@article{BittracherMoschnerKokschetal.2021, author = {Bittracher, Andreas and Moschner, Johann and Koksch, Beate and Netz, Roland and Sch{\"u}tte, Christof}, title = {Exploring the locking stage of NFGAILS amyloid fibrillation via transition manifold analysis}, volume = {94}, journal = {The European Physical Journal B}, doi = {10.1140/epjb/s10051-021-00200-0}, year = {2021}, language = {en} } @article{LueckeLuQuevedo2022, author = {L{\"u}cke, Marvin and Lu, Jingyi and Quevedo, Daniel E.}, title = {Coding for secrecy in remote state estimation with an adversary}, volume = {67}, journal = {IEEE Transactions on Automatic Control}, number = {9}, doi = {10.1109/TAC.2022.3169839}, pages = {4955 -- 4962}, year = {2022}, abstract = {We study the problem of remote state estimation in the presence of an eavesdropper. A sensor transmits state information over a packet-dropping link to a legitimate user. This information is randomly overheard by an eavesdropper. To reduce information leakage to the eavesdropper, previous studies have shown that by encoding the estimate with the acknowledgments (Acks), perfect secrecy can be achieved. However, this strategy greatly relies on the accuracy of the Acks and may easily fail if the Acks are compromised by cyberattacks. In this article, we tackle this issue by proposing to switch between sending an encoded state and sending the plain state to stay resilient against fake Acks. Specifically, we assume the Acks to be randomly attacked and derive recursive expressions for the minimum-mean-squared error estimates and error covariance matrices at the legitimate user and at the eavesdropper. Based upon this, we propose a transmission policy that depends on the probability of synchronization. We formulate a partially observable Markov decision process to model the evolution of the synchronization status and derive associated optimal transmission policies. Numerical examples are provided to verify the theoretical results.}, language = {en} } @article{CheginiKopanicakovaKrauseetal.2021, author = {Chegini, Fatemeh and Kopanicakova, Alena and Krause, Rolf and Weiser, Martin}, title = {Efficient Identification of Scars using Heterogeneous Model Hierarchies}, volume = {23}, journal = {EP Europace}, doi = {10.1093/europace/euaa402}, pages = {i113 -- i122}, year = {2021}, abstract = {Aims. Detection and quantification of myocardial scars are helpful both for diagnosis of heart diseases and for building personalized simulation models. Scar tissue is generally charac­terized by a different conduction of electrical excitation. We aim at estimating conductivity-related parameters from endocardial mapping data, in particular the conductivity tensor. Solving this inverse problem requires computationally expensive monodomain simulations on fine discretizations. Therefore, we aim at accelerating the estimation using a multilevel method combining electrophysiology models of different complexity, namely the mono­domain and the eikonal model. Methods. Distributed parameter estimation is performed by minimizing the misfit between simulated and measured electrical activity on the endocardial surface, subject to the mono­domain model and regularization, leading to a constrained optimization problem. We formulate this optimization problem, including the modeling of scar tissue and different regularizations, and design an efficient iterative solver. We consider monodomain grid hierarchies and monodomain-eikonal model hierarchies in a recursive multilevel trust-region method. Results. From several numerical examples, both the efficiency of the method and the estimation quality, depending on the data, are investigated. The multilevel solver is significantly faster than a comparable single level solver. Endocardial mapping data of realistic density appears to be just sufficient to provide quantitatively reasonable estimates of location, size, and shape of scars close to the endocardial surface. Conclusion. In several situations, scar reconstruction based on eikonal and monodomain models differ significantly, suggesting the use of the more accurate but more expensive monodomain model for this purpose. Still, eikonal models can be utilized to accelerate the computations considerably, enabling the use of complex electrophysiology models for estimating myocardial scars from endocardial mapping data.}, language = {en} } @inproceedings{JaegerTillmannKatzetal.2020, author = {J{\"a}ger, Klaus and Tillmann, Peter and Katz, Eugene A. and Becker, Christiane}, title = {Simulating bifacial perovskite/silicon tandem solar cells in large PV fields}, booktitle = {OSA Advanced Photonics Congress}, doi = {10.1364/PVLED.2020.PvTh1G.3}, pages = {PvTh1G.3}, year = {2020}, language = {en} } @article{JaegerTillmannKatzetal.2021, author = {J{\"a}ger, Klaus and Tillmann, Peter and Katz, Eugene A. and Becker, Christiane}, title = {Perovskite/silicon tandem solar cells: Effect of luminescent coupling and bifaciality}, volume = {5}, journal = {Sol. RRL}, arxiv = {http://arxiv.org/abs/2008.13696}, doi = {10.1002/solr.202000628}, pages = {2000628}, year = {2021}, language = {en} } @article{HelfmannHeitzigKoltaietal.2021, author = {Helfmann, Luzie and Heitzig, Jobst and Koltai, P{\´e}ter and Kurths, J{\"u}rgen and Sch{\"u}tte, Christof}, title = {Statistical analysis of tipping pathways in agent-based models}, volume = {230}, journal = {Eur. Phys. J. Spec. Top.}, arxiv = {http://arxiv.org/abs/2103.02883}, doi = {10.1140/epjs/s11734-021-00191-0}, pages = {3249 -- 3271}, year = {2021}, abstract = {Agent-based models are a natural choice for modeling complex social systems. In such models simple stochastic interaction rules for a large population of individuals on the microscopic scale can lead to emergent dynamics on the macroscopic scale, for instance a sudden shift of majority opinion or behavior. Here we are introducing a methodology for studying noise-induced tipping between relevant subsets of the agent state space representing characteristic configurations. Due to a large number of interacting individuals, agent-based models are high-dimensional, though usually a lower-dimensional structure of the emerging collective behaviour exists. We therefore apply Diffusion Maps, a non-linear dimension reduction technique, to reveal the intrinsic low-dimensional structure. We characterize the tipping behaviour by means of Transition Path Theory, which helps gaining a statistical understanding of the tipping paths such as their distribution, flux and rate. By systematically studying two agent-based models that exhibit a multitude of tipping pathways and cascading effects, we illustrate the practicability of our approach.