network is additionally equipped with a second class of agents that is able to transmit a patch to neighboring infected agents that in turn can further distribute the patch, leading to a chaseescape dynamics. We give conditions for parameter configurations that guarantee existence and absence of global survival as well as an inandout of the survival regime, depending on the speed of the devices. We also provide complementary results for the setting in which the chaseescape dynamics is defined as an independent process on the connectivity graph. The proofs mainly rest on percolation arguments via discretization and multiscale analysis. 
A. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Connectivity in mobile devicetodevice networks in urban environments, Preprint no. 2952, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2952 .
Abstract, PDF (606 kByte)
In this article we setup a dynamic devicetodevice communication system where devices, given as a Poisson point process, move in an environment, given by a street system of random planartessellation type, via a randomwaypoint model. Every device independently picks a target location on the street system using a general waypoint kernel, and travels to the target along the shortest path on the streets with an individual velocity. Then, any pair of devices becomes connected whenever they are on the same street in sufficiently close proximity, for a sufficiently long time. After presenting some general properties of the multiparameter system, we focus on an analysis of the clustering behavior of the random connectivity graph. In our main results we isolate regimes for the almostsure absence of percolation if, for example, the device intensity is too small, or the connectivity time is too large. On the other hand, we exhibit parameter regimes of sufficiently large intensities of devices, under favorable choices of the other parameters, such that percolation is possible with positive probability. Most interestingly, we also show an inandout of percolation as the velocity increases. The rigorous analysis of the system mainly rests on comparison arguments with simplified models via spatial coarse graining and thinning approaches. Here we also make contact to geostatistical percolation models with infiniterange dependencies. 
B. Jahnel, S.K. Jhawar, A.D. Vu, Continuum percolation in a nonstabilizing environment, Preprint no. 2943, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2943 .
Abstract, PDF (2463 kByte)
We prove nontrivial phase transitions for continuum percolation in a Boolean model based on a Cox point process with nonstabilizing directing measure. The directing measure, which can be seen as a stationary random environment for the classical PoissonBoolean model, is given by a planar rectangular Poisson line process. This Manhattan grid type construction features longrange dependencies in the environment, leading to absence of a sharp phase transition for the associated CoxBoolean model. Our proofs rest on discretization arguments and a comparison to percolation on randomly stretched lattices established in [MR2116736]. 
B. Jahnel, J. Köppl, Dynamical Gibbs variational principles for irreversible interacting particle systems with applications to attractor properties, Preprint no. 2935, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2935 .
Abstract, PDF (355 kByte)
We consider irreversible translationinvariant interacting particle systems on the ddimensional cubic lattice with finite local state space, which admit at least one Gibbs measure as a timestationary measure. Under some mild degeneracy conditions on the rates and the specification we prove, that zero relative entropy loss of a translationinvariant measure implies, that the measure is Gibbs w.r.t. the same specification as the timestationary Gibbs measure. As an application, we obtain the attractor property for irreversible interacting particle systems, which says that any weak limit point of any trajectory of translationinvariant measures is a Gibbs measure w.r.t. the same specification as the timestationary measure. This extends previously known results to fairly general irreversible interacting particle systems. 
A. Stephan, H. Stephan, Positivity and polynomial decay of energies for squarefield operators, Preprint no. 2901, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2901 .
Abstract, PDF (328 kByte)
We show that for a general Markov generator the associated squarefield (or carré du champs) operator and all their iterations are positive. The proof is based on an interpolation between the operators involving the generator and their semigroups, and an interplay between positivity and convexity on Banach lattices. Positivity of the squarefield operators allows to define a hierarchy of quadratic and positive energy functionals which decay to zero along solutions of the corresponding evolution equation. Assuming that the Markov generator satisfies an operatortheoretic normality condition, the sequence of energies is logconvex. In particular, this implies polynomial decay in time for the energy functionals along solutions. 
L. Andreis, W. König, H. Langhammer, R.I.A. Patterson, A largedeviations principle for all the components in a sparse inhomogeneous random graph, Preprint no. 2898, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2898 .
Abstract, PDF (690 kByte)
We study an inhomogeneous sparse random graph, G_{N}, on [N] = { 1,...,N } as introduced in a seminal paper [BJR07] by Bollobás, Janson and Riordan (2007): vertices have a type (here in a compact metric space S), and edges between different vertices occur randomly and independently over all vertex pairs, with a probability depending on the two vertex types. In the limit N → ∞ , we consider the sparse regime, where the average degree is O(1). We prove a largedeviations principle with explicit rate function for the statistics of the collection of all the connected components, registered according to their vertex type sets, and distinguished according to being microscopic (of finite size) or macroscopic (of size ≈ N). In doing so, we derive explicit logarithmic asymptotics for the probability that G_{N} is connected. We present a full analysis of the rate function including its minimizers. From this analysis we deduce a number of limit laws, conditional and unconditional, which provide comprehensive information about all the microscopic and macroscopic components of G_{N}. In particular, we recover the criterion for the existence of the phase transition given in [BJR07]. 
A. Stephan, Coarsegraining and reconstruction for Markov matrices, Preprint no. 2891, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2891 .
Abstract, PDF (248 kByte)
We present a coarsegraining (or model order reduction) procedure for stochastic matrices by clustering. The method is consistent with the natural structure of Markov theory, preserving positivity and mass, and does not rely on any tools from Hilbert space theory. The reconstruction is provided by a generalized PenroseMoore inverse of the coarsegraining operator incorporating the inhomogeneous invariant measure of the Markov matrix. As we show, the method provides coarsegraining and reconstruction also on the level of tensor spaces, which is consistent with the notion of an incidence matrix and quotient graphs, and, moreover, allows to coarsegrain and reconstruct fluxes. Furthermore, we investigate the connection with functional inequalities and Poincarétype constants. 
M. Heida, B. Jahnel, A.D. Vu, Stochastic homogenization on irregularly perforated domains, Preprint no. 2880, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2880 .
Abstract, PDF (668 kByte)
We study stochastic homogenization of a quasilinear parabolic PDE with nonlinear microscopic Robin conditions on a perforated domain. The focus of our work lies on the underlying geometry that does not allow standard homogenization techniques to be applied directly. Instead we prove homogenization on a regularized geometry and demonstrate afterwards that the form of the homogenized equation is independent from the regularization. Then we pass to the regularization limit to obtain the anticipated limit equation. Furthermore, we show that Boolean models of Poisson point processes are covered by our approach. 
B. Jahnel, Ch. Külske, Gibbsianness and nonGibbsianness for Bernoulli lattice fields under removal of isolated sites, Preprint no. 2878, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2878 .
Abstract, PDF (426 kByte)
We consider the i.i.d. Bernoulli field μ _{p} on Z ^{d} with occupation density p ∈ [0,1]. To each realization of the set of occupied sites we apply a thinning map that removes all occupied sites that are isolated in graph distance. We show that, while this map seems noninvasive for large p, as it changes only a small fraction p(1p)^{2d} of sites, there is p(d) <1 such that for all p ∈ (p(d), 1) the resulting measure is a nonGibbsian measure, i.e., it does not possess a continuous version of its finitevolume conditional probabilities. On the other hand, for small p, the Gibbs property is preserved. 
R.I.A. Patterson, D.R.M. Renger, U. Sharma, Variational structures beyond gradient flows: A macroscopic fluctuationtheory perspective, Preprint no. 2826, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2826 .
Abstract, PDF (522 kByte)
Macroscopic equations arising out of stochastic particle systems in detailed balance (called dissipative systems or gradient flows) have a natural variational structure, which can be derived from the largedeviation rate functional for the density of the particle system. While large deviations can be studied in considerable generality, these variational structures are often restricted to systems in detailed balance. Using insights from macroscopic fluctuation theory, in this work we aim to generalise this variational connection beyond dissipative systems by augmenting densities with fluxes, which encode nondissipative effects. Our main contribution is an abstract framework, which for a given fluxdensity cost and a quasipotential, provides a decomposition into dissipative and nondissipative components and a generalised orthogonality relation between them. We then apply this abstract theory to various stochastic particle systems  independent copies of jump processes, zerorange processes, chemicalreaction networks in complex balance and latticegas models. 
N. Nüsken, D.R.M. Renger, Stein variational gradient descent: Manyparticle and longtime asymptotics, Preprint no. 2819, WIAS, Berlin, 2021, DOI 10.20347/WIAS.PREPRINT.2819 .
Abstract, PDF (430 kByte)
Stein variational gradient descent (SVGD) refers to a class of methods for Bayesian inference based on interacting particle systems. In this paper, we consider the originally proposed deterministic dynamics as well as a stochastic variant, each of which represent one of the two main paradigms in Bayesian computational statistics: emphvariational inference and emphMarkov chain Monte Carlo. As it turns out, these are tightly linked through a correspondence between gradient flow structures and largedeviation principles rooted in statistical physics. To expose this relationship, we develop the cotangent space construction for the Stein geometry, prove its basic properties, and determine the largedeviation functional governing the manyparticle limit for the empirical measure. Moreover, we identify the emphSteinFisher information (or emphkernelised Stein discrepancy) as its leading order contribution in the longtime and manyparticle regime in the sense of $Gamma$convergence, shedding some light on the finiteparticle properties of SVGD. Finally, we establish a comparison principle between the SteinFisher information and RKHSnorms that might be of independent interest.
Talks, Poster

B. Jahnel, Continuum percolation in random environments, Topics in High Dimensional Probability, January 2  13, 2023, International Centre for Theoretical Sciences, Bangalore, India, January 3, 2023.

T. Iyer, Preferential attachment trees with neighbourhood influence, Summer School: Mathematics of Large Networks, May 30  June 3, 2022, Erdős Center, Budapest, Hungary, May 31, 2022.

T. Iyer, Preferential attachment trees with neighbourhood influence, Probability Seminar, Universität zu Köln, Department Mathematik/Informatik, April 29, 2022.

T. Iyer, The influence of competition on geneological trees associated with explosive agedependent branching processes, Oberseminar Stochastik, Westfälische WilhelmsUniversität Münster, Fachbereich Mathematik und Informatik, November 16, 2022.

E. Magnanini, Gelation in a Spatial MarcusLushnikov Process, Conference for Junior Female Researchers in Probability 2022, October 5  7, 2022, Stochastic Analysis in Interaction. BerlinOxford IRTG 2544, October 4, 2022.

B. Jahnel, Malware propagation in mobile devicetodevice networks (online talk), IEEE CloudNet '2; Workshop: AI@EDGE  INSPIRE5G (Online Event), November 8, 2022.

A. Stephan, Gradient systems and EDPconvergence with applications to nonlinear fastslow reaction systems (online talk), DS21: SIAM Conference on Applications of Dynamical Systems, Minisymposium 19 ``Applications of Stochastic Reaction Networks'' (Online Event), May 23  27, 2021, Society for Industrial and Applied Mathematics, May 23, 2021.

A. Stephan, Gradient systems and mulitscale reaction networks (online talk), Limits and Control of Stochastic Reaction Networks (Online Event), July 26  30, 2021, American Institute of Mathematics, San Jose, USA, July 29, 2021.

E. Magnanini, Limit theorems for the edge density in exponential random graphs, Workshop ``Junior Female Researchers in Probability'', October 4  6, 2021, Stochastic Analysis in Interaction. BerlinOxford IRTG 2544, October 5, 2021.

E. Magnanini, Limit theorems for the edge density in exponential random graphs, Probability Seminar, Università degli Studi di Firenze, Dipartimento di Matematica e Informatica ``Ulisse Dini'', Italy, November 17, 2021.

B. Jahnel, Connectivity improvements in mobile devicetodevice networks (online talk), Telecom Orange Paris, France, July 6, 2021.

B. Jahnel, Firstpassage percolation and chaseescape dynamics on random geometric graphs, Stochastic Geometry Days, November 15  19, 2021, Dunkerque, France, November 17, 2021.

B. Jahnel, Gibbsian representation for point processes via hyperedge potentials (online talk), Thematic Einstein Semester on Geometric and Topological Structure of Materials, Summer Semester 2021, Technische Universität Berlin, May 20, 2021.

B. Jahnel, Phase transitions for the Boolean model for Cox point processes, Workshop on Randomness Unleashed Geometry, Topology, and Data, September 22  24, 2021, University of Groningen, Faculty of Science and Engineering, Groningen, Netherlands, September 23, 2021.

B. Jahnel, Phase transitions for the Boolean model for Cox point processes (online talk), DYOGENE Seminar (Online Event), INRIA Paris, France, January 11, 2021.

B. Jahnel, Phase transitions for the Boolean model for Cox point processes (online talk), Probability Seminar Bath (Online Event), University of Bath, Department of Mathematical Sciences, UK, October 18, 2021.

W. König, A grid version of the interacting Bose gas (online talk), Probability Seminar (Online Event), University of Bath, Department of Mathematical Sciences, UK, February 15, 2021.

W. König, Cluster size distributions in a classical manybody system (online talk), Thematic Einstein Semester on Geometric and Topological Structure of Materials, Summer Semester 2021, Technische Universität Berlin, May 20, 2021.

W. van Zuijlen, Large time behaviour of the parabolic Anderson model (online talk), Probability Meeting (Online Event), University of Oxford, Department of Statistics, UK, February 10, 2021.

W. van Zuijlen, Large time behaviour of the parabolic Anderson model (online talk), Probability and Statistical Physics Seminar (Online Event), The University of Chicago, Department of Mathematics, Statistics, and Computer Science, USA, February 12, 2021.

T. Orenshtein, Aging for the O'ConellYor model in intermediate disorder (online talk), Joint Israeli Probability Seminar (Online Event), Technion, Haifa, November 17, 2020.

T. Orenshtein, Aging for the stationary KPZ equation, The 3rd Haifa Probability School. Workshop on Random Geometry and Stochastic Analysis, February 24  28, 2020, Technion Israel Institute of Technology, Haifa, February 24, 2020.

T. Orenshtein, Aging for the stationary KPZ equation (online talk), BernoulliIMS One World Symposium 2020 (Online Event), August 24  28, 2020, A virtual one week symposium on Probability and Mathematical Statistics, August 27, 2020.

T. Orenshtein, Aging for the stationary KPZ equation (online talk), 13th Annual ERC BerlinOxford Young Researchers Meeting on Applied Stochastic Analysis (Online Event), June 8  10, 2020, WIAS Berlin, June 10, 2020.

T. Orenshtein, Aging in EdwardsWilkinson and KPZ universality classes (online talk), Probability, Stochastic Analysis and Statistics Seminar (Online Event), University of Pisa, Italy, October 27, 2020.

A. Stephan, Coarsegraining via EDPconvergence for linear fastslow reaction systems, Seminar ``Applied Analysis'', Eindhoven University of Technology, Centre for Analysis, Scientific Computing, and Applications  Mathematics and Computer Science, Netherlands, January 20, 2020.

A. Stephan, On mathematical coarsegraining for linear reaction systems, 8th BMS Student Conference, February 19  21, 2020, Technische Universität Berlin, February 21, 2020.

A. Stephan, On gradient flows and gradient systems (online talk), CRC 1114 PhD Seminar (Online Event), Freie Universität Berlin, November 11, 2020.

A. Stephan, On gradient systems and applications to interacting particle systems (online talk), CRC 1114 PhD Seminar (Online Event), Freie Universität Berlin, November 25, 2020.

L. Andreis, A large deviations approach to sparse random graphs (online talk), BernoulliIMS One World Symposium 2020 (Online Event), August 24  28, 2020, A virtual one week symposium on Probability and Mathematical Statistics. BernoulliIMS One World Symposium 2020, August 25, 2020.

L. Andreis, Sparse inhomogeneous random graphs from a large deviation point of view (online talk), Probability Seminar (Online Event), University of Bath, Department of Mathematical Sciences, UK, June 1, 2020.

L. Andreis, The phase transition in random graphs and coagulation processes: A large deviation approach (online talk), Seminar of DISMA (Online Event), Politecnico di Torino, Department of Mathematical Sciences (DISMA), Italy, July 14, 2020.

A. Mielke, EDPconvergence for multiscale gradient systems with applications to fastslow reaction systems (online talk), One World Dynamics Seminar (Online Event), Technische Universität München, November 13, 2020.

A. Hinsen, Data mobility in adhoc networks: Vulnerability and security, KEIN öffentlicher Vortrag (Orange), Telecom Orange Paris, France, December 12, 2019.

A. Stephan, Rigorous derivation of the effective equation of a linear reaction system with different time scales, 90th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM 2019), Section S14 ``Applied Analysis'', February 18  22, 2019, Universität Wien, Technische Universität Wien, Austria, February 21, 2019.

B. Jahnel, Continuum percolation in random environment, Workshop on Probability, Analysis and Applications (PAA), September 23  October 4, 2019, African Institute for Mathematical Sciences  Ghana (AIMS Ghana), Accra.

R.I.A. Patterson, Fluctuations and confidence intervals for stochastic particle simulations, First BerlinLeipzig Workshop on Fluctuating Hydrodynamics, August 26  30, 2019, MaxPlanckInstitut für Mathematik in den Naturwissenschaften, Leipzig, August 29, 2019.

