The theory of large deviations, a branch of probability theory, provides tools for the description of the asymptotic decay rate of a small probability, as a certain parameter diverges or shrinks to zero. Examples are large times, low temperatures, large numbers of stochastic quantities, or an approximation parameter. In this way the deviation of a stochastic quantity from its expected behaviour can often be described, e.g. the deviation of an empirical average from the mean in the law of large numbers. The decay rate is expressed in terms of a nonnegative rate function, which in many cases is explicit. Its minimiser(s) often describe(s) the normal behaviour of the stochastic system under interest in terms of a variational formula. Furthermore, the rate function contains information about the behaviour of the system that gives the main contribution to the rare event under consideration. Hence, variational methods are often very helpful in analysing the stochastic system. Often, the largedeviation analysis is only a starting point for deeper analysis, like the investigation of finer asymptotics or of deviations on different scales.
Furthermore, the theory provides also tools and concepts for the description of the asymptotics of expectations of exponential functionals of the system. This applies to the partition functions for many models in statistical physics. The description is in terms of a variational formula that shows the best compromise between the functional and the rate function. In many cases, the object that satisfies a largedeviations principle is not immediately apparent and has to be found by suitable reformulations of the problem.
Contribution of the Institute
At WIAS, largedeviation theory is employed for the analysis of various models from quite different areas.
For instance, in statistical physics or atomistic materials science, classical and quantum mechanical stochastic manybody systems are investigated using methods from this theory. Here large, but finite point clouds in large boxes in the euclidean space are under the influence of a pairinteraction that rules out strong clumping (mutually repelling forces), but favours distances of a certain fixed amount (attracting forces). Such systems are defined in terms of a Gibbs measure with LennardJones potential. In the thermodynamic limit (many particles in a large box with fixed particle density), one of the interesting questions is about the sizes of the subgroups (clusters) that are formed. In one work a largedeviation principle for the statistics of these cardinalities is derived and could by described quite explicitly in a certain lowdensity regime. If kinetic energy is added to any of the particles and a certain symmetry to the system, describing bosons, then a largedeviation principle for the empirical stationary field of a certain marked Poisson point process involving Brownian bridges proved helpful for the analysis of the limiting free energy of the system.
A highlight was the derivation of a prominent largedeviation principle for the normalised occupation measure of a Brownian motion without requesting compactness.
A further example is the study of the decay rate of frustration probabilities
, that is, the probability of unwanted events in a telecommunications network in the limit of a high density of participants. The unwanted events are occurrences such as significantly reduced connectivity or low capacity. The decay rates of such events were analysed by the Leibniz Group 4 and in particular the configurations that lead to such events were investigated. The main focus for multihop communication is on the question of whether the network is mainly degraded when many participants come together and cause mutual interference or whether problems are more likely to arise due to having insufficient participants to relay messages through critical regions.
Large deviations play also an important role in the approximation of the Smoluchowski equation with the empirical process of coagulating Brownian motions, see the Application Area Coagulation. The deviations of the approximating process from the equation is described, in the spirit of WentselFreidlin theory, by an explicit rate function, which gives rise to the construction of gradient flows.
Publications
Monographs

W. König, The Parabolic Anderson Model  Random Walks in Random Potential, Pathways in Mathematics, Birkhäuser, Basel, 2016, xi+192 pages, (Monograph Published).
Articles in Refereed Journals