}, language = {en} } @article{ManleySegantiniAhibozetal.2021, author = {Manley, Phillip and Segantini, Michele and Ahiboz, Doguscan and Hammerschmidt, Martin and Arnaoutakis, Georgios and MacQueen, Rowan W. and Burger, Sven and Becker, Christiane}, title = {Double-layer metasurface for enhanced photon up-conversion}, volume = {6}, journal = {APL Photon.}, arxiv = {http://arxiv.org/abs/2012.03587}, doi = {10.1063/5.0040839}, pages = {036103}, year = {2021}, language = {en} } @article{PakhomovHammerschmidtBurgeretal.2021, author = {Pakhomov, Anton V. and Hammerschmidt, Martin and Burger, Sven and Pertsch, Thomas and Setzpfand, Frank}, title = {Modeling of surface-induced second-harmonic generation from multilayer structures by the transfer matrix method}, volume = {29}, journal = {Opt. Express}, doi = {10.1364/OE.417066}, pages = {9098}, year = {2021}, language = {en} } @article{BinkowskiWuLalanneetal.2021, author = {Binkowski, Felix and Wu, Tong and Lalanne, Philippe and Burger, Sven and Govorov, Alexander O.}, title = {Hot Electron Generation through Near-Field Excitation of Plasmonic Nanoresonators}, volume = {8}, journal = {ACS Photonics}, arxiv = {http://arxiv.org/abs/2103.06652}, doi = {10.1021/acsphotonics.1c00231}, pages = {1243}, year = {2021}, language = {en} } @article{CvetkovicConradLie2021, author = {Cvetkovic, Nada and Conrad, Tim and Lie, Han Cheng}, title = {A Convergent Discretisation Method for Transition Path Theory for Diffusion Processes}, volume = {19}, journal = {Multiscale Modeling \& Simulation}, number = {1}, publisher = {Society for Industrial and Applied Mathematics}, doi = {10.1137/20M1329354}, pages = {242 -- 266}, year = {2021}, language = {en} } @book{DeuflhardWeiser2020, author = {Deuflhard, Peter and Weiser, Martin}, title = {Numerische Mathematik 3. Adaptive L{\"o}sung partieller Differentialgleichungen}, edition = {2}, publisher = {de Gruyter}, isbn = {978-3-11-069168-9}, doi = {10.1515/9783110689655}, pages = {456}, year = {2020}, language = {de} } @article{SikorskiWeberSchuette2021, author = {Sikorski, Alexander and Weber, Marcus and Sch{\"u}tte, Christof}, title = {The Augmented Jump Chain}, volume = {4}, journal = {Advanced Theory and Simulations}, number = {4}, publisher = {Wiley-VCH}, arxiv = {http://arxiv.org/abs/2008.04624}, doi = {10.1002/adts.202000274}, year = {2021}, abstract = {Modern methods of simulating molecular systems are based on the mathematical theory of Markov operators with a focus on autonomous equilibrated systems. However, non-autonomous physical systems or non-autonomous simulation processes are becoming more and more important. A representation of non-autonomous Markov jump processes is presented as autonomous Markov chains on space-time. Augmenting the spatial information of the embedded Markov chain by the temporal information of the associated jump times, the so-called augmented jump chain is derived. The augmented jump chain inherits the sparseness of the infinitesimal generator of the original process and therefore provides a useful tool for studying time-dependent dynamics even in high dimensions. Furthermore, possible generalizations and applications to the computation of committor functions and coherent sets in the non-autonomous setting are discussed. After deriving the theoretical foundations, the concepts with a proof-of-concept Galerkin discretization of the transfer operator of the augmented jump chain applied to simple examples are illustrated.}, language = {en} } @article{SechiSikorskiWeber2021, author = {Sechi, Renata and Sikorski, Alexander and Weber, Marcus}, title = {Estimation of the Koopman Generator by Newton's Extrapolation}, volume = {19}, journal = {Multiscale Modeling and Simulation}, number = {2}, publisher = {SIAM}, doi = {10.1137/20M1333006}, pages = {758 -- 774}, year = {2021}, abstract = {This article addresses the problem of estimating the Koopman generator of a Markov process. The direct computation of the infinitesimal generator is not easy because of the discretization of the state space, in particular because of the trade-off inherent in the choice of the best lag time to study the process. Short lag times implies a strong discretization of the state space and a consequent loss of Markovianity. Large lag times bypass events on fast timescales. We propose a method to approximate the generator with the computation of the Newton polynomial extrapolation. This technique is a multistep approach which uses as its input Koopman transfer operators evaluated for a series of lag times. Thus, the estimated infinitesimal generator combines information from different time resolutions and does not bias only fast- or slow-decaying dynamics. We show that the multi-scale Newton method can improve the estimation of the generator in comparison to the computation using finite difference or matrix logarithm methods.}, language = {en} } @phdthesis{Venkatareddy2020, author = {Venkatareddy, Narendra Lagumaddepalli}, title = {Revealing secrets of mussel-glue mimetic peptides - From advanced NMR to computational process modelling}, year = {2020}, language = {en} } @phdthesis{Eshtewy2020, author = {Eshtewy, Neveen Ali Salem}, title = {Mathematical Modeling of Metabolic-Genetic Networks}, year = {2020}, language = {en} } @article{OettingerMontefuscoPeletier2021, author = {{\"O}ttinger, Hans Christian and Montefusco, Alberto and Peletier, Mark A.