R.I.A. Patterson, Flux large deviations, Workshop on Chemical Reaction Networks, July 1  3, 2019, Politecnico di Torino, Dipartimento di Scienze Matematiche ``G. L. Lagrange``, Italy, July 2, 2019.

R.I.A. Patterson, Flux large deviations, Seminar, Statistical Laboratory, University of Cambridge, Faculty of Mathematics, UK, May 7, 2019.

R.I.A. Patterson, Interaction clusters for the Kac process, BerlinLeipzig Workshop in Analysis and Stochastics, January 16  18, 2019, MaxPlanckInstitut für Mathematik in den Naturwissenschaften, Leipzig, January 18, 2019.

R.I.A. Patterson, Interaction clusters for the Kac process, Workshop on Effective Equations: Frontiers in Classical and Quantum Systems, June 24  28, 2019, Hausdorff Research Institute for Mathematics, Bonn, June 28, 2019.

R.I.A. Patterson, Kinetic interaction clusters, Oberseminar, MartinLutherUniversität HalleWittenberg, Naturwissenschaftliche Fakultät II  Chemie, Physik und Mathematik, April 17, 2019.

R.I.A. Patterson, The role of fluctuating hydrodynamics in the CRC 1114, CRC 1114 School 2019: Fluctuating Hydrodynamics, Zuse Institute Berlin (ZIB), October 28, 2019.

L. Taggi, Critical density in activated random walks, Horowitz Seminar on Probability, Ergodic Theory and Dynamical Systems, Tel Aviv University, School of Mathematical Sciences, Israel, May 20, 2019.

M. Maurelli, McKeanVlasov SDEs with irregular drift: Large deviations for particle approximation, University of Oxford, Mathematical Institute, UK, March 5, 2018.

M. Maurelli , A McKeanVlasov SDE with reflecting boundaries, CASA Colloquium, Eindhoven University of Technology, Department of Mathematics and Computer Science, Netherlands, January 10, 2018.

L. Andreis, A largedeviations approach to the multiplicative coagulation process, Probability Seminar, Università degli Studi di Padova, Dipartimento di Matematica ``Tullio LeviCivita'', Italy, October 12, 2018.

L. Andreis, A largedeviations approach to the multiplicative coagulation process, Seminar ''Theory of Complex Systems and Neurophysics  Theory of Statistical Physics and Nonlinear Dynamics``, HumboldtUniversität zu Berlin, Institut für Physik, October 30, 2018.

L. Andreis, Ergodicity of a system of interacting random walks with asymmetric interaction, 13th German Probability and Statistics Days 2018  Freiburger StochastikTage, February 27  March 2, 2018, AlbertLudwigsUniversität Freiburg, Abteilung für Mathematische Stochastik, Freiburg, February 1, 2018.

L. Andreis, Networks of interacting components with macroscopic selfsustained periodic behavior, Neural Coding 2018, September 9  14, 2018, University of Torino, Department of Mathematics, Italy, September 10, 2018.

L. Andreis, Selfsustained periodic behavior in interacting systems, Random Structures in Neuroscience and Biology, March 26  29, 2018, LudwigMaximilians Universität München, Fakultät für Mathematik, Informatik und Statistik, Herrsching, March 26, 2018.

L. Andreis, System of interacting random walks with asymmetric interaction, 48th Probability Summer School, July 8  20, 2018, Clermont Auvergne University, Saint Flour, France, July 17, 2018.

W. Dreyer, Thermodynamics and kinetic theory of nonNewtonian fluids, Technische Universität Darmstadt, Mathematische Modellierung und Analysis, June 13, 2018.

W. Dreyer, J. Fuhrmann, P. Gajewski, C. Guhlke, M. Landstorfer, M. Maurelli, R. Müller, Stochastic model for LiFePO4electrodes, ModVal14  14th Symposium on Fuel Cell and Battery Modeling and Experimental Validation, Karlsruhe, March 2  3, 2017.

D.R.M. Renger, From large deviations to Wasserstein gradient flows in multiple dimensions, Workshop on Gradient Flows, Large Deviations and Applications, November 22  29, 2015, EURANDOM, Mathematics and Computer Science Department, Eindhoven, Netherlands, November 23, 2015.