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. 
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. 
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. 
F. Flegel, M. Heida, M. Slowik, Homogenization theory for the random conductance model with degenerate ergodic weights and unboundedrange jumps, Annales de l'Institut Henri Poincare. Probabilites et Statistiques, 55 (2019), pp. 12261257, DOI 10.1214/18AIHP917 .
Abstract
We study homogenization properties of the discrete Laplace operator with random conductances on a large domain in Zd. More precisely, we prove almostsure homogenization of the discrete Poisson equation and of the top of the Dirichlet spectrum. We assume that the conductances are stationary, ergodic and nearestneighbor conductances are positive. In contrast to earlier results, we do not require uniform ellipticity but certain integrability conditions on the lower and upper tails of the conductances. We further allow jumps of arbitrary length. Without the longrange connections, the integrability condition on the lower tail is optimal for spectral homogenization. It coincides with a necessary condition for the validity of a local central limit theorem for the random walk among random conductances. As an application of spectral homogenization, we prove a quenched large deviation principle for thenormalized and rescaled local times of the random walk in a growing box. Our proofs are based on a compactness result for the Laplacian's Dirichlet energy, Poincaré inequalities, Moser iteration and twoscale convergence 
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. 
CH. Bayer, P. Friz, A. Gulisashvili, B. Horvath, B. Stemper, Shorttime nearthemoney skew in rough fractional volatility models, Quantitative Finance, 19 (2019), pp. 779798, DOI 10.1080/14697688.2018.1529420 .
Abstract
We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the "rough" regime of Hurst parameter H < ½. This regime recently attracted a lot of attention both from the statistical and option pricing point of view. With focus on the latter, we sharpen the large deviation results of FordeZhang (2017) in a way that allows us to zoomin around the money while maintaining full analytical tractability. More precisely, this amounts to proving higher order moderate deviation estimates, only recently introduced in the option pricing context. This in turn allows us to push the applicability range of known atthemoney skew approximation formulae from CLT type logmoneyness deviations of order t^{1/2} (recent works of Alòs, León & Vives and Fukasawa) to the wider moderate deviations regime. 
R.I.A. Patterson, D.R.M. Renger, Large deviations of jump process fluxes, Mathematical Physics, Analysis and Geometry. An International Journal Devoted to the Theory and Applications of Analysis and Geometry to Physics, 22 (2019), pp. 21/121/32, DOI 10.1007/s1104001993184 .
Abstract
We study a system of interacting particles that randomly react to form new particles. The reaction flux is the rescaled number of reactions that take place in a time interval. We prove a dynamic largedeviation principle for the reaction fluxes under general assumptions that include massaction kinetics. This result immediately implies the dynamic large deviations for the empirical concentration. 
M. Heida, M. Röger, Large deviation principle for a stochastic AllenCahn equation, Journal of Theoretical Probability, 31 (2018), pp. 364401, DOI 10.1007/s1095901607117 .
Abstract
The AllenCahn equation is a prototype model for phase separation processes, a fundamental example of a nonlinear spatial dynamic and an important approximation of a geometric evolution equation by a reactiondiffusion equation. Stochastic perturbations, especially in the case of additive noise, to the AllenCahn equation have attracted considerable attention. We consider here an alternative random perturbation determined by a Brownian flow of spatial diffeomorphism that was introduced by Röger and Weber [Stoch. Partial Differ. Equ. Anal. Comput. 1 (2013)]. We first provide a large deviation principle for stochastic flows in spaces of functions that are Höldercontinuous in time, which extends results by Budhiraja, Dupuis and Maroulas [Ann. Probab. 36 (2008)]. From this result and a continuity argument we deduce a large deviation principle for the AllenCahn equation perturbed by a Brownian flow in the limit of small noise. Finally, we present two asymptotic reductions of the large deviation functional. 
D.R.M. Renger, Flux large deviations of independent and reacting particle systems, with implications for macroscopic fluctuation theory, Journal of Statistical Physics, 172 (2018), pp. 12911326, DOI 10.1007/s1095501820830 .
Abstract
We consider a system of independent particles on a finite state space, and prove a dynamic largedeviation principle for the empirical measureempirical flux pair, taking the specific fluxes rather than net fluxes into account. We prove the large deviations under deterministic initial conditions, and under random initial conditions satisfying a largedeviation principle. We then show how to use this result to generalise a number of principles from Macroscopic Fluctuation Theory to the finitespace setting. 
D.R.M. Renger, P. Koltai , From large deviations to transport semidistances: Coherence analysis for finite Lagrangian data, Journal of NonNewtonian Fluid Mechanics, 28 (2018), pp. 19151957, DOI 10.1007/s0033201894710 .
Abstract
Onsager's 1931 `reciprocity relations' result connects microscopic timereversibility with a symmetry property of corresponding macroscopic evolution equations. Among the many consequences is a variational characterization of the macroscopic evolution equation as a gradientflow, steepestascent, or maximalentropyproduction equation. Onsager's original theorem is limited to closetoequilibrium situations, with a Gaussian invariant measure and a linear macroscopic evolution. In this paper we generalize this result beyond these limitations, and show how the microscopic timereversibility leads to natural generalized symmetry conditions, which take the form of generalized gradient flows. 
D.R.M. Renger, Gradient and GENERIC systems in the space of fluxes, applied to reacting particle systems, Entropy. An International and Interdisciplinary Journal of Entropy and Information Studies, 20 (2018), pp. 596/1596/26, DOI 10.3390/e20080596 .
Abstract
In a previous work we devised a framework to derive generalised gradient systems for an evolution equation from the large deviations of an underlying microscopic system, in the spirit of the OnsagerMachlup relations. Of particular interest is the case where the microscopic system consists of random particles, and the macroscopic quantity is the empirical measure or concentration. In this work we take the particle flux as the macroscopic quantity, which is related to the concentration via a continuity equation. By a similar argument the large deviations can induce a generalised gradient or Generic system in the space of fluxes. In a general setting we study how flux gradient or generic systems are related to gradient systems of concentrations. The arguments are explained by the example of reacting particle systems, which is later expanded to include spatial diffusion as well. 
CH. Hirsch, B. Jahnel, R.I.A. Patterson, Spacetime large deviations in capacityconstrained relay networks, ALEA. Latin American Journal of Probability and Mathematical Statistics, 15 (2018), pp. 587615, DOI 10.30757/ALEA.v1524 .
Abstract
We consider a singlecell network of random transmitters and fixed relays in a bounded domain of Euclidean space. The transmitters arrive over time and select one relay according to a spatially inhomogeneous preference kernel. Once a transmitter is connected to a relay, the connection remains and the relay is occupied. If an occupied relay is selected by another transmitters with later arrival time, this transmitter becomes frustrated. We derive a large deviation principle for the spacetime evolution of frustrated transmitters in the highdensity regime. 
CH. Bayer, P. Friz, A. Gulisashvili, B. Horvath, B. Stemper, Shorttime nearthemoney skew in rough fractional volatility models, Quantitative Finance, 19 (2019), pp. 779798 (published online on 13.11.2018), DOI 10.1080/14697688.2018.1529420 .
Abstract
We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the "rough" regime of Hurst parameter H < ½. This regime recently attracted a lot of attention both from the statistical and option pricing point of view. With focus on the latter, we sharpen the large deviation results of FordeZhang (2017) in a way that allows us to zoomin around the money while maintaining full analytical tractability. More precisely, this amounts to proving higher order moderate deviation estimates, only recently introduced in the option pricing context. This in turn allows us to push the applicability range of known atthemoney skew approximation formulae from CLT type logmoneyness deviations of order t^{1/2} (recent works of Alòs, León & Vives and Fukasawa) to the wider moderate deviations regime. 
M. Liero, A. Mielke, M.A. Peletier, D.R.M. Renger, On microscopic origins of generalized gradient structures, Discrete and Continuous Dynamical Systems  Series S, 10 (2017), pp. 135, DOI 10.3934/dcdss.2017001 .
Abstract
Classical gradient systems have a linear relation between rates and driving forces. In generalized gradient systems we allow for arbitrary relations derived from general nonquadratic dissipation potentials. This paper describes two natural origins for these structures. A first microscopic origin of generalized gradient structures is given by the theory of largedeviation principles. While Markovian diffusion processes lead to classical gradient structures, Poissonian jump processes give rise to coshtype dissipation potentials. A second origin arises via a new form of convergence, that we call EDPconvergence. Even when starting with classical gradient systems, where the dissipation potential is a quadratic functional of the rate, we may obtain a generalized gradient system in the evolutionary Gammalimit. As examples we treat (i) the limit of a diffusion equation having a thin layer of low diffusivity, which leads to a membrane model, and (ii) the limit of diffusion over a high barrier, which gives a reactiondiffusion system. 
W. van Zuijlen, Large deviations of continuous regular conditional probabilities, Journal of Theoretical Probability, published online on 27.12.2016., DOI 10.1007/s1095901607331 .

E. Bolthausen, W. König, Ch. Mukherjee, Meanfield interaction of Brownian occupation measures. II: A rigorous construction of the Pekar process, Communications on Pure and Applied Mathematics, 70 (2017), pp. 15981629.
Abstract
We consider meanfield interactions corresponding to Gibbs measures on interacting Brownian paths in three dimensions. The interaction is selfattractive and is given by a singular Coulomb potential. The logarithmic asymptotics of the partition function for this model were identified in the 1980s by Donsker and Varadhan [DV83] in terms of the Pekar variational formula, which coincides with the behavior of the partition function corresponding to the polaron problem under strong coupling. Based on this, Spohn ([Sp87]) made a heuristic observation that the strong coupling behavior of the polaron path measure, on certain time scales, should resemble a process, named as the itPekar process, whose distribution could somehow be guessed from the limiting asymptotic behavior of the meanfield measures under interest, whose rigorous analysis remained open. The present paper is devoted to a precise analysis of these meanfield path measures and convergence of the normalized occupation measures towards an explicit mixture of the maximizers of the Pekar variational problem. This leads to a rigorous construction of the aforementioned Pekar process and hence, is a contribution to the understanding of the “meanfield approximation" of the polaron problem on the level of path measures. The method of our proof is based on the compact large deviation theory developed in [MV14], its extension to the uniform strong metric for the singular Coulomb interaction carried out in [KM15], as well as an idea inspired by a itpartial path exchange argument appearing in [BS97] 
J.D. Deuschel, P. Friz, M. Maurelli, M. Slowik, The enhanced Sanov theorem and propagation of chaos, Stochastic Processes and their Applications, 128 (2018), pp. 22282269 (published online on 21.09.2017), DOI 10.1016/j.spa.2017.09.010 .
Abstract
We establish a Sanov type large deviation principle for an ensemble of interacting Brownian rough paths. As application a large deviations for the (klayer, enhanced) empirical measure of weakly interacting diffusions is obtained. This in turn implies a propagation of chaos result in a space of rough paths and allows for a robust analysis of the particle system and its McKean?Vlasov type limit, as shown in two corollaries. 
CH. Hirsch, B. Jahnel, P. Keeler, R.I.A. Patterson, Large deviations in relayaugmented wireless networks, Queueing Systems. Theory and Applications, 88 (2018), pp. 349387 (published online on 28.10.2017).
Abstract
We analyze a model of relayaugmented cellular wireless networks. The network users, who move according to a general mobility model based on a Poisson point process of continuous trajectories in a bounded domain, try to communicate with a base station located at the origin. Messages can be sent either directly or indirectly by relaying over a second user. We show that in a scenario of an increasing number of users, the probability that an atypically high number of users experiences bad quality of service over a certain amount of time, decays at an exponential speed. This speed is characterized via a constrained entropy minimization problem. Further, we provide simulation results indicating that solutions of this problem are potentially nonunique due to symmetry breaking. Also two general sources for bad quality of service can be detected, which we refer to as isolation and screening. 
W. König, Ch. Mukherjee, Meanfield interaction of Brownian occupation measures. I: Uniform tube property of the Coulomb functional, Annales de l'Institut Henri Poincare. Probabilites et Statistiques, 53 (2017), pp. 22142228, DOI 10.1214/16AIHP788 .
Abstract
We study the transformed path measure arising from the selfinteraction of a threedimensional Brownian motion via an exponential tilt with the Coulomb energy of the occupation measures of the motion by time $t$. The logarithmic asymptotics of the partition function were identified in the 1980s by Donsker and Varadhan [DV83P] in terms of a variational formula. Recently [MV14] a new technique for studying the path measure itself was introduced, which allows for proving that the normalized occupation measure asymptotically concentrates around the set of all maximizers of the formula. In the present paper, we show that likewise the Coulomb functional of the occupation measure concentrates around the set of corresponding Coulomb functionals of the maximizers in the uniform topology. This is a decisive step on the way to a rigorous proof of the convergence of the normalized occupation measures towards an explicit mixture of the maximizers, which will be carried out elsewhere. Our methods rely on deriving Höldercontinuity of the Coulomb functional of the occupation measure with exponentially small deviation probabilities and invoking the largedeviation theory developed in [MV14] to a certain shiftinvariant functional of the occupation measures. 
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. 
CH. Hirsch, B. Jahnel, P. Keeler, R.I.A. Patterson, Largedeviation principles for connectable receivers in wireless networks, Advances in Applied Probability, 48 (2016), pp. 10611094.
Abstract
We study largedeviation principles for a model of wireless networks consisting of Poisson point processes of transmitters and receivers, respectively. To each transmitter we associate a family of connectable receivers whose signaltointerferenceandnoise ratio is larger than a certain connectivity threshold. First, we show a largedeviation principle for the empirical measure of connectable receivers associated with transmitters in large boxes. Second, making use of the observation that the receivers connectable to the origin form a Cox point process, we derive a largedeviation principle for the rescaled process of these receivers as the connection threshold tends to zero. Finally, we show how these results can be used to develop importancesampling algorithms that substantially reduce the variance for the estimation of probabilities of certain rare events such as users being unable to connect. 
S. Jansen, W. König, B. Metzger, Large deviations for cluster size distributions in a continuous classical manybody system, The Annals of Applied Probability, 25 (2015), pp. 930973.
Abstract