}, title = {A Framework of Nonequilibrium Statistical Mechanics. I. Role and Types of Fluctuations}, volume = {46}, journal = {Journal of Non-Equilibrium Thermodynamics}, number = {1}, publisher = {De Gruyter}, doi = {10.1515/jnet-2020-0068}, pages = {1 -- 13}, year = {2021}, abstract = {Understanding the fluctuations by which phenomenological evolution equations with thermodynamic structure can be enhanced is the key to a general framework of nonequilibrium statistical mechanics. These fluctuations provide an idealized representation of microscopic details. We consider fluctuation-enhanced equations associated with Markov processes and elaborate the general recipes for evaluating dynamic material properties, which characterize force-flux constitutive laws, by statistical mechanics. Markov processes with continuous trajectories are conveniently characterized by stochastic differential equations and lead to Green-Kubo-type formulas for dynamic material properties. Markov processes with discontinuous jumps include transitions over energy barriers with the rates calculated by Kramers. We describe a unified approach to Markovian fluctuations and demonstrate how the appropriate type of fluctuations (continuous versus discontinuous) is reflected in the mathematical structure of the phenomenological equations.}, language = {en} } @article{MontefuscoPeletierOettinger2021, author = {Montefusco, Alberto and Peletier, Mark A. and {\"O}ttinger, Hans Christian}, title = {A Framework of Nonequilibrium Statistical Mechanics. II. Coarse-Graining}, volume = {46}, journal = {Journal of Non-Equilibrium Thermodynamics}, number = {1}, publisher = {De Gruyter}, doi = {10.1515/jnet-2020-0069}, pages = {15 -- 33}, year = {2021}, abstract = {For a given thermodynamic system, and a given choice of coarse-grained state variables, the knowledge of a force-flux constitutive law is the basis for any nonequilibrium modeling. In the first paper of this series we established how, by a generalization of the classical fluctuation-dissipation theorem (FDT), the structure of a constitutive law is directly related to the distribution of the fluctuations of the state variables. When these fluctuations can be expressed in terms of diffusion processes, one may use Green-Kubo-type coarse-graining schemes to find the constitutive laws. In this paper we propose a coarse-graining method that is valid when the fluctuations are described by means of general Markov processes, which include diffusions as a special case. We prove the success of the method by numerically computing the constitutive law for a simple chemical reaction A⇄B. Furthermore, we show that, for such a system, one cannot find a consistent constitutive law by any Green-Kubo-like scheme.}, language = {en} } @article{SunkaraHeinzHeinrichetal.2020, author = {Sunkara, Vikram and Heinz, Gitta A. and Heinrich, Frederik F. and Durek, Pawel and Mobasheri, Ali and Mashreghi, Mir-Farzin and Lang, Annemarie}, title = {Combining segmental bulk- and single-cell RNA-sequencing to define the chondrocyte gene expression signature in the murine knee joint}, journal = {bioarxiv (Accepted in Osteoarthr. Cartil.)}, doi = {10.1101/2020.06.13.148056}, year = {2020}, language = {en} } @article{LangHelfmeierStefanowskietal.2020, author = {Lang, Annemarie and Helfmeier, Sarah and Stefanowski, Jonathan and Kuppe, Aditi and Sunkara, Vikram and Pfeiffenberger, Moritz and Wolter, Angelique and Damerau, Alexandra and Hemmati-Sadeghi, Shabnam and Ringe, Jochen and Haag, Rainer and Hauser, Anja E. and L{\"o}hning, Max and Perka, Carsten and Duda, Georg and Hoff, Paula and Schmidt-Bleek, Katharina and Gaber, Timo and Buttgereit, Frank}, title = {HIF-stabilization prevents delayed fracture healing}, journal = {bioarxiv}, doi = {10.1101/2020.07.02.182832}, year = {2020}, language = {en} } @article{LaydonSunkaraBoelenetal.2020, author = {Laydon, Daniel J. and Sunkara, Vikram and Boelen, Lies and Bangham, Charles R. M. and Asquith, Becca}, title = {The relative contributions of infectious and mitotic spread to HTLV-1 persistence}, journal = {PLOS Computational Biology}, doi = {10.1371/journal.pcbi.1007470}, year = {2020}, language = {en} } @article{SchielaStoeckleinWeiser2021, author = {Schiela, Anton and St{\"o}cklein, Matthias and Weiser, Martin}, title = {A primal dual projection algorithm for efficient constraint preconditioning}, volume = {43}, journal = {SIAM Journal on Scientific Computing}, number = {6}, doi = {10.1137/20M1380739}, pages = {A4095 -- A4120}, year = {2021}, abstract = {We consider a linear iterative solver for large scale linearly constrained quadratic minimization problems that arise, for example, in optimization with PDEs. By a primal-dual projection (PDP) iteration, which can be interpreted and analysed as a gradient method on a quotient space, the given problem can be solved by computing sulutions for a sequence of constrained surrogate problems, projections onto the feasible subspaces, and Lagrange multiplier updates. As a major application we consider a class of optimization problems with PDEs, where PDP can be applied together with a projected cg method using a block triangular constraint preconditioner. Numerical experiments show reliable and competitive performance for an optimal control problem in elasticity.}, language = {en} } @article{MielkeMontefuscoPeletier2021, author = {Mielke, Alexander and Montefusco, Alberto and Peletier, Mark A.}, title = {Exploring families of energy-dissipation landscapes via tilting: three types of EDP convergence}, volume = {33}, journal = {Continuum Mechanics and Thermodynamics}, publisher = {Springer}, doi = {10.1007/s00161-020-00932-x}, pages = {611 -- 637}, year = {2021}, abstract = {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 well-known 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 Energy-Dissipation Principle that provides a variational formulation to gradient-flow equations that allows one to apply techniques from Γ-convergence of functional on states and functionals on trajectories.}, language = {en} } @phdthesis{Santiago2021, author = {Santiago, Xavier Garcia}, title = {Numerical methods for shape optimization of photonic nanostructures}, organization = {Karlsruher Institut f{\"u}r Technologie}, doi = {10.5445/IR/1000131006}, year = {2021}, language = {en} } @article{RaharinirinaAcevedoTrejosMerico2022, author = {Raharinirina, N. Alexia and Acevedo-Trejos, Esteban and Merico, Agostino}, title = {Modelling the acclimation capacity of coral reefs to a warming ocean}, journal = {PLOS COMPUTATIONAL BIOLOGY}, doi = {10.1371/journal.pcbi.1010099}, year = {2022}, abstract = {The symbiotic relationship between corals and photosynthetic algae is the foundation of coral reef ecosystems. This relationship breaks down, leading to coral death, when sea temperature exceeds the thermal tolerance of the coral-algae complex. While acclimation via phenotypic plasticity at the organismal level is an important mechanism for corals to cope with global warming, community-based shifts in response to acclimating capacities may give valuable indications about the future of corals at a regional scale. Reliable regional-scale predictions, however, are hampered by uncertainties on the speed with which coral communities will be able to acclimate. Here we present a trait-based, acclimation dynamics model, which we use in combination with observational data, to provide a first, crude estimate of the speed of coral acclimation at the community level and to investigate the effects of different global warming scenarios on three iconic reef ecosystems of the tropics: Great Barrier Reef, South East Asia, and Caribbean. The model predicts that coral acclimation may confer some level of protection by delaying the decline of some reefs such as the Great Barrier Reef. However, the current rates of acclimation will not be sufficient to rescue corals from global warming. Based on our estimates of coral acclimation capacities, the model results suggest substantial declines in coral abundances in all three regions, ranging from 12\% to 55\%, depending on the region and on the climate change scenario considered. Our results highlight the importance and urgency of precise assessments and quantitative estimates, for example through laboratory experiments, of the natural acclimation capacity of corals and of the speed with which corals may be able to acclimate to global warming.}, language = {en} } @misc{SchuetteKlusHartmann2022, author = {Sch{\"u}tte, Christof and Klus, Stefan and Hartmann, Carsten}, title = {Overcoming the Timescale Barrier in Molecular Dynamics: Transfer Operators, Variational Principles, and Machine Learning}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-88637}, year = {2022}, abstract = {One of the main challenges in molecular dynamics is overcoming the "timescale barrier", a phrase used to describe that in many realistic molecular systems, biologically important rare transitions occur on timescales that are not accessible to direct numerical simulation, not even on the largest or specifically dedicated supercomputers. This article discusses how to circumvent the timescale barrier by a collection of transfer operator-based techniques that have emerged from dynamical systems theory, numerical mathematics, and machine learning over the last two decades. We will focus on how transfer operators can be used to approximate the dynamical behavior on long timescales, review the introduction of this approach into molecular dynamics, and outline the respective theory as well as the algorithmic development from the early numerics-based methods, via variational reformulations, to modern data-based techniques utilizing and improving concepts from machine learning. Furthermore, its relation to rare event simulation techniques will be explained, revealing a broad equivalence of variational principles for long-time quantities in MD. The article will mainly take a mathematical perspective and will leave the application to real-world molecular systems to the more than 1000 research articles already written on this subject.}, language = {en} } @article{RamosLeiteZschiedrichKizilkayaetal.2022, author = {Ramos Leite, Tiago and Zschiedrich, Lin and Kizilkaya, Orhan and McPeak, Kevin M.}, title = {Resonant Plasmonic-Biomolecular Chiral Interactions in the Far-Ultraviolet: Enantiomeric Discrimination of sub-10 nm Amino Acid Films}, volume = {22}, journal = {Nano Lett.}, doi = {10.1021/acs.nanolett.2c01724}, pages = {7343}, year = {2022}, language = {en} } @article{RejSantiagoBaturinaetal.2022, author = {Rej, Sourav and Santiago, Eva Yazmin and Baturina, Olga and Zhang, Yu and Burger, Sven and Kment, Stepan and Govorov, Alexander O. and Naldoni, Alberto}, title = {Colloidal Titanium Nitride Nanobars for Broadband Inexpensive Plasmonics and Photochemistry from Visible to Mid-IR Wavelengths}, volume = {104}, journal = {Nano Energy}, arxiv = {http://arxiv.org/abs/2209.04678}, doi = {10.1016/j.nanoen.2022.107989}, pages = {107989}, year = {2022}, language = {en} } @inproceedings{BernerRichterUllrich2024, author = {Berner, Julius and Richter, Lorenz and Ullrich, Karen}, title = {An optimal control perspective on diffusion-based generative modeling}, booktitle = {Transactions on Machine Learning Research}, year = {2024}, abstract = {We establish a connection between stochastic optimal control and generative models based on stochastic differential equations (SDEs) such as recently developed diffusion probabilistic models. In particular, we derive a Hamilton-Jacobi-Bellman equation that governs the evolution of the log-densities of the underlying SDE marginals. This perspective allows to transfer methods from optimal control theory to generative modeling. First, we show that the evidence lower bound is a direct consequence of the well-known verification theorem from control theory. Further, we develop a novel diffusion-based method for sampling from unnormalized densities -- a problem frequently occurring in statistics and computational sciences.}, language = {en} } @article{NueskenRichter2023, author = {N{\"u}sken, Nikolas and Richter, Lorenz}, title = {Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems}, volume = {2}, journal = {Journal of Machine Learning}, number = {1}, arxiv = {http://arxiv.org/abs/2112.03749}, doi = {0.4208/jml.220416}, pages = {31 -- 64}, year = {2023}, abstract = {Solving high-dimensional partial differential equations is a recurrent challenge in economics, science and engineering. In recent years, a great number of computational approaches have been developed, most of them relying on a combination of Monte Carlo sampling and deep learning based approximation. For elliptic and parabolic problems, existing methods can broadly be classified into those resting on reformulations in terms of backward stochastic differential equations (BSDEs) and those aiming to minimize a regression-type L2-error (physics-informed neural networks, PINNs). In this paper, we review the literature and suggest a methodology based on the novel diffusion loss that interpolates between BSDEs and PINNs. Our contribution opens the door towards a unified understanding of numerical approaches for high-dimensional PDEs, as well as for implementations that combine the strengths of BSDEs and PINNs. The diffusion loss furthermore bears close similarities to (least squares) temporal difference objectives found in reinforcement learning. We also discuss eigenvalue problems and perform extensive numerical studies, including calculations of the ground state for nonlinear Schr ¨odinger operators and committor functions relevant in molecular dynamics.}, language = {en} } @article{HartmannRichter2024, author = {Hartmann, Carsten and Richter, Lorenz}, title = {Nonasymptotic bounds for suboptimal importance sampling}, volume = {12}, journal = {SIAM/ASA Journal on Uncertainty Quantification}, number = {2}, arxiv = {http://arxiv.org/abs/2102.09606}, doi = {10.1137/21M1427760}, pages = {309 -- 346}, year = {2024}, abstract = {Importance sampling is a popular variance reduction method for Monte Carlo estimation, where an evident question is how to design good proposal distributions. While in most cases optimal (zero-variance) estimators are theoretically possible, in practice only suboptimal proposal distributions are available and it can often be observed numerically that those can reduce statistical performance significantly, leading to large relative errors and therefore counteracting the original intention. Previous analysis on importance sampling has often focused on asymptotic arguments that work well in a large deviations regime. In this article, we provide lower and upper bounds on the relative error in a nonasymptotic setting. They depend on the deviation of the actual proposal from optimality, and we thus identify potential robustness issues that importance sampling may have, especially in high dimensions. We particularly focus on path sampling problems for diffusion processes with nonvanishing noise, for which generating good proposals comes with additional technical challenges. We provide numerous numerical examples that support our findings and demonstrate the applicability of the derived bounds.}, language = {en} } @article{RickertBetzPlocketal.2023, author = {Rickert, Lucas and Betz, Fridtjof and Plock, Matthias and Burger, Sven and Heindel, Tobias}, title = {High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings}, volume = {31}, journal = {Opt. Express}, arxiv = {http://arxiv.org/abs/2212.04883}, doi = {10.1364/OE.486060}, pages = {14750}, year = {2023}, language = {en} } @misc{RickertBetzPlocketal.2022, author = {Rickert, Lucas and Betz, Fridtjof and Plock, Matthias and Burger, Sven and Heindel, Tobias}, title = {Data publication for "High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings"}, journal = {Zenodo}, doi = {10.5281/zenodo.7360516}, pages = {7360516}, year = {2022}, language = {en} } @article{GorgullaJayarajFackeldeyetal.2022, author = {Gorgulla, Christoph and Jayaraj, Abhilash and Fackeldey, Konstantin and Arthanari, Haribabu}, title = {Emerging frontiers in virtual drug discovery: From quantum mechanical methods to deep learning approaches}, volume = {69}, journal = {Current Opinion in Chemical Biology}, doi = {10.1016/j.cbpa.2022.102156}, pages = {102156 -- 102156-12}, year = {2022}, abstract = {Virtual screening-based approaches to discover initial hit and lead compounds have the potential to reduce both the cost and time of early drug discovery stages, as well as to find inhibitors for even challenging target sites such as protein-protein interfaces. Here in this review, we provide an overview of the progress that has been made in virtual screening methodology and technology on multiple fronts in recent years. The advent of ultra-large virtual screens, in which hundreds of millions to billions of compounds are screened, has proven to be a powerful approach to discover highly potent hit compounds. However, these developments are just the tip of the iceberg, with new technologies and methods emerging to propel the field forward. Examples include novel machine-learning approaches, which can reduce the computational costs of virtual screening dramatically, while progress in quantum-mechanical approaches can increase the accuracy of predictions of various small molecule properties.}, language = {en} } @misc{StraubeWinkelmannHoefling2022, author = {Straube, Arthur and Winkelmann, Stefanie and H{\"o}fling, Felix}, title = {Accurate reduced models for the pH oscillations in the urea-urease reaction confined to giant lipid vesicles}, issn = {1438-0064}, doi = {10.12752/8817}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-88179}, year = {2022}, abstract = {Our theoretical study concerns an urea-urease-based pH oscillator confined to giant lipid vesicles. Under suitable conditions, differential transport of urea and hydrogen ion across the unilamellar vesicle membrane periodically resets the pH clock that switches the system from acid to basic, resulting in self-sustained oscillations. We analyse the structure of the limit cycle, which controls the dynamics for giant vesicles and dominates the strongly stochastic oscillations in small vesicles of submicrometer size. To this end, we derive reduced models, amenable to analytic treatments, and show that the accuracy of predictions, including the period of oscillations, is highly sensitive to the choice of the reduction scheme. In particular, we suggest an accurate two-variable model and show its equivalence to a three-variable model that admits an interpretation in terms of a chemical reaction network. The accurate description of a single pH oscillator appears crucial for rationalizing experiments and understanding communication of vesicles and synchronization of rhythms.}, language = {en} } @article{DonatiWeber2022, author = {Donati, Luca and Weber, Marcus}, title = {Assessing transition rates as functions of environmental variables}, volume = {157}, journal = {The Journal of Chemical Physics}, number = {22}, publisher = {AIP Publishing}, doi = {10.1063/5.0109555}, pages = {224103-1 -- 224103-14}, year = {2022}, abstract = {We present a method to estimate the transition rates of molecular systems under different environmental conditions which cause the formation or the breaking of bonds and require the sampling of the Grand Canonical Ensemble. For this purpose, we model the molecular system in terms of probable "scenarios", governed by different potential energy functions, which are separately sampled by classical MD simulations. Reweighting the canonical distribution of each scenario according to specific environmental variables, we estimate the grand canonical distribution, then we use the Square Root Approximation (SqRA) method to discretize the Fokker-Planck operator into a rate matrix and the robust Perron Cluster Cluster Analysis (PCCA+) method to coarse-grain the kinetic model. This permits to efficiently estimate the transition rates of conformational states as functions of environmental variables, for example, the local pH at a cell membrane. In this work we formalize the theoretical framework of the procedure and we present a numerical experiment comparing the results with those provided by a constant-pH method based on non-equilibrium Molecular Dynamics Monte Carlo simulations. The method is relevant for the development of new drug design strategies which take into account how the cellular environment influences biochemical processes.}, language = {en} } @article{SechiFackeldeyChewleetal.2022, author = {Sechi, Renata and Fackeldey, Konstantin and Chewle, Surahit and Weber, Marcus}, title = {SepFree NMF: A Toolbox for Analyzing the Kinetics of Sequential Spectroscopic Data}, volume = {15}, journal = {Algorithms}, number = {9}, doi = {10.3390/a15090297}, pages = {297}, year = {2022}, abstract = {This work addresses the problem of determining the number of components from sequential spectroscopic data analyzed by non-negative matrix factorization without separability assumption (SepFree NMF). These data are stored in a matrix M of dimension "measured times" versus "measured wavenumbers" and can be decomposed to obtain the spectral fingerprints of the states and their evolution over time. SepFree NMF assumes a memoryless (Markovian) process to underline the dynamics and decomposes M so that M=WH, with W representing the components' fingerprints and H their kinetics. However, the rank of this decomposition (i.e., the number of physical states in the process) has to be guessed from pre-existing knowledge on the observed process. We propose a measure for determining the number of components with the computation of the minimal memory effect resulting from the decomposition; by quantifying how much the obtained factorization is deviating from the Markovian property, we are able to score factorizations of a different number of components. In this way, we estimate the number of different entities which contribute to the observed system, and we can extract kinetic information without knowing the characteristic spectra of the single components. This manuscript provides the mathematical background as well as an analysis of computer generated and experimental sequentially measured Raman spectra.}, language = {en} } @article{DjurdjevacConradKoepplDjurdjevac2022, author = {Djurdjevac Conrad, Natasa and K{\"o}ppl, Jonas and Djurdjevac, Ana}, title = {Feedback Loops in Opinion Dynamics of Agent-Based Models with Multiplicative Noise}, volume = {24(10)}, journal = {Entropy}, arxiv = {http://arxiv.org/abs/2209.07151}, doi = {10.3390/e24101352}, year = {2022}, abstract = {We introduce an agent-based model for co-evolving opinions 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 the positions and opinions of other agents and similarly, the opinion dynamics are influenced by agents' spatial proximity and their opinion similarity. Using numerical simulations and formal analyses, we study this feedback loop between opinion dynamics and the mobility of agents in a social space. We investigate the behaviour of this ABM in different regimes and explore the influence of various factors on the 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.}, language = {en} } @article{DonatiWeberKeller2022, author = {Donati, Luca and Weber, Marcus and Keller, Bettina G.}, title = {A review of Girsanov Reweighting and of Square Root Approximation for building molecular Markov State Models}, volume = {63}, journal = {Journal of Mathematical Physics}, number = {12}, publisher = {AIP Publishing}, doi = {10.1063/5.0127227}, pages = {123306-1 -- 123306-21}, year = {2022}, abstract = {Dynamical reweighting methods permit to estimate kinetic observables of a stochastic process governed by a target potential U(x) from trajectories that have been generated at a different potential V(x). In this article, we present Girsanov reweighting and Square Root Approximation (SqRA): the first method reweights path probabilities exploiting the Girsanov theorem and can be applied to Markov State Models (MSMs) to reweight transition probabilities; the second method was originally developed to discretize the Fokker-Planck operator into a transition rate matrix, but here we implement it into a reweighting scheme for transition rates. We begin by reviewing the theoretical background of the methods, then present two applications relevant to Molecular Dynamics (MD), highlighting their strengths and weaknesses.}, language = {en} } @article{QuerRiberaBorrell2024, author = {Quer, Jannes and Ribera Borrell, Enric}, title = {Connecting Stochastic Optimal Control and Reinforcement Learning}, volume = {65}, journal = {Journal of Mathematical Physics}, number = {8}, doi = {10.1063/5.0140665}, year = {2024}, abstract = {In this paper the connection between stochastic optimal control and reinforcement learning is investigated. Our main motivation is to apply importance sampling to sampling rare events which can be reformulated as an optimal control problem. By using a parameterised approach the optimal control problem becomes a stochastic optimization problem which still raises some open questions regarding how to tackle the scalability to high-dimensional problems and how to deal with the intrinsic metastability of the system. To explore new methods we link the optimal control problem to reinforcement learning since both share the same underlying framework, namely a Markov Decision Process (MDP). For the optimal control problem we show how the MDP can be formulated. In addition we discuss how the stochastic optimal control problem can be interpreted in the framework of reinforcement learning. At the end of the article we present the application of two different reinforcement learning algorithms to the optimal control problem and a comparison of the advantages and disadvantages of the two algorithms.}, language = {en} } @article{RayFackeldeySteinetal.2023, author = {Ray, Sourav and Fackeldey, Konstantin and Stein, Christoph and Weber, Marcus}, title = {Coarse Grained MD Simulations of Opioid interactions with the µ-opioid receptor and the surrounding lipid membrane}, volume = {3}, journal = {Biophysica}, number = {2}, doi = {10.3390/biophysica3020017}, pages = {263 -- 275}, year = {2023}, abstract = {In our previous studies, a new opioid (NFEPP) was developed to only selectively bind to the 𝜇-opoid receptor (MOR) in inflamed tissue and thus avoid the severe side effects of fentanyl. We know that NFEPP has a reduced binding affinity to MOR in healthy tissue. Inspired by the modelling and simulations performed by Sutcliffe et al., we present our own results of coarse-grained molecular dynamics simulations of fentanyl and NFEPP with regards to their interaction with the 𝜇-opioid receptor embedded within the lipid cell membrane. For technical reasons, we have slightly modified Sutcliffe's parametrisation of opioids. The pH-dependent opioid simulations are of interest because while fentanyl is protonated at the physiological pH, NFEPP is deprotonated due to its lower pKa value than that of fentanyl. Here, we analyse for the first time whether pH changes have an effect on the dynamical behaviour of NFEPP when it is inside the cell membrane. Besides these changes, our analysis shows a possible alternative interaction of NFEPP at pH 7.4 outside the binding region of the MOR. The interaction potential of NFEPP with MOR is also depicted by analysing the provided statistical molecular dynamics simulations with the aid of an eigenvector analysis of a transition rate matrix. In our modelling, we see differences in the XY-diffusion profiles of NFEPP compared with fentanyl in the cell membrane.}, language = {en} } @inproceedings{RichterBerner2022, author = {Richter, Lorenz and Berner, Julius}, title = {Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning}, volume = {162}, booktitle = {Proceedings of the 39th International Conference on Machine Learning, PMLR}, pages = {18649 -- 18666}, year = {2022}, abstract = {The combination of Monte Carlo methods and deep learning has recently led to efficient algorithms for solving partial differential equations (PDEs) in high dimensions. Related learning problems are often stated as variational formulations based on associated stochastic differential equations (SDEs), which allow the minimization of corresponding losses using gradient-based optimization methods. In respective numerical implementations it is therefore crucial to rely on adequate gradient estimators that exhibit low variance in order to reach convergence accurately and swiftly. In this article, we rigorously investigate corresponding numerical aspects that appear in the context of linear Kolmogorov PDEs. In particular, we systematically compare existing deep learning approaches and provide theoretical explanations for their performances. Subsequently, we suggest novel methods that can be shown to be more robust both theoretically and numerically, leading to substantial performance improvements.}, language = {en} } @article{delRazoWinkelmannKleinetal.2023, author = {del Razo, Mauricio and Winkelmann, Stefanie and Klein, Rupert and H{\"o}fling, Felix}, title = {Chemical diffusion master equation: formulations of reaction-diffusion processes on the molecular level}, volume = {64}, journal = {Journal of Mathematical Physics}, number = {1}, arxiv = {http://arxiv.org/abs/2210.02268}, doi = {10.1063/5.0129620}, year = {2023}, abstract = {The chemical diffusion master equation (CDME) describes the probabilistic dynamics of reaction--diffusion systems at the molecular level [del Razo et al., Lett. Math. Phys. 112:49, 2022]; it can be considered the master equation for reaction--diffusion processes. The CDME consists of an infinite ordered family of Fokker--Planck equations, where each level of the ordered family corresponds to a certain number of particles and each particle represents a molecule. The equations at each level describe the spatial diffusion of the corresponding set of particles, and they are coupled to each other via reaction operators --linear operators representing chemical reactions. These operators change the number of particles in the system, and thus transport probability between different levels in the family. In this work, we present three approaches to formulate the CDME and show the relations between them. We further deduce the non-trivial combinatorial factors contained in the reaction operators, and we elucidate the relation to the original formulation of the CDME, which is based on creation and annihilation operators acting on many-particle probability density functions. Finally we discuss applications to multiscale simulations of biochemical systems among other future prospects.}, language = {en} } @article{LueckeHeitzigKoltaietal.2023, author = {L{\"u}cke, Marvin and Heitzig, Jobst and Koltai, P{\´e}ter and Molkethin, Nora and Winkelmann, Stefanie}, title = {Large population limits of Markov processes on random networks}, volume = {166}, journal = {Stochastic Processes and their Applications}, arxiv = {http://arxiv.org/abs/2210.02934}, doi = {10.1016/j.spa.2023.09.007}, year = {2023}, abstract = {We consider time-continuous Markovian discrete-state dynamics on random networks of interacting agents and study the large population limit. The dynamics are projected onto low-dimensional collective variables given by the shares of each discrete state in the system, or in certain subsystems, and general conditions for the convergence of the collective variable dynamics to a mean-field ordinary differential equation are proved. We discuss the convergence to this mean-field limit for a continuous-time noisy version of the so-called "voter model" on Erdős-R{\´e}nyi random graphs, on the stochastic block model, as well as on random regular graphs. Moreover, a heterogeneous population of agents is studied. For each of these types of interaction networks, we specify the convergence conditions in dependency on the corresponding model parameters.}, language = {en} } @inproceedings{SchneiderZschiedrichHammerschmidtetal.2022, author = {Schneider, Philipp-Immanuel and Zschiedrich, Lin and Hammerschmidt, Martin and Kuen, Lilli and Sekulic, Ivan and Kluge, Julien and Leykauf, Bastian and Krutzik, Markus and Burger, Sven}, title = {Boosting quantum optics experiments with Bayesian optimization}, volume = {12227}, booktitle = {Proc. SPIE}, doi = {10.1117/12.2632419}, pages = {122270F}, year = {2022}, language = {en} } @inproceedings{KruegerManleyZschiedrichetal.2022, author = {Kr{\"u}ger, Jan and Manley, Phillip and Zschiedrich, Lin and Hammerschmidt, Martin and Schneider, Philipp-Immanuel and K{\"o}ning, Rainer and Bodermann, Bernd}, title = {Untersuchung des Schwingungseinflusses auf gemessene Punktspreizfunktionen in der optischen Mikroskopie}, booktitle = {Proc. DGaO}, url = {http://nbn-resolving.de/urn:nbn:de:0287-2022-P005-6}, pages = {P5}, year = {2022}, language = {en} } @article{BoppPlockTuranetal.2024, author = {Bopp, Julian M. and Plock, Matthias and Turan, Tim and Pieplow, Gregor and Burger, Sven and Schr{\"o}der, Tim}, title = {Sawfish Photonic Crystal Cavity for Near-Unity Emitter-to-Fiber Interfacing in Quantum Network Applications}, volume = {12}, journal = {Adv. Opt. Mater.}, arxiv = {http://arxiv.org/abs/2210.04702}, doi = {10.1002/adom.202301286}, pages = {2301286}, year = {2024}, language = {en} } @inproceedings{ManleyKruegerZschiedrichetal.2022, author = {Manley, Phillip and Kr{\"u}ger, Jan and Zschiedrich, Lin and Hammerschmidt, Martin and Bodermann, Bernd and K{\"o}ning, Rainer and Schneider, Philipp-Immanuel}, title = {Elementary, my dear Zernike: model order reduction for accelerating optical dimensional microscopy}, volume = {266}, booktitle = {EPJ Web Conf.}, doi = {10.1051/epjconf/202226610010}, pages = {10010}, year = {2022}, language = {en} } @article{RaharinirinaFackeldeyWeber2022, author = {Raharinirina, N. Alexia and Fackeldey, Konstantin and Weber, Marcus}, title = {Qualitative Euclidean embedding of Disjoint Sets of Points}, year = {2022}, abstract = {We consider two disjoint sets of points with a distance metric, or a proximity function, associated with each set. If each set can be separately embedded into separate Euclidean spaces, then we provide sufficient conditions for the two sets to be jointly embedded in one Euclidean space. In this joint Euclidean embedding, the distances between the points are generated by a specific relation-preserving function. Consequently, the mutual distances between two points of the same set are specific qualitative transformations of their mutual distances in their original space; the pairwise distances between the points of different sets can be constructed from an arbitrary proximity function (might require scaling).}, language = {en} } @article{BoegeFritzeGoergenetal.2023, author = {Boege, Tobias and Fritze, Ren{\´e} and G{\"o}rgen, Christiane and Hanselmann, Jeroen and Iglezakis, Dorothea and Kastner, Lars and Koprucki, Thomas and Krause, Tabea and Lehrenfeld, Christoph and Polla, Silvia and Reidelbach, Marco and Riedel, Christian and Saak, Jens and Schembera, Bj{\"o}rn and Tabelow, Karsten and Weber, Marcus}, title = {Research-Data Management Planning in the German Mathematical Community}, volume = {130}, journal = {Eur. Math. Soc. Mag.}, doi = {10.4171/mag/152}, pages = {40 -- 47}, year = {2023}, abstract = {In this paper we discuss the notion of research data for the field of mathematics and report on the status quo of research-data management and planning. A number of decentralized approaches are presented and compared to needs and challenges faced in three use cases from different mathematical subdisciplines. We highlight the importance of tailoring research-data management plans to mathematicians' research processes and discuss their usage all along the data life cycle.}, language = {en} } @article{ReidelbachBaiZoellneretal.2022, author = {Reidelbach, Marco and Bai, Mei and Z{\"o}llner, Martin Sebastian and Schneeberger, Michaela and Kubicek, Katharina and Kirchberg, Henning and Bressler, Christian and Thorwart, Michael and Herrmann, Carmen}, title = {Solvent dynamics of aqueous halides before and after photoionization}, journal = {Journal of Physical Chemistry}, year = {2022}, language = {en} }