D.R.M. Renger, The inverse problem: From gradient flows to large deviations, Workshop ``Analytic Approaches to Scaling Limits for Random System'', January 26  30, 2015, Universität Bonn, Hausdorff Research Institute for Mathematics, January 26, 2015.
External Preprints

A. Bianchi, F. Collet, E. Magnanini, Limit theorems for exponential random graphs, Preprint no. arXiv:2105.06312, Cornell University Library, arXiv.org, 2021.
Abstract
We consider the edgetriangle model, a twoparameter family of exponential random graphs in which dependence between edges is introduced through triangles. In the socalled replica symmetric regime, the limiting free energy exists together with a complete characterization of the phase diagram of the model. We borrow tools from statistical mechanics to obtain limit theorems for the edge density. First, we determine the asymptotic distribution of this quantity, as the graph size tends to infinity, in the various phases. Then we study the fluctuations of the edge density around its average value off the critical curve and formulate conjectures about the behavior at criticality based on the analysis of a meanfield approximation of the model. Some of our results can be extended with no substantial changes to more general classes of exponential random graphs 
D. Heydecker , R.I.A. Patterson, Kac interaction clusters: A bilinear coagulation equation and phase transition, Preprint no. arXiv:1902.07686, Cornell University Library, 2019.
Abstract
We consider the interaction clusters for Kac's model of a gas with quadratic interaction rates, and show that they behave as coagulating particles with a bilinear coagulation kernel. In the large particle number limit the distribution of the interaction cluster sizes is shown to follow an equation of Smoluchowski type. Using a coupling to random graphs, we analyse the limiting equation, showing wellposedness, and a closed form for the time of the gelation phase transition tg when a macroscopic cluster suddenly emerges. We further prove that the second moment of the cluster size distribution diverges exactly at tg. Our methods apply immediately to coagulating particle systems with other bilinear coagulation kernels. 
A. González Casanova Soberón, J.C. Pardo, J.L. Perez, Branching processes with interactions: The subcritical cooperative regime, Preprint no. arXiv:1704.04203, Cornell University Library, arXiv.org, 2017.
Abstract
In this paper, we introduce a particular family of processes with values on the nonnegative integers that model the dynamics of populations where individuals are allow to have different types of inter actions. The types of interactions that we consider include pairwise: competition, annihilation and cooperation; and interaction among several individuals that can be consider as catastrophes. We call such families of processes branching processes with interactions. In particular, we prove that a process in this class has a moment dual which turns out to be a jumpdiffusion that can be thought as the evolution of the frequency of a trait or phenotype. The aim of this paper is to study the long term behaviour of branching processes with interac tions under the assumption that the cooperation parameter satisfies a given condition that we called subcritical cooperative regime. The moment duality property is useful for our purposes. 
J. Blath, E. Buzzoni, A. Casanova Soberón, M.W. Berenguer, The seed bank diffusion, and its relation to the twoisland model, Preprint no. arXiv:1710.08164, Cornell University Library, arXiv.org, 2017.
Abstract
In this paper, we introduce a particular family of processes with values on the nonnegative integers that model the dynamics of populations where individuals are allow to have different types of inter actions. The types of interactions that we consider include pairwise: competition, annihilation and cooperation; and interaction among several individuals that can be consider as catastrophes. We call such families of processes branching processes with interactions. In particular, we prove that a process in this class has a moment dual which turns out to be a jumpdiffusion that can be thought as the evolution of the frequency of a trait or phenotype. The aim of this paper is to study the long term behaviour of branching processes with interac tions under the assumption that the cooperation parameter satisfies a given condition that we called subcritical cooperative regime. The moment duality property is useful for our purposes. 
K.F. Lee, M. Dosta, A.D. Mcguire, S. Mosbach, W. Wagner, S. Heinrich, M. Kraft, Development of a multicompartment population balance model for highshear wet granulation with Discrete Element Method, Technical report no. 170, c4ePreprint Series, 2016.
Abstract
This paper presents a multicompartment population balance model for wet granulation coupled with DEM (Discrete Element Method) simulations. Methodologies are developed to extract relevant data from the DEM simulations to inform the population balance model. First, compartmental residence times are calculated for the population balance model from DEM. Then, a suitable collision kernel is chosen for the population balance model based on particleparticle collision frequencies extracted from DEM. It is found t hat the population balance model is able to predict the trends exhibited by the experimental size and porosity distributions by utilising the information provided by the DEM simulations.