An interesting problem in statistical physics is the condensation of classical particles in droplets or clusters when the pairinteraction is given by a stable LennardJonestype potential. We study two aspects of this problem. We start by deriving a large deviations principle for the cluster size distribution for any inverse temperature $betain(0,infty)$ and particle density $rhoin(0,rho_rmcp)$ in the thermodynamic limit. Here $rho_rmcp >0$ is the close packing density. While in general the rate function is an abstract object, our second main result is the $Gamma$convergence of the rate function towards an explicit limiting rate function in the lowtemperature dilute limit $betatoinfty$, $rho downarrow 0$ such that $beta^1logrhoto nu$ for some $nuin(0,infty)$. The limiting rate function and its minimisers appeared in recent work, where the temperature and the particle density were coupled with the particle number. In the decoupled limit considered here, we prove that just one cluster size is dominant, depending on the parameter $nu$. Under additional assumptions on the potential, the $Gamma$convergence along curves can be strengthened to uniform bounds, valid in a lowtemperature, lowdensity rectangle. 
D. Belomestny, M. Ladkau, J.G.M. Schoenmakers, Simulation based policy iteration for American style derivatives  A multilevel approach, SIAM ASA J. Uncertainty Quantification, 3 (2015), pp. 460483.
Abstract
This paper presents a novel approach to reduce the complexity of simulation based policy iteration methods for pricing American options. Typically, Monte Carlo construction of an improved policy gives rise to a nested simulation algorithm for the price of the American product. In this respect our new approach uses the multilevel idea in the context of the inner simulations required, where each level corresponds to a specific number of inner simulations. A thorough analysis of the crucial convergence rates in the respective multilevel policy improvement algorithm is presented. A detailed complexity analysis shows that a significant reduction in computational effort can be achieved in comparison to standard Monte Carlo based policy iteration. 
M. Erbar, J. Maas, D.R.M. Renger, From large deviations to Wasserstein gradient flows in multiple dimensions, Electronic Communications in Probability, 20 (2015), pp. 112.
Abstract
We study the large deviation rate functional for the empirical distribution of independent Brownian particles with drift. In one dimension, it has been shown by Adams, Dirr, Peletier and Zimmer [ADPZ11] that this functional is asymptotically equivalent (in the sense of Gammaconvergence) to the JordanKinderlehrerOtto functional arising in the Wasserstein gradient flow structure of the FokkerPlanck equation. In higher dimensions, part of this statement (the lower bound) has been recently proved by Duong, Laschos and Renger, but the upper bound remained open, since the proof in [DLR13] relies on regularity properties of optimal transport maps that are restricted to one dimension. In this note we present a new proof of the upper bound, thereby generalising the result of [ADPZ11] to arbitrary dimensions. 
O. Gün, W. König, O. Sekulović, Moment asymptotics for multitype branching random walks in random environment, Journal of Theoretical Probability, 28 (2015), pp. 17261742.
Abstract
We study a discrete time multitype branching random walk on a finite space with finite set of types. Particles follow a Markov chain on the spatial space whereas offspring distributions are given by a random field that is fixed throughout the evolution of the particles. Our main interest lies in the averaged (annealed) expectation of the population size, and its longtime asymptotics. We first derive, for fixed time, a formula for the expected population size with fixed offspring distributions, which is reminiscent of a FeynmanKac formula. We choose Weibulltype distributions with parameter 1/ρ_{ij} for the upper tail of the mean number of j type particles produced by an i type particle. We derive the first two terms of the longtime asymptotics, which are written as two coupled variational formulas, and interpret them in terms of the typical behavior of the system. 
W. König, T. Wolff, Large deviations for the local times of a random walk among random conductances in a growing box, Special issue for Pastur's 75th birthday, Markov Processes and Related Fields, 21 (2015), pp. 591638.
Abstract
We derive an annealed large deviation principle (LDP) for the normalised and rescaled local times of a continuoustime random walk among random conductances (RWRC) in a timedependent, growing box in Z^{d}. We work in the interesting case that the conductances are positive, but may assume arbitrarily small values. Thus, the underlying picture of the principle is a joint strategy of small conductance values and large holding times of the walk. The speed and the rate function of our principle are explicit in terms of the lower tails of the conductance distribution as well as the timedependent size of the box.
An interesting phase transition occurs if the thickness parameter of the conductance tails exceeds a certain threshold: for thicker tails, the random walk spreads out over the entire growing box, for thinner tails it stays confined to some bounded region. In fact, in the first case, the rate function turns out to be equal to the pth power of the pnorm of the gradient of the square root for some 2d/(d+2) < p < 2. This extends the DonskerVaradhanGärtner rate function for the local times of Brownian motion (with deterministic environment) from p=2 to these values.
As corollaries of our LDP, we derive the logarithmic asymptotics of the nonexit probability of the RWRC from the growing box, and the Lifshitz tails of the generator of the RWRC, the randomised Laplace operator. To contrast with the annealed, not uniformly elliptic case, we also provide an LDP in the quenched setting for conductances that are bounded and bounded away from zero. The main tool here is a spectral homogenisation result, based on a quenched invariance principle for the RWRC. 
A. Mielke, M.A. Peletier, D.R.M. Renger, On the relation between gradient flows and the largedeviation principle, with applications to Markov chains and diffusion, Potential Analysis, 41 (2014), pp. 12931325.
Abstract
Motivated by the occurence in rate functions of timedependent largedeviation principles, we study a class of nonnegative functions ℒ that induce a flow, given by ℒ(z_{t},ż_{t})=0. We derive necessary and sufficient conditions for the unique existence of a generalized gradient structure for the induced flow, as well as explicit formulas for the corresponding driving entropy and dissipation functional. In particular, we show how these conditions can be given a probabilistic interpretation when ℒ is associated to the large deviations of a microscopic particle system. Finally, we illustrate the theory for independent Brownian particles with drift, which leads to the entropyWasserstein gradient structure, and for independent Markovian particles on a finite state space, which leads to a previously unknown gradient structure. 
M.H. Duong, V. Laschos, M. Renger, Wasserstein gradient flows from large deviations of manyparticle limits, ESAIM. Control, Optimisation and Calculus of Variations, 19 (2013), pp. 11661188.

M.A. Peletier, M. Renger, M. Veneroni, Variational formulation of the FokkerPlanck equation with decay: A particle approach, Communications in Contemporary Mathematics, 15 (2013), pp. 1350017/11350017/43.

W. König, Ch. Mukherjee, Large deviations for Brownian intersection measures, Communications on Pure and Applied Mathematics, 66 (2013), pp. 263306.
Abstract
We consider $p$ independent Brownian motions in $R^d$. We assume that $pgeq 2$ and $p(d2)<d$. Let $ell_t$ denote the intersection measure of the $p$ paths by time $t$, i.e., the random measure on $R^d$ that assigns to any measurable set $Asubset R^d$ the amount of intersection local time of the motions spent in $A$ by time $t$. Earlier results of Chen citeCh09 derived the logarithmic asymptotics of the upper tails of the total mass $ell_t(R^d)$ as $ttoinfty$. In this paper, we derive a largedeviation principle for the normalised intersection measure $t^pell_t$ on the set of positive measures on some open bounded set $BsubsetR^d$ as $ttoinfty$ before exiting $B$. The rate function is explicit and gives some rigorous meaning, in this asymptotic regime, to the understanding that the intersection measure is the pointwise product of the densities of the normalised occupation times measures of the $p$ motions. Our proof makes the classical DonskerVaradhan principle for the latter applicable to the intersection measure. A second version of our principle is proved for the motions observed until the individual exit times from $B$, conditional on a large total mass in some compact set $Usubset B$. This extends earlier studies on the intersection measure by König and Mörters citeKM01,KM05. 
M. Becker, W. König, Selfintersection local times of random walks: Exponential moments in subcritical dimensions, Probability Theory and Related Fields, 154 (2012), pp. 585605.
Abstract
Fix $p>1$, not necessarily integer, with $p(d2)0$ that are bounded from above, possibly tending to zero. The speed is identified in terms of mixed powers of $t$ and $theta_t$, and the precise rate is characterized in terms of a variational formula, which is in close connection to the it GagliardoNirenberg inequality. As a corollary, we obtain a largedeviation principle for $ ell_t _p/(t r_t)$ for deviation functions $r_t$ satisfying $t r_tggE[ ell_t _p]$. Informally, it turns out that the random walk homogeneously squeezes in a $t$dependent box with diameter of order $ll t^1/d$ to produce the required amount of selfintersections. Our main tool is an upper bound for the joint density of the local times of the walk. 
S. Adams, A. Collevecchio, W. König, A variational formula for the free energy of an interacting manyparticle system, The Annals of Probability, 39 (2011), pp. 683728.
Abstract
We consider $N$ bosons in a box in $R^d$ with volume $N/rho$ under the influence of a mutually repellent pair potential. The particle density $rhoin(0,infty)$ is kept fixed. Our main result is the identification of the limiting free energy, $f(beta,rho)$, at positive temperature $1/beta$, in terms of an explicit variational formula, for any fixed $rho$ if $beta$ is sufficiently small, and for any fixed $beta$ if $rho$ is sufficiently small. The thermodynamic equilibrium is described by the symmetrised trace of $rm e^beta Hcal_N$, where $Hcal_N$ denotes the corresponding Hamilton operator. The wellknown FeynmanKac formula reformulates this trace in terms of $N$ interacting Brownian bridges. Due to the symmetrisation, the bridges are organised in an ensemble of cycles of various lengths. The novelty of our approach is a description in terms of a marked Poisson point process whose marks are the cycles. This allows for an asymptotic analysis of the system via a largedeviations analysis of the stationary empirical field. The resulting variational formula ranges over random shiftinvariant marked point fields and optimizes the sum of the interaction and the relative entropy with respect to the reference process. In our proof of the lower bound for the free energy, we drop all interaction involving lq infinitely longrq cycles, and their possible presence is signalled by a loss of mass of the lq finitely longrq cycles in the variational formula. In the proof of the upper bound, we only keep the mass on the lq finitely longrq cycles. We expect that the precise relationship between these two bounds lies at the heart of BoseEinstein condensation and intend to analyse it further in future. 
W. König, P. Schmid, Brownian motion in a truncated Weyl chamber, Markov Processes and Related Fields, 17 (2011), pp. 499522.
Abstract
We examine the nonexit probability of a multidimensional Brownian motion from a growing truncated Weyl chamber. Different regimes are identified according to the growth speed, ranging from polynomial decay over stretchedexponential to exponential decay. Furthermore we derive associated large deviation principles for the empirical measure of the properly rescaled and transformed Brownian motion as the dimension grows to infinity. Our main tool is an explicit eigenvalue expansion for the transition probabilities before exiting the truncated Weyl chamber. 
A. Collevecchio, W. König, P. Mörters, N. Sidorova, Phase transitions for dilute particle systems with LennardJones potential, Communications in Mathematical Physics, 299 (2010), pp. 603630.

G. Grüninger, W. König, Potential confinement property in the parabolic Anderson model, Annales de l'Institut Henri Poincare. Probabilites et Statistiques, 45 (2009), pp. 840863.

W. König, H. Lacoin, P. Mörters, N. Sidorova, A two cities theorem for the parabolic Anderson model, The Annals of Probability, 37 (2009), pp. 347392.
Contributions to Collected Editions

A. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Malware propagation in urban D2D networks, IEEE 18th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Institut of Electrical and Electronics Engineer (IEEE), 2020, pp. 16.
Abstract
We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary CoxGilbert graphs. Here, the devices form a Poisson point process with random intensity measure λ, Λ where Λ is stationary and given, for example, by the edgelength measure of a realization of a PoissonVoronoi tessellation that represents an urban street system. We assume that, at initial time, a typical device at the center of the network carries a malware and starts to infect neighboring devices after random waiting times. Here we focus on Markovian models, where the waiting times are exponential random variables, and nonMarkovian models, where the waiting times feature strictly positive minimal and finite maximal waiting times. We present numerical results for the speed of propagation depending on the system parameters. In a second step, we introduce and analyze a counter measure for the malware propagation given by special devices called white knights, which have the ability, once attacked, to eliminate the malware from infected devices and turn them into white knights. Based on simulations, we isolate parameter regimes in which the malware survives or is eliminated, both in the Markovian and nonMarkovian setting. 
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.

TH. Dickhaus, H. Finner, Asymptotic density crossing points of selfnormalized sums and normal (electronic only), in: Proceedings of the 3rd Annual International Conference on Computational Mathematics, Computational Geometry and Statistics, CMCGS 2014, Singapore, February 34, 2014, Global Science and Technology Forum (GSTF), Singapore, pp. 8488.
Preprints, Reports, Technical Reports

B. Jahnel, A. Tóbiás, E. Cali, Phase transitions for the Boolean model of continuum percolation for Cox point processes, Preprint no. 2704, WIAS, Berlin, 2020, DOI 10.20347/WIAS.PREPRINT.2704 .
Abstract, PDF (389 kByte)
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. 
A. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Malware propagation in urban D2D networks, Preprint no. 2674, WIAS, Berlin, 2020, DOI 10.20347/WIAS.PREPRINT.2674 .
Abstract, PDF (3133 kByte)
We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary CoxGilbert graphs. Here, the devices form a Poisson point process with random intensity measure λ, Λ where Λ is stationary and given, for example, by the edgelength measure of a realization of a PoissonVoronoi tessellation that represents an urban street system. We assume that, at initial time, a typical device at the center of the network carries a malware and starts to infect neighboring devices after random waiting times. Here we focus on Markovian models, where the waiting times are exponential random variables, and nonMarkovian models, where the waiting times feature strictly positive minimal and finite maximal waiting times. We present numerical results for the speed of propagation depending on the system parameters. In a second step, we introduce and analyze a counter measure for the malware propagation given by special devices called white knights, which have the ability, once attacked, to eliminate the malware from infected devices and turn them into white knights. Based on simulations, we isolate parameter regimes in which the malware survives or is eliminated, both in the Markovian and nonMarkovian setting. 
A. Mielke, A. Montefusco, M.A. Peletier, Exploring families of energydissipation landscapes via tilting  Three types of EDP convergence, Preprint no. 2668, WIAS, Berlin, 2019, DOI 10.20347/WIAS.PREPRINT.2668 .
Abstract, PDF (372 kByte)
This paper revolves around a subtle distinction between two concepts: passing to the limit in a family of gradient systems, on one hand, and deriving effective kinetic relations on the other. The two concepts are strongly related, and in many examples they even appear to be the same. Our main contributions are to show that they are different, to show that wellknown techniques developed for the former may give incorrect results for the latter, and to introduce new tools to remedy this. The approach is based on the EnergyDissipation Principle that provides a variational formulation to gradientflow equations that allows one to apply techniques from Γconvergence of functional on states and functionals on trajectories. 
B. Jahnel, A. Tóbiás, SINR percolation for Cox point processes with random powers, Preprint no. 2659, WIAS, Berlin, 2019, DOI 10.20347/WIAS.PREPRINT.2659 .
Abstract, PDF (356 kByte)
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. Hinsen, B. Jahnel, E. Cali, J.P. Wary, Phase transitions for chaseescape models on Gilbert graphs, Preprint no. 2642, WIAS, Berlin, 2019, DOI 10.20347/WIAS.PREPRINT.2642 .
Abstract, PDF (219 kByte)
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. 
K. Chouk, W. van Zuijlen, Asymptotics of the eigenvalues of the Anderson Hamiltonian with white noise potential in two dimensions, Preprint no. 2606, WIAS, Berlin, 2019, DOI 10.20347/WIAS.PREPRINT.2606 .
Abstract, PDF (588 kByte)
In this paper we consider the Anderson Hamiltonian with white noise potential on the box [0,L]² with Dirichlet boundary conditions. We show that all the eigenvalues divided by log L converge as L → ∞ almost surely to the same deterministic constant, which is given by a variational formula. 
L. Andreis, W. König, R.I.A. Patterson, A largedeviations approach to gelation, Preprint no. 2568, WIAS, Berlin, 2019, DOI 10.20347/WIAS.PREPRINT.2568 .
Abstract, PDF (338 kByte)
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. 
M. Mittnenzweig, Hydrodynamic limit and large deviations of reactiondiffusion master equations, Preprint no. 2521, WIAS, Berlin, 2018, DOI 10.20347/WIAS.PREPRINT.2521 .
Abstract, PDF (389 kByte)
We derive the hydrodynamic limit of a reactiondiffusion master equation, that combines an exclusion process with a reversible chemical master equation expression for the reaction rates. The crucial assumption is that the associated macroscopic reaction network has a detailed balance equilibrium. The hydrodynamic limit is given by a system of reactiondiffusion equations with a modified mass action law for the reaction rates. We provide the upper bound for large deviations of the empirical measure from the hydrodynamic limit.
Talks, Poster

D.R.M. Renger, Reaction fluxes, Applied Mathematics Seminar, University of Birmingham, School of Mathematics, UK, April 4, 2019.

L. Andreis, A largedeviations approach to the multiplicative coagulation process, Workshop ``Woman in Probability'', May 31  June 1, 2019, Technische Universität München, Fakultät für Mathematik, May 31, 2019.

L. Andreis, Coagulating particles and gelation phase transition: A largedeviation approach, Second Italian Meeting on Probability and Mathematical Statistics, June 17  20, 2019, Vietri sul Mare, Italy, June 19, 2019.

L. Andreis, Largedeviation approach to coagulation processes and gelation, Workshop on Chemical Reaction Networks, July 1  3, 2019, Politecnico di Torino, Dipartimento di Scienze Matematiche ''G. L. Lagrange``, Italy, July 2, 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, The role of fluctuating hydrodynamics in the CRC 1114, CRC 1114 School 2019: Fluctuating Hydrodynamics, Zuse Institute Berlin (ZIB), October 28, 2019.

M. Maurelli, Sanov theorem for Brownian rough paths and an application to interacting particles, Università di Roma La Sapienza, Dipartimento di Matematica Guido Castelnuovo, Italy, January 18, 2018.

D.R.M. Renger, Gradient and GENERIC structures from flux large deviations, POLYPHYS Seminar, Eidgenössische Technische Hochschule Zürich, Department of Materials, Zürich, Switzerland, March 28, 2018.

D.R.M. Renger, Gradient and GENERIC structures in the space of fluxes, Analysis of Evolutionary and Complex Systems (ALEX2018), September 24  28, 2018, WIAS Berlin, September 27, 2018.

D.R.M. Renger, Gradient and Generic structures in the space of fluxes, Analysis of Evolutionary and Complex Systems (ALEX2018), September 24  28, 2018, WIAS Berlin, September 27, 2018.

D.R.M. Renger, Large deviations for reaction fluxes, Workshop on Transformations and Phase Transitions, January 29  31, 2018, RuhrUniversität Bochum, Fakultät für Mathematik, January 29, 2018.

D.R.M. Renger, Large deviations for reaction fluxes, Università degli Studi dell'Aquila, Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica, L'Aquila, Italy, January 10, 2018.

W. van Zuijlen, A HamiltonJacobi point of view on meanfield GibbsnonGibbs transitions, Workshop on Transformations and Phase Transitions, January 29  31, 2018, RuhrUniversität Bochum, Fakultät für Mathematik, Bochum, January 30, 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.

CH. Bayer, Shorttime nearthemoney skew in rough fractional volatility models, 9th International Workshop on Applied Probability, June 18  21, 2018, Eörvös Loránd University (ELU), Budapest, Hungary, June 19, 2018.

A. Mielke, Construction of effective gradient systems via EDP convergence, Workshop on Mathematical Aspects of NonEquilibrium Thermodynamics, March 5  7, 2018, RheinischWestfälische Technische Hochschule Aachen, March 6, 2018.

D.R.M. Renger, Gradient flows and GENERIC in flux space, Workshop ``Variational Methods for Evolution'', November 12  18, 2017, Mathematisches Forschungsinstitut Oberwolfach, November 16, 2017.

D.R.M. Renger, Large deviations and gradient flows, Spring School 2017: From Particle Dynamics to Gradient Flows, February 27  March 3, 2017, Technische Universität Kaiserslautern, Fachbereich Mathematik, March 1, 2017.

A. Mielke, Perspectives for gradient flows, GAMMWorkshop on Analysis of Partial Differential Equations, September 27  29, 2017, Eindhoven University of Technology, Mathematics and Computer Science Department, Netherlands, September 28, 2017.

M. Heida, Large deviation principle for a stochastic AllenCahn equation, 9th European Conference on Elliptic and Parabolic Problems, May 23  27, 2016, University of Zurich, Institute of Mathematics, Gaeta, Italy, May 25, 2016.

M. Maurelli, Enhanced Sanov theorem and large deviations for interacting particles, Workshop ``Rough Paths, Regularity Structures and Related Topics'', May 1  7, 2016, Mathematisches Forschungsinstitut Oberwolfach, May 5, 2016.

R.I.A. Patterson, Pathwise LDPs for chemical reaction networks, 12th German Probability and Statistics Days 2016  Bochumer StochastikTage, February 29  March 4, 2016, RuhrUniversität Bochum, Fakultät für Mathematik, March 4, 2016.

D.R.M. Renger, Large deviations for reacting particle systems: The empirical and ensemble processes, Workshop ``Interplay of Analysis and Probability in Applied Mathematics'', July 26  August 1, 2015, Mathematisches Forschungsinstitut Oberwolfach, Oberwolfach, July 30, 2015.

M. Maurelli, A large deviation principle for enhanced Brownian empirical measure, 4th Annual ERC BerlinOxford Young Researchers Meeting on Applied Stochastic Analysis, December 7  9, 2015, WIAS Berlin, December 8, 2015.

M. Maurelli, A large deviation principle for interacting particle SDEs via rough paths, 38th Conference on Stochastic Processes and their Applications, July 13  17, 2015, University of Oxford, OxfordMan Institute of Quantitative Finance, UK, July 14, 2015.

M. Maurelli, Enhanced Sanov theorem for Brownian rough paths and an application to interacting particles, Seminar Stochastic Analysis, Imperial College London, UK, October 20, 2015.

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 empirical process of reacting particles: Large deviations and thermodynamic principles, Minisymposium ``Real World Phenomena Explained by Microscopic Particle Models'' of the 8th International Congress on Industrial and Applied Mathematics (ICIAM 2015), August 8  22, 2015, International Council for Industrial and Applied Mathematics, Beijing, China, August 10, 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.

A. Mielke, Chemical Master Equation: Coarse graining via gradient structures, Kolloquium des SFB 1114 ``Scaling Cascades in Complex Systems'', Freie Universität Berlin, Fachbereich Mathematik, Berlin, June 4, 2015.

A. Mielke, Evolutionary $Gamma$convergence for generalized gradient systems, Workshop ``Gradient Flows'', June 22  23, 2015, Université Pierre et Marie Curie, Laboratoire JacquesLouis Lions, Paris, France, June 22, 2015.

A. Mielke, The Chemical Master Equation as a discretization of the FokkerPlanck and Liouville equation for chemical reactions, Colloquium of Collaborative Research Center/Transregio ``Discretization in Geometry and Dynamics'', Technische Universität Berlin, Institut für Mathematik, Berlin, February 10, 2015.

A. Mielke, The Chemical Master Equation as entropic gradient flow, Conference ``New Trends in Optimal Transport'', March 2  6, 2015, Universität Bonn, Institut für Angewandte Mathematik, March 2, 2015.

D.R.M. Renger, Connecting particle systems to entropydriven gradient flows, Conference ``Stochastic Processes and High Dimensional Probability Distributions'', June 16  20, 2014, Euler International Mathematical Institute, SaintPetersburg, Russian Federation, June 20, 2014.

D.R.M. Renger, Connecting particle systems to entropydriven gradient flows, Conference on Nonlinearity, Transport, Physics, and Patterns, October 6  10, 2014, Fields Institute for Research in Mathematical Sciences, Toronto, Canada, October 9, 2014.

D.R.M. Renger, Connecting particle systems to entropydriven gradient flows, Oberseminar ``Stochastische und Geometrische Analysis'', Universität Bonn, Institut für Angewandte Mathematik, May 28, 2014.

TH. Dickhaus, H. Finner, Asymptotic density crossing points of selfnormalized sums and normal, 3rd Annual International Conference on Computational Mathematics, Computational Geometry & Statistics (CMCGS 2014), February 3  4, 2014, Singapore, February 3, 2014.

T. Wolff, Annealed asymptotics for occupation time measures of a random walk among random conductances, ``Young European Probabilists 2013 (YEP X)'' and ``School on Random Polymers'', January 8  12, 2013, EURANDOM, Eindhoven, Netherlands, January 10, 2013.

W. König, Eigenvalue order statistics and mass concentration in the parabolic Anderson model, SFB/TR12 Workshop, November 4  8, 2012, Universität zu Köln, SFB TR12 ``Symmetries and Universality in Mesoscopic Systems'', Langeoog, November 7, 2012.

W. König, Large deviations for the cluster size distributions in a classical interacting manyparticle system with LennardJones potential, Mark Kac Seminar, Eindhoven University of Technology, Netherlands, November 9, 2012.

M. Becker , Random walks and selfintersections, Evolving Complex Networks (ECONS) PhdStudent Meeting, WIAS, August 24, 2010.

S. Jansen, M. Aizenman, P. Jung, Symmetry breaking in quasi 1D Coulomb systems, Combinatorics and Analysis in Spatial Probability  ESF Mathematics Conference in Partnership with EMS and ERCOM, Eindhoven, Netherlands, December 12  18, 2010.

B. Metzger, The parabolic Anderson model: The asymptotics of the statistical moments and Lifshitz tails revisited, EURANDOM, Eindhoven, Netherlands, December 1, 2010.

W. König, Die Universalitätsklassen im parabolischen AndersonModell, Mathematisches Kolloquium, Technische Universität Darmstadt, Fachbereich Mathematik, July 7, 2010.

W. König, Phase transitions for dilute particle systems with LennardJones potential, University of Bath, Department of Mathematical Sciences, UK, April 14, 2010.

W. König, The parabolic Anderson model, XIV Escola Brasileira de Probabilidade, August 2  7, 2010, Instituto Nacional de Matemática Pura e Aplicada (IMPA), Rio de Janeiro, Brazil.
External Preprints

CH. Bayer, P. Friz, P. Gassiat, J. Martin, B. Stemper , A regularity structure for rough volatility, Preprint no. arXiv:1710.07481, Cornell University Library, arXiv.org, 2017.
Abstract
A new paradigm recently emerged in financial modelling: rough (stochastic) volatility, first observed by Gatheral et al. in highfrequency data, subsequently derived within market microstructure models, also turned out to capture parsimoniously key stylized facts of the entire implied volatility surface, including extreme skews that were thought to be outside the scope of stochastic volatility. On the mathematical side, Markovianity and, partially, semimartingality are lost. In this paper we show that Hairer's regularity structures, a major extension of rough path theory, which caused a revolution in the field of stochastic partial differential equations, also provides a new and powerful tool to analyze rough volatility models. 
J.D. Deuschel, P. Friz, M. Maurelli, M. Slowik, The enhanced Sanov theorem and propagation of chaos, Preprint no. arxiv:1602.08043, Cornell University Library, arXiv.org, 2016.