Prof. Michael Hintermüller
Publications since 2016
Articles in Refereed Journals

M. Bongarti, M. Hintermüller, Optimal boundary control of the isothermal semilinear Euler equation for gas dynamics on a network, Applied Mathematics and Optimization. An International Journal with Applications to Stochastics, 89 (2024), pp. 36/136/48, DOI 10.1007/s00245023100880 .
Abstract
The analysis and boundary optimal control of the nonlinear transport of gas on a network of pipelines is considered. The evolution of the gas distribution on a given pipe is modeled by an isothermal semilinear compressible Euler system in one space dimension. On the network, solutions satisfying (at nodes) the Kirchhoff flux continuity conditions are shown to exist in a neighborhood of an equilibrium state. The associated nonlinear optimization problem then aims at steering such dynamics to a given target distribution by means of suitable (network) boundary controls while keeping the distribution within given (state) constraints. The existence of local optimal controls is established and a corresponding KarushKuhnTucker (KKT) stationarity system with an almost surely nonsingular Lagrange multiplier is derived. 
M. Hintermüller, S.M. Stengl, A generalized $Gamma$convergence concept for a type of equilibrium problems, Journal of Nonlinear Science, 34 (2024), pp. 83/183/28, DOI 10.1007/s0033202410059x .
Abstract
A novel generalization of Γconvergence applicable to a class of equilibrium problems is studied. After the introduction of the latter, a variety of its applications is discussed. The existence of equilibria with emphasis on Nash equilibrium problems is investigated. Subsequently, our Γconvergence notion for equilibrium problems, generalizing the existing one from optimization, is introduced and discussed. The work ends with its application to a class of penalized generalized Nash equilibrium problems and quasivariational inequalities. 
M. Gugat, J. Habermann, M. Hintermüller, O. Huber, Constrained exact boundary controllability of a semilinear model for pipeline gas flow, European Journal of Applied Mathematics, 34 (2023), pp. 532553, DOI 10.1017/S0956792522000389 .
Abstract
While the quasilinear isothermal Euler equations are an excellent model for gas pipeline flow, the operation of the pipeline flow with high pressure and small Mach numbers allows us to obtain approximate solutions by a simpler semilinear model. We provide a derivation of the semilinear model that shows that the semilinear model is valid for sufficiently low Mach numbers and sufficiently high pressures. We prove an existence result for continuous solutions of the semilinear model that takes into account lower and upper bounds for the pressure and an upper bound for the magnitude of the Mach number of the gas flow. These state constraints are important both in the operation of gas pipelines and to guarantee that the solution remains in the set where the model is physically valid. We show the constrained exact boundary controllability of the system with the same pressure and Mach number constraints. 
M. Hintermüller, T. Keil, Strong stationarity conditions for the optimal control of a CahnHilliardNavierStokes system, Applied Mathematics and Optimization. An International Journal with Applications to Stochastics, 89 (2024), pp. 12/112/28 (published online on 05.12.2023), DOI 10.1007/s00245023100639 .
Abstract
This paper is concerned with the distributed optimal control of a timediscrete CahnHilliardNavierStokes system with variable densities. It focuses on the doubleobstacle potential which yields an optimal control problem for a variational inequality of fourth order and the NavierStokes equation. The existence of solutions to the primal system and of optimal controls is established. The Lipschitz continuity of the constraint mapping is derived and used to characterize the directional derivative of the constraint mapping via a system of variational inequalities and partial differential equations. Finally, strong stationarity conditions are presented following an approach from Mignot and Puel. 
M. Hintermüller, A. Kröner, Differentiability properties for boundary control of fluidstructure interactions of linear elasticity with NavierStokes equations with mixedboundary conditions in a channel, Applied Mathematics and Optimization. An International Journal with Applications to Stochastics, 87 (2023), pp. 15/115/38, DOI 10.1007/s00245022099380 .
Abstract
In this paper we consider a fluidstructure interaction problem given by the steady Navier Stokes equations coupled with linear elasticity taken from [Lasiecka, Szulc, and Zochoswki, Nonl. Anal.: Real World Appl., 44, 2018]. An elastic body surrounded by a liquid in a rectangular domain is deformed by the flow which can be controlled by the Dirichlet boundary condition at the inlet. On the walls along the channel homogeneous Dirichlet boundary conditions and on the outflow boundary donothing conditions are prescribed. We recall existence results for the nonlinear system from that reference and analyze the control to state mapping generaziling the results of [Wollner and Wick, J. Math. Fluid Mech., 21, 2019] to the setting of the nonlinear NavierStokes equation for the fluid and the situation of mixed boundary conditions in a domain with corners. 
D.G. Gahururu, M. Hintermüller, Th.M. Surowiec, Riskneutral PDEconstrained generalized Nash equilibrium problems, Mathematical Programming. A Publication of the Mathematical Programming Society, 198 (2023), pp. 12871337 (published online on 29.03.2022), DOI 10.1007/s1010702201800z .

G. Dong, M. Hintermüller, K. Papafitsoros, Optimization with learninginformed differential equation constraints and its applications, ESAIM. Control, Optimisation and Calculus of Variations, 28 (2022), pp. 3/13/44, DOI 10.1051/cocv/2021100 .
Abstract
Inspired by applications in optimal control of semilinear elliptic partial differential equations and physicsintegrated imaging, differential equation constrained optimization problems with constituents that are only accessible through datadriven techniques are studied. A particular focus is on the analysis and on numerical methods for problems with machinelearned components. For a rather general context, an error analysis is provided, and particular properties resulting from artificial neural network based approximations are addressed. Moreover, for each of the two inspiring applications analytical details are presented and numerical results are provided. 
C. Geiersbach, M. Hintermüller, Optimality conditions and MoreauYosida regularization for almost sure state constraints, ESAIM. Control, Optimisation and Calculus of Variations, 28 (2022), pp. 80/180/36, DOI 10.1051/cocv/2022070 .
Abstract
We analyze a potentially riskaverse convex stochastic optimization problem, where the control is deterministic and the state is a Banachvalued essentially bounded random variable. We obtain strong forms of necessary and sufficient optimality conditions for problems subject to equality and conical constraints. We propose a MoreauYosida regularization for the conical constraint and show consistency of the optimality conditions for the regularized problem as the regularization parameter is taken to infinity. 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, On the differentiability of the minimal and maximal solution maps of elliptic quasivariational inequalities, Journal of Mathematical Analysis and Applications, 507 (2022), pp. 125732/1125732/19, DOI 10.1016/j.jmaa.2021.125732 .
Abstract
In this short note, we prove that the minimal and maximal solution maps associated to elliptic quasivariational inequalities of obstacle type are directionally differentiable with respect to the forcing term and for directions that are signed. On the way, we show that the minimal and maximal solutions can be seen as monotone limits of solutions of certain variational inequalities and that the aforementioned directional derivatives can also be characterised as the monotone limits of sequences of directional derivatives associated to variational inequalities. 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, Optimal control and directional differentiability for elliptic quasivariational inequalities, SetValued and Variational Analysis. Theory and Applications. Springer, Dordrecht. English., 30 (2022), pp. 873922, DOI 10.1007/s1122802100624x .
Abstract
We focus on elliptic quasivariational inequalities (QVIs) of obstacle type and prove a number of results on the existence of solutions, directional differentiability and optimal control of such QVIs. We give three existence theorems based on an order approach, an iteration scheme and a sequential regularisation through partial differential equations. We show that the solution map taking the source term into the set of solutions of the QVI is directionally differentiable for general unsigned data, thereby extending the results of our previous work which provided a first differentiability result for QVIs in infinite dimensions. Optimal control problems with QVI constraints are also considered and we derive various forms of stationarity conditions for control problems, thus supplying among the first such results in this area. 
M. Hintermüller, K. Papafitsoros, C.N. Rautenberg, H. Sun, Dualization and automatic distributed parameter selection of total generalized variation via bilevel optimization, Numerical Functional Analysis and Optimization. An International Journal, 43 (2022), pp. 887932, DOI 10.1080/01630563.2022.2069812 .
Abstract
Total Generalized Variation (TGV) regularization in image reconstruction relies on an infimal convolution type combination of generalized first and secondorder derivatives. This helps to avoid the staircasing effect of Total Variation (TV) regularization, while still preserving sharp contrasts in images. The associated regularization effect crucially hinges on two parameters whose proper adjustment represents a challenging task. In this work, a bilevel optimization framework with a suitable statisticsbased upper level objective is proposed in order to automatically select these parameters. The framework allows for spatially varying parameters, thus enabling better recovery in highdetail image areas. A rigorous dualization framework is established, and for the numerical solution, two Newton type methods for the solution of the lower level problem, i.e. the image reconstruction problem, and two bilevel TGV algorithms are introduced, respectively. Denoising tests confirm that automatically selected distributed regularization parameters lead in general to improved reconstructions when compared to results for scalar parameters. 
G. Dong, M. Hintermüller, Y. Zhang, A class of secondorder geometric quasilinear hyperbolic PDEs and their application in imaging, SIAM Journal on Imaging Sciences, 14 (2021), pp. 645688, DOI 10.1137/20M1366277 .
Abstract
In this paper, we study damped secondorder dynamics, which are quasilinear hyperbolic partial differential equations (PDEs). This is inspired by the recent development of secondorder damping systems for accelerating energy decay of gradient flows. We concentrate on two equations: one is a damped secondorder total variation flow, which is primarily motivated by the application of image denoising; the other is a damped secondorder mean curvature flow for level sets of scalar functions, which is related to a nonconvex variational model capable of correcting displacement errors in image data (e.g. dejittering). For the former equation, we prove the existence and uniqueness of the solution. For the latter, we draw a connection between the equation and some secondorder geometric PDEs evolving the hypersurfaces which are described by level sets of scalar functions, and show the existence and uniqueness of the solution for a regularized version of the equation. The latter is used in our algorithmic development. A general algorithm for numerical discretization of the two nonlinear PDEs is proposed and analyzed. Its efficiency is demonstrated by various numerical examples, where simulations on the behavior of solutions of the new equations and comparisons with firstorder flows are also documented. 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, On the differentiability of the minimal and maximal solution maps of elliptic quasivariational inequalities, Journal of Mathematical Analysis and Applications, published online on 27.10.2021, DOI 10.1016/j.jmaa.2021.125732 .
Abstract
In this short note, we prove that the minimal and maximal solution maps associated to elliptic quasivariational inequalities of obstacle type are directionally differentiable with respect to the forcing term and for directions that are signed. On the way, we show that the minimal and maximal solutions can be seen as monotone limits of solutions of certain variational inequalities and that the aforementioned directional derivatives can also be characterised as the monotone limits of sequences of directional derivatives associated to variational inequalities. 
M. Hintermüller, S.M. Stengl, Th.M. Surowiec, Uncertainty quantification in image segmentation using the AmbrosioTortorelli approximation of the MumfordShah energy, Journal of Mathematical Imaging and Vision, 63 (2021), pp. 10951117, DOI 10.1007/s10851021010342 .
Abstract
The quantification of uncertainties in image segmentation based on the MumfordShah model is studied. The aim is to address the error propagation of noise and other error types in the original image to the restoration result and especially the reconstructed edges (sharp image contrasts). Analytically, we rely on the AmbrosioTortorelli approximation and discuss the existence of measurable selections of its solutions as well as samplingbased methods and the limitations of other popular methods. Numerical examples illustrate the theoretical findings. 
M. Hintermüller, S. Rösel, Duality results and regularization schemes for PrandtlReuss perfect plasticity, ESAIM. Control, Optimisation and Calculus of Variations, 27 (2021), pp. S1/1S1/32, DOI 10.1051/cocv/2018004 .
Abstract
We consider the timediscretized problem of the quasistatic evolution problem in perfect plasticity posed in a nonreflexive Banach space and we derive an equivalent version in a reflexive Banach space. A primaldual stabilization scheme is shown to be consistent with the initial problem. As a consequence, not only stresses, but also displacement and strains are shown to converge to a solution of the original problem in a suitable topology. This scheme gives rise to a welldefined Fenchel dual problem which is a modification of the usual stress problem in perfect plasticity. The dual problem has a simpler structure and turns out to be wellsuited for numerical purposes. For the corresponding subproblems an efficient algorithmic approach in the infinitedimensional setting based on the semismooth Newton method is proposed. 
L. Banz, M. Hintermüller, A. Schröder, A posteriori error control for distributed elliptic optimal control problems with control constraints discretized by $hp$finite elements, Computers & Mathematics with Applications. An International Journal, 80 (2020), pp. 24332450, DOI 10.1016/j.camwa.2020.08.007 .

C. Rautenberg, M. Hintermüller, A. Alphonse, Stability of the solution set of quasivariational inequalities and optimal control, SIAM Journal on Control and Optimization, 58 (2020), pp. 35083532, DOI 10.1137/19M1250327 .

A. Alphonse, M. Hintermüller, C.N. Rautenberg, Existence, iteration procedures and directional differentiability for parabolic QVIs, Calculus of Variations and Partial Differential Equations, 59 (2020), pp. 95/195/53, DOI 10.1007/s00526020017326 .
Abstract
We study parabolic quasivariational inequalities (QVIs) of obstacle type. Under appropriate assumptions on the obstacle mapping, we prove the existence of solutions of such QVIs by two methods: one by time discretisation through elliptic QVIs and the second by iteration through parabolic variational inequalities (VIs). Using these results, we show the directional differentiability (in a certain sense) of the solution map which takes the source term of a parabolic QVI into the set of solutions, and we relate this result to the contingent derivative of the aforementioned map. We finish with an example where the obstacle mapping is given by the inverse of a parabolic differential operator. 
M. Hintermüller, K. Papafitsoros, C.N. Rautenberg, Variable step mollifiers and applications, Integral Equations and Operator Theory, 92 (2020), pp. 53/153/34, DOI 10.1007/s00020020026082 .
Abstract
We consider a mollifying operator with variable step that, in contrast to the standard mollification, is able to preserve the boundary values of functions. We prove boundedness of the operator in all basic Lebesgue, Sobolev and BV spaces as well as corresponding approximation results. The results are then applied to extend recently developed theory concerning the density of convex intersections. 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, Directional differentiability for elliptic quasivariational inequalities of obstacle type, Calculus of Variations and Partial Differential Equations, 58 (2019), pp. 39/139/47, DOI 10.1007/s0052601814730 .
Abstract
The directional differentiability of the solution map of obstacle type quasivariational inequal ities (QVIs) with respect to perturbations on the forcing term is studied. The classical result of Mignot is then extended to the quasivariational case under assumptions that allow multiple solu tions of the QVI. The proof involves selection procedures for the solution set and represents the directional derivative as the limit of a monotonic sequence of directional derivatives associated to specific variational inequalities. Additionally, estimates on the coincidence set and several sim plifications under higher regularity are studied. The theory is illustrated by a detailed study of an application to thermoforming comprising of modelling, analysis and some numerical experiments. 
L. Adam, M. Hintermüller, D. Peschka, Th.M. Surowiec, Optimization of a multiphysics problem in semiconductor laser design, SIAM Journal on Applied Mathematics, 79 (2019), pp. 257283, DOI 10.1137/18M1179183 .
Abstract
A multimaterial topology optimization framework is suggested for the simultaneous optimization of mechanical and optical properties to be used in the development of optoelectronic devices. Based on the physical aspects of the underlying device, a nonlinear multiphysics model for the elastic and optical properties is proposed. Rigorous proofs are provided for the sensitivity of the fundamental mode of the device with respect to the changes in the underlying topology. After proving existence and optimality results, numerical experiments leading to an optimal material distribution for maximizing the strain in a GeonSi microbridge are given. The highly favorable electronic properties of this design are demonstrated by steadystate simulations of the corresponding van Roosbroeck (driftdiffusion) system. 
G. Dong, M. Hintermüller, K. Papafitsoros, Quantitative magnetic resonance imaging: From fingerprinting to integrated physicsbased models, SIAM Journal on Imaging Sciences, 2 (2019), pp. 927971, DOI 10.1137/18M1222211 .
Abstract
Quantitative magnetic resonance imaging (qMRI) is concerned with estimating (in physical units) values of magnetic and tissue parameters, e.g., relaxation times $T_1$, $T_2$, or proton density $rho$. Recently, in [Ma et al., Nature, 495 (2013), pp. 187193], magnetic resonance fingerprinting (MRF) was introduced as a technique being capable of simultaneously recovering such quantitative parameters by using a twostep procedure: (i) given a probe, a series of magnetization maps are computed and then (ii) matched to (quantitative) parameters with the help of a precomputed dictionary which is related to the Bloch manifold. In this paper, we first put MRF and its variants into perspective with optimization and inverse problems to gain mathematical insights concerning identifiability of parameters under noise and interpretation in terms of optimizers. Motivated by the fact that the Bloch manifold is nonconvex and that the accuracy of the MRFtype algorithms is limited by the ?discretization size? of the dictionary, a novel physicsbased method for qMRI is proposed. In contrast to the conventional twostep method, our model is dictionaryfree and is rather governed by a single nonlinear equation, which is studied analytically. This nonlinear equation is efficiently solved via robustified Newtontype methods. The effectiveness of the new method for noisy and undersampled data is shown both analytically and via extensive numerical examples, for which improvement over MRF and its variants is also documented. 
S. Hajian, M. Hintermüller, C. Schillings, N. Strogies, A Bayesian approach to parameter identification in gas networks, Control and Cybernetics, 48 (2019), pp. 377402.
Abstract
The inverse problem of identifying the friction coefficient in an isothermal semilinear Euler system is considered. Adopting a Bayesian approach, the goal is to identify the distribution of the quantity of interest based on a finite number of noisy measurements of the pressure at the boundaries of the domain. First wellposedness of the underlying nonlinear PDE system is shown using semigroup theory, and then Lipschitz continuity of the solution operator with respect to the friction coefficient is established. Based on the Lipschitz property, wellposedness of the resulting Bayesian inverse problem for the identification of the friction coefficient is inferred. Numerical tests for scalar and distributed parameters are performed to validate the theoretical results. 
M. Hintermüller, N. Strogies, Identification of the friction function in a semilinear system for gas transport through a network, Optimization Methods & Software, 35 (2020), pp. 576617 (published online on 10.12.2019), DOI 10.1080/10556788.2019.1692206 .

L. Adam, M. Hintermüller, Th.M. Surowiec, A PDEconstrained optimization approach for topology optimization of strained photonic devices, Annali di Matematica Pura ed Applicata. Serie Quarta. Fondazione Annali di Matematica Pura ed Applicata, c/o Dipartimento di Matematica ``U. Dini'', Firenze; SpringerVerlag, Heidelberg. English, French, German, Italian, English abstracts., 19 (2018), pp. 521557, DOI 10.1007/s1108101893945 .
Abstract
Recent studies have demonstrated the potential of using tensilestrained, doped Germanium as a means of developing an integrated light source for (amongst other things) future microprocessors. In this work, a multimaterial phasefield approach to determine the optimal material configuration within a socalled GermaniumonSilicon microbridge is considered. Here, an “optimal" configuration is one in which the strain in a predetermined minimal optical cavity within the Germanium is maximized according to an appropriately chosen objective functional. Due to manufacturing requirements, the emphasis here is on the crosssection of the device; i.e. a socalled aperture design. Here, the optimization is modeled as a nonlinear optimization problem with partial differential equation (PDE) and manufacturing constraints. The resulting problem is analyzed and solved numerically. The theory portion includes a proof of existence of an optimal topology, differential sensitivity analysis of the displacement with respect to the topology, and the derivation of first and secondorder optimality conditions. For the numerical experiments, an array of first and secondorder solution algorithms in functionspace are adapted to the current setting, tested, and compared. The numerical examples yield designs for which a significant increase in strain (as compared to an intuitive empirical design) is observed. 
L. Adam, M. Hintermüller, Th.M. Surowiec, A semismooth Newton method with analytical pathfollowing for the $H^1$projection onto the Gibbs simplex, IMA Journal of Numerical Analysis, 39 (2019), pp. 12761295 (published online on 07.06.2018), DOI 10.1093/imanum/dry034 .
Abstract
An efficient, functionspacebased secondorder method for the $H^1$projection onto the Gibbssimplex is presented. The method makes use of the theory of semismooth Newton methods in function spaces as well as MoreauYosida regularization and techniques from parametric optimization. A pathfollowing technique is considered for the regularization parameter updates. A rigorous first and secondorder sensitivity analysis of the value function for the regularized problem is provided to justify the update scheme. The viability of the algorithm is then demonstrated for two applications found in the literature: binary image inpainting and labeled data classification. In both cases, the algorithm exhibits meshindependent behavior. 
M. Hintermüller, M. Hinze, Ch. Kahle, T. Keil, A goaloriented dualweighted adaptive finite element approach for the optimal control of a nonsmooth CahnHilliardNavierStokes system, Optimization and Engineering. International Multidisciplinary Journal to Promote Optimization Theory & Applications in Engineering Sciences, 19 (2018), pp. 629662, DOI 10.1007/s1108101893936 .
Abstract
This paper is concerned with the development and implementation of an adaptive solution algorithm for the optimal control of a timediscrete CahnHilliardNavierStokes system with variable densities. The free energy density associated to the CahnHilliard system incorporates the doubleobstacle potential which yields an optimal control problem for a family of coupled systems in each time instant of a variational inequality of fourth order and the NavierStokes equation. A dualweighed residual approach for goaloriented adaptive finite elements is presented which is based on the concept of Cstationarity. The overall error representation depends on primal residual weighted by approximate dual quantities and vice versa as well as various complementary mismatch errors. Details on the numerical realization of the adaptive concept and a report on numerical tests are given. 
M. Hintermüller, M. Holler, K. Papafitsoros, A function space framework for structural total variation regularization with applications in inverse problems, Inverse Problems. An International Journal on the Theory and Practice of Inverse Problems, Inverse Methods and Computerized Inversion of Data, 34 (2018), pp. 064002/1064002/39, DOI 10.1088/13616420/aab586 .
Abstract
In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semicontinuous envelope (relaxation) of a suitable total variation type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted total variation for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddlepoint problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson loglikelihood data discrepancy terms. Finally, we provide proofofconcept numerical examples where we solve the saddlepoint problem for weighted TV denoising as well as for MR guided PET image reconstruction. 
M. Hintermüller, C.N. Rautenberg, N. Strogies, Dissipative and nondissipative evolutionary quasivariational inequalities with gradient constraints, SetValued and Variational Analysis. Theory and Applications. Springer, Dordrecht. English., 27 (2019), pp. 433468 (published online on 14.07.2018), DOI 10.1007/s1122801804890 .
Abstract
Evolutionary quasivariational inequality (QVI) problems of dissipative and nondissipative nature with pointwise constraints on the gradient are studied. A semidiscretization in time is employed for the study of the problems and the derivation of a numerical solution scheme, respectively. Convergence of the discretization procedure is proven and properties of the original infinite dimensional problem, such as existence, extra regularity and nondecrease in time, are derived. The proposed numerical solver reduces to a finite number of gradientconstrained convex optimization problems which can be solved rather efficiently. The paper ends with a report on numerical tests obtained by a variable splitting algorithm involving different nonlinearities and types of constraints. 
H. Antil, M. Hintermüller, R.H. Nochetto, Th.M. Surowiec, D. Wegner, Finite horizon model predictive control of electrowetting on dielectric with pinning, Interfaces and Free Boundaries. Mathematical Modelling, Analysis and Computation, 19 (2017), pp. 130, DOI 10.4171/IFB/375 .

S. Hajian, M. Hintermüller, S. Ulbrich, Total variation diminishing schemes in optimal control of scalar conservation laws, IMA Journal of Numerical Analysis, 39 (2019), pp. 105140 (published online on 14.12.2017), DOI 10.1093/imanum/drx073 .
Abstract
In this paper, optimal control problems subject to a nonlinear scalar conservation law are studied. Such optimal control problems are challenging both at the continuous and at the discrete level since the controltostate operator poses difficulties as it is, e.g., not differentiable. Therefore discretization of the underlying optimal control problem should be designed with care. Here the discretizethenoptimize approach is employed where first the full discretization of the objective function as well as the underlying PDE is considered. Then, the derivative of the reduced objective is obtained by using an adjoint calculus. In this paper total variation diminishing RungeKutta (TVDRK) methods for the time discretization of such problems are studied. TVDRK methods, also called strong stability preserving (SSP), are originally designed to preserve total variation of the discrete solution. It is proven in this paper that providing an SSP state scheme, is enough to ensure stability of the discrete adjoint. However requiring SSP for both discrete state and adjoint is too strong. Also approximation properties that the discrete adjoint inherits from the discretization of the state equation are studied. Moreover order conditions are derived. In addition, optimal choices with respect to CFL constant are discussed and numerical experiments are presented. 
M. Hintermüller, T. Keil, D. Wegner, Optimal control of a semidiscrete CahnHilliardNavierStokes system with nonmatched fluid densities, SIAM Journal on Control and Optimization, 55 (2017), pp. 19541989.

M. Hintermüller, K. Papafitsoros, C.N. Rautenberg, Analytical aspects of spatially adapted total variation regularisation, Journal of Mathematical Analysis and Applications, 454 (2017), pp. 891935, DOI 10.1016/j.jmaa.2017.05.025 .
Abstract
In this paper we study the structure of solutions of the one dimensional weighted total variation regularisation problem, motivated by its application in signal recovery tasks. We study in depth the relationship between the weight function and the creation of new discontinuities in the solution. A partial semigroup property relating the weight function and the solution is shown and analytic solutions for simply data functions are computed. We prove that the weighted total variation minimisation problem is wellposed even in the case of vanishing weight function, despite the lack of coercivity. This is based on the fact that the total variation of the solution is bounded by the total variation of the data, a result that it also shown here. Finally the relationship to the corresponding weighted fidelity problem is explored, showing that the two problems can produce completely different solutions even for very simple data functions. 
M. Hintermüller, C.N. Rautenberg, M. Mohammadi, M. Kanitsar, Optimal sensor placement: A robust approach, SIAM Journal on Control and Optimization, 55 (2017), pp. 36093639.
Abstract
We address the problem of optimally placing sensor networks for convectiondiffusion processes where the convective part is perturbed. The problem is formulated as an optimal control problem where the integral Riccati equation is a constraint and the design variables are sensor locations. The objective functional involves a term associated to the trace of the solution to the Riccati equation and a term given by a constrained optimization problem for the directional derivative of the previous quantity over a set of admissible perturbations. The paper addresses the existence of the derivative with respect to the convective part of the solution to the Riccati equation, the wellposedness of the optimization problem and finalizes with a range of numerical tests. 
M. Hintermüller, C.N. Rautenberg, S. Rösel, Density of convex intersections and applications, Proceedings of the Royal Society of Edinburgh. Section A. Mathematics, 473 (2017), pp. 20160919/120160919/28, DOI 10.1098/rspa.2016.0919 .
Abstract
In this paper we address density properties of intersections of convex sets in several function spaces. Using the concept of Gammaconvergence, it is shown in a general framework, how these density issues naturally arise from the regularization, discretization or dualization of constrained optimization problems and from perturbed variational inequalities. A variety of density results (and counterexamples) for pointwise constraints in Sobolev spaces are presented and the corresponding regularity requirements on the upper bound are identified. The results are further discussed in the context of finite element discretizations of sets associated to convex constraints. Finally, two applications are provided, which include elastoplasticity and image restoration problems. 
M. Hintermüller, C.N. Rautenberg, T. Wu, A. Langer, Optimal selection of the regularization function in a generalized total variation model. Part II: Algorithm, its analysis and numerical tests, Journal of Mathematical Imaging and Vision, 59 (2017), pp. 515533.
Abstract
Based on the generalized total variation model and its analysis pursued in part I (WIAS Preprint no. 2235), in this paper a continuous, i.e., infinite dimensional, projected gradient algorithm and its convergence analysis are presented. The method computes a stationary point of a regularized bilevel optimization problem for simultaneously recovering the image as well as determining a spatially distributed regularization weight. Further, its numerical realization is discussed and results obtained for image denoising and deblurring as well as Fourier and wavelet inpainting are reported on. 
M. Hintermüller, C.N. Rautenberg, On the uniqueness and numerical approximation of solutions to certain parabolic quasivariational inequalities, Portugaliae Mathematica. A Journal of the Portuguese Mathematical Society, 74 (2017), pp. 135.
Abstract
A class of abstract nonlinear evolution quasivariational inequality (QVI) problems in function space is considered. The abstract framework developed in this paper includes constraint sets of obstacle and gradient type. The paper address the existence, uniqueness and approximation of solutions when the constraint set mapping is of a special form. Uniqueness is addressed through contractive behavior of a nonlinear mapping whose fixed points are solutions to the QVI. An axiomatic semidiscrete approximation scheme is developed, which is proven to be convergent and which is numerically implemented. The paper ends by a report on numerical tests for several nonlinear constraints of gradienttype. 
M. Hintermüller, C.N. Rautenberg, Optimal selection of the regularization function in a weighted total variation model. Part I: Modeling and theory, Journal of Mathematical Imaging and Vision, 59 (2017), pp. 498514.
Abstract
Based on the generalized total variation model and its analysis pursued in part I (WIAS Preprint no. 2235), in this paper a continuous, i.e., infinite dimensional, projected gradient algorithm and its convergence analysis are presented. The method computes a stationary point of a regularized bilevel optimization problem for simultaneously recovering the image as well as determining a spatially distributed regularization weight. Further, its numerical realization is discussed and results obtained for image denoising and deblurring as well as Fourier and wavelet inpainting are reported on. 
K. Sturm, M. Hintermüller, D. Hömberg, Distortion compensation as a shape optimisation problem for a sharp interface model, Computational Optimization and Applications. An International Journal, 64 (2016), pp. 557588.
Abstract
We study a mechanical equilibrium problem for a material consisting of two components with different densities, which allows to change the outer shape by changing the interface between the subdomains. We formulate the shape design problem of compensating unwanted workpiece changes by controlling the interface, employ regularity results for transmission problems for a rigorous derivation of optimality conditions based on the speed method, and conclude with some numerical results based on a spline approximation of the interface. 
M. Hintermüller, S. Rösel, A dualitybased pathfollowing semismooth Newton method for elastoplastic contact problems, Journal of Computational and Applied Mathematics, 292 (2016), pp. 150173.

M. Hintermüller, Th. Surowiec, A bundlefree implicit programming approach for a class of elliptic MPECs in function space, Mathematical Programming Series A, 160 (2016), pp. 271305.
Contributions to Collected Editions

R. Danabalan, M. Hintermüller, Th. Koprucki, K. Tabelow, MaRDI: Building research data infrastructures for mathematics and the mathematical sciences, in: 1st Conference on Research Data Infrastructure (CoRDI)  Connecting Communities, Y. SureVetter, C. Goble, eds., 1 of Proceedings of the Conference on Research Data Infrastructure, TIB Open Publishing, Hannover, 2023, pp. 69/169/4, DOI 10.52825/cordi.v1i.397 .
Abstract
MaRDI is building a research data infrastructure for mathematics and beyond based on semantic technologies (metadata, ontologies, knowledge graphs) and data repositories. Focusing on the algorithms, models and workflows, the MaRDI infrastructure will connect with other disciplines and NFDI consortia on data processing methods, solving real world problems and support mathematicians on research datamanagement 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, Stability and sensitivity analysis for quasivariational inequalities, in: NonSmooth and ComplementarityBased Distributed Parameter Systems: Simulation and Hierarchical Optimization, M. Hintermüller, R. Herzog, Ch. Kanzow, M. Ulbrich, S. Ulbrich, eds., 172 of International Series of Numerical Mathematics, Birkhäuser, Springer Nature Switzerland AG, Cham, 2022, pp. 183210.

D. Gahururu, M. Hintermüller, S.M. Stengl, Th.M. Surowiec, Generalized Nash equilibrium problems with partial differential operators: Theory, algorithms and risk aversion, in: NonSmooth and ComplementarityBased Distributed Parameter Systems: Simulation and Hierarchical Optimization, M. Hintermüller, R. Herzog, Ch. Kanzow, M. Ulbrich, S. Ulbrich, eds., 172 of International Series of Numerical Mathematics, Birkhäuser, Springer Nature Switzerland AG, Cham, 2022, pp. 145181.

C. Grässle, M. Hintermüller, M. Hinze, T. Keil, Simulation and control of a nonsmooth CahnHilliard NavierStokes system with variable fluid densities, in: NonSmooth and ComplementarityBased Distributed Parameter Systems: Simulation and Hierarchical Optimization, M. Hintermüller, R. Herzog, Ch. Kanzow, M. Ulbrich, S. Ulbrich, eds., 172 of International Series of Numerical Mathematics, Birkhäuser, Springer Nature Switzerland AG, Cham, 2022, pp. 211240.

A. Alphonse, M. Hintermüller, C.N. Rautenberg, Recent trends and views on elliptic quasivariational inequalities, 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. 131.

M. Hintermüller, N. Strogies, On the consistency of RungeKutta methods up to order three applied to the optimal control of scalar conservation laws, in: Numerical Analysis and Optimization, M. AlBaali, L. Grandinetti, A. Purnama, eds., 235 of Springer Proceedings in Mathematics & Statistics, Springer Nature Switzerland AG, Cham, 2019, pp. 119154.
Abstract
Higherorder RungeKutta (RK) time discretization methods for the optimal control of scalar conservation laws are analyzed and numerically tested. The hyperbolic nature of the state system introduces specific requirements on discretization schemes such that the discrete adjoint states associated with the control problem converge as well. Moreover, conditions on the RKcoefficients are derived that coincide with those characterizing strong stability preserving RungeKutta methods. As a consequence, the optimal order for the adjoint state is limited, e.g., to two even in the case where the conservation law is discretized by a thirdorder method. Finally, numerical tests for controlling Burgers equation validate the theoretical results. 
M. Hintermüller, T. Keil, Some recent developments in optimal control of multiphase flows, in: Shape Optimization, Homogenization and Optimal Control. DFGAIMS Workshop held at the AIMS Center Senegal, March 1316, 2017, V. Schulz, D. Seck, eds., 169 of International Series of Numerical Mathematics, Birkhäuser, Springer Nature Switzerland AG, Cham, 2018, pp. 113142, DOI 10.1007/9783319904696_7 .

M. Hintermüller, A. Langer, C.N. Rautenberg, T. Wu, Adaptive regularization for image reconstruction from subsampled data, in: Imaging, Vision and Learning Based on Optimization and PDEs IVLOPDE, Bergen, Norway, August 29  September 2, 2016, X.Ch. Tai, E. Bae, M. Lysaker, eds., Mathematics and Visualization, Springer International Publishing, Berlin, 2018, pp. 326, DOI 10.1007/9783319912745 .
Abstract
Choices of regularization parameters are central to variational methods for image restoration. In this paper, a spatially adaptive (or distributed) regularization scheme is developed based on localized residuals, which properly balances the regularization weight between regions containing image details and homogeneous regions. Surrogate iterative methods are employed to handle given subsampled data in transformed domains, such as Fourier or wavelet data. In this respect, this work extends the spatially variant regularization technique previously established in [15], which depends on the fact that the given data are degraded images only. Numerical experiments for the reconstruction from partial Fourier data and for wavelet inpainting prove the efficiency of the newly proposed approach.
Preprints, Reports, Technical Reports

G. Dong, M. Flaschel, M. Hintermüller, K. Papafitsoros, C. Sirotenko, K. Tabelow, Datadriven methods for quantitative imaging, Preprint no. 3105, WIAS, Berlin, 2024, DOI 10.20347/WIAS.PREPRINT.3105 .
Abstract, PDF (7590 kByte)
In the field of quantitative imaging, the image information at a pixel or voxel in an underlying domain entails crucial information about the imaged matter. This is particularly important in medical imaging applications, such as quantitative Magnetic Resonance Imaging (qMRI), where quantitative maps of biophysical parameters can characterize the imaged tissue and thus lead to more accurate diagnoses. Such quantitative values can also be useful in subsequent, automatized classification tasks in order to discriminate normal from abnormal tissue, for instance. The accurate reconstruction of these quantitative maps is typically achieved by solving two coupled inverse problems which involve a (forward) measurement operator, typically illposed, and a physical process that links the wanted quantitative parameters to the reconstructed qualitative image, given some underlying measurement data. In this review, by considering qMRI as a prototypical application, we provide a mathematicallyoriented overview on how datadriven approaches can be employed in these inverse problems eventually improving the reconstruction of the associated quantitative maps. 
A. Alphonse, M. Hintermüller, C.N. Rautenberg, G. Wachsmuth, Minimal and maximal solution maps of elliptic QVIs: Penalisation, Lipschitz stability, differentiability and optimal control, Preprint no. 3093, WIAS, Berlin, 2024.
Abstract, PDF (501 kByte)
Quasivariational inequalities (QVIs) of obstacle type in many cases have multiple solutions that can be ordered. We study a multitude of properties of the operator mapping the source term to the minimal or maximal solution of such QVIs. We prove that the solution maps are locally Lipschitz continuous and directionally differentiable and show existence of optimal controls for problems that incorporate these maps as the controltostate operator. We also consider a Moreau?Yosidatype penalisation for the QVI wherein we show that it is possible to approximate the minimal and maximal solutions by sequences of minimal and maximal solutions (respectively) of certain PDEs, which have a simpler structure and offer a convenient characterisation in particular for computation. For solution mappings of these penalised problems, we prove a number of properties including Lipschitz and differential stability. Making use of the penalised equations, we derive (in the limit) Cstationarity conditions for the control problem, in addition to the Bouligand stationarity we get from the differentiability result. 
M. Hintermüller, D. Korolev, A hybrid physicsinformed neural network based multiscale solver as a partial differential equation constrained optimization problem, Preprint no. 3052, WIAS, Berlin, 2023, DOI 10.20347/WIAS.PREPRINT.3052 .
Abstract, PDF (1045 kByte)
In this work, we study physicsinformed neural networks (PINNs) constrained by partial differential equations (PDEs) and their application in approximating multiscale PDEs. From a continuous perspective, our formulation corresponds to a nonstandard PDEconstrained optimization problem with a PINNtype objective. From a discrete standpoint, the formulation represents a hybrid numerical solver that utilizes both neural networks and finite elements. We propose a function space framework for the problem and develop an algorithm for its numerical solution, combining an adjointbased technique from optimal control with automatic differentiation. The multiscale solver is applied to a heat transfer problem with oscillating coefficients, where the neural network approximates a finescale problem, and a coarsescale problem constrains the learning process. We show that incorporating coarsescale information into the neural network training process through our modelling framework acts as a preconditioner for the lowfrequency component of the finescale PDE, resulting in improved convergence properties and accuracy of the PINN method. The relevance of the hybrid solver to numerical homogenization is discussed. 
G. Dong, M. Hintermüller, K. Papafitsoros, A descent algorithm for the optimal control of ReLU neural network informed PDEs based on approximate directional derivatives, Preprint no. 2964, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2964 .
Abstract, PDF (748 kByte)
We propose and analyze a numerical algorithm for solving a class of optimal control problems for learninginformed semilinear partial differential equations. The latter is a class of PDEs with constituents that are in principle unknown and are approximated by nonsmooth ReLU neural networks. We first show that a direct smoothing of the ReLU network with the aim to make use of classical numerical solvers can have certain disadvantages, namely potentially introducing multiple solutions for the corresponding state equation. This motivates us to devise a numerical algorithm that treats directly the nonsmooth optimal control problem, by employing a descent algorithm inspired by a bundlefree method. Several numerical examples are provided and the efficiency of the algorithm is shown. 
A. Alphonse, C. Geiersbach, M. Hintermüller, Th.M. Surowiec, Riskaverse optimal control of random elliptic VIs, Preprint no. 2962, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2962 .
Abstract, PDF (1541 kByte)
We consider a riskaverse optimal control problem governed by an elliptic variational inequality (VI) subject to random inputs. By deriving KKTtype optimality conditions for a penalised and smoothed problem and studying convergence of the stationary points with respect to the penalisation parameter, we obtain two forms of stationarity conditions. The lack of regularity with respect to the uncertain parameters and complexities induced by the presence of the risk measure give rise to new challenges unique to the stochastic setting. We also propose a pathfollowing stochastic approximation algorithm using variance reduction techniques and demonstrate the algorithm on a modified benchmark problem. 
G. Dong, M. Hintermüller, K. Papafitsoros, K. Völkner, Firstorder conditions for the optimal control of learninginformed nonsmooth PDEs, Preprint no. 2940, WIAS, Berlin, 2022, DOI 10.20347/WIAS.PREPRINT.2940 .
Abstract, PDF (408 kByte)
In this paper we study the optimal control of a class of semilinear elliptic partial differential equations which have nonlinear constituents that are only accessible by data and are approximated by nonsmooth ReLU neural networks. The optimal control problem is studied in detail. In particular, the existence and uniqueness of the state equation are shown, and continuity as well as directional differentiability properties of the corresponding controltostate map are established. Based on approximation capabilities of the pertinent networks, we address fundamental questions regarding approximating properties of the learninginformed controltostate map and the solution of the corresponding optimal control problem. Finally, several stationarity conditions are derived based on different notions of generalized differentiability. 
M. Hintermüller, S.M. Stengl, On the convexity of optimal control problems involving nonlinear PDEs or VIs and applications to Nash games (changed title: Vectorvalued convexity of solution operators with application to optimal control problems), Preprint no. 2759, WIAS, Berlin, 2020, DOI 10.20347/WIAS.PREPRINT.2759 .
Abstract, PDF (338 kByte)
Generalized Nash equilibrium problems in function spaces involving PDEs are considered. One of the central issues arising in this context is the question of existence, which requires the topological characterization of the set of minimizers for each player of the associated Nash game. In this paper, we propose conditions on the operator and the functional that guarantee the reduced formulation to be a convex minimization problem. Subsequently, we generalize results of convex analysis to derive optimality systems also for nonsmooth operators. Our theoretical findings are illustrated by examples.
External Preprints

V. Grimm, M. Hintermüller, O. Huber, L. Schewe, M. Schmidt, G. Zöttl, A PDEconstrained generalized Nash equilibrium approach for modeling gas markets with transport, Preprint no. 458, Dokumentserver des Sonderforschungsbereichs Transregio 154, urlhttps://opus4.kobv.de/opus4trr154/home, 2021.

M. Hintermüller, N. Strogies, On the identification of the friction coefficient in a semilinear system for gas transport through a network, Preprint, DFG SFB Transregio 154 ``Mathematical Modelling, Simulation and Optimization using the Example of Gas Networks'', 2017.
Publications before 2016
 M. Hintermüller, T. Valkonen, T. Wu, Limiting aspects of nonconvex ^phi$ models [pdf], SIAM J. Imaging Sciences 8(4), pp. 25812621, 2015 [bib]
 M. Hintermüller, T. Wu, Bilevel Optimization for Calibrating Point Spread Functions in Blind Deconvolution, Inverse Problems in Imaging 9(4), pp. 11391169, 2015 [bib]
 M. Hintermüller, T. Surowiec, A. Kämmler, Generalized Nash Equilibrium Problems in Banach Spaces: Theory, NikaidoIsodaBased PathFollowing Methods, and Applications [pdf], SIAM J. Optimization 25(3), pp. 18261856, 2015 [bib]
 M. Hintermüller, C. Löbhard, H.M. Tber, An l1penalty scheme for the optimal control of elliptic variational inequalities, in: Numerical Analysis and Optimization Volume 134 of the series Springer Proceedings in Mathematics & Statistics, pp. 151190, 2015 [bib]
 M. Hintermüller, A. Laurain, I. Yousept, Shape Sensitivities for an Inverse Problem in Magnetic Induction Tomography Based on the Eddy Current Model [pdf], Inverse Problems 31(6), 2015 [bib]
 M. Hintermüller, C.N. Rautenberg, On the density of classes of closed convex sets with pointwise constraints in Sobolev spaces [pdf], J. Math. Anal. Appl. 426(1) pp. 585593, 2015 [bib]
 M. Hintermüller, J. Rasch, Several pathfollowing methods for a class of gradient constrained variational inequalities [pdf], Computers and Mathematics with Applications 69(10),2015, pp. 10451067 [bib]
 C. Brett, C. Elliott, M. Hintermüller, C. Löbhard, Mesh Adaptivity in Optimal Control of Elliptic Variational Inequalities with PointTracking of the State [pdf], Interfaces and Free Boundaries 17(1), pp. 2153, 2015 [bib]
 A. Gaevskaja, M. Hintermüller, R.H.W. Hoppe, C. Löbhard, Adaptive finite elements for optimally controlled elliptic variational inequalities of obstacle type, in: Optimization with PDE Constraints, pp. 95105, 2014, Ronald Hoppe (Ed.) [bib]
 M. Hintermüller, T. Wu, Robust Principal Component Pursuit via Alternating Minimization on Matrix Manifolds [pdf], (the final publication is available at Springer via http://dx.doi.org/10.1007/s108510140527y), Journal of Mathematical Imaging and Vision 51(3), pp. 361377, 2015 [bib]
 M. Hintermüller, A. Langer, NonOverlapping Domain Decomposition Methods For Dual Total Variation Based Image Denoising, Journal of Scientific Computing 62(2), pp. 456481, 2015 [bib]
 M. Hintermüller, C.N. Rautenberg, J. Hahn, Functionalanalytic and numerical issues in splitting methods for total variationbased image reconstruction, Inverse Problems 30(5), pp. 055014, 2014 [bib]
 M. Hintermüller, A. Langer, Surrogate Functional Based Subspace Correction Methods for Image Processing, in Domain Decomposition Methods in Science and Engineering XXI Volume 98 of the series Lecture Notes in Computational Science and Engineering, pp. 829837, 2014 [bib]
 M. Hintermüller, M.M. RinconCamacho, An adaptive finite element method in $L2$TVbased image denoising, Inverse Problems and Imaging, 8(3), 2014, pp. 685711 [bib]
 M. Hintermüller, B.S. Mordukhovich, T. Surowiec, Several Approaches for the Derivation of Stationarity Conditions for Elliptic MPECs with UpperLevel Control Constraints, Mathematical Programming 146(12), pp. 555582 [bib]
 M. Hintermüller, D. Wegner, Optimal control of a semidiscrete CahnHilliardNavierStokes system, SIAM J. Control and Optimization 52(1), pp. 747772, 2014 [bib]
 M. Hintermüller, A. Schiela, W. Wollner, The length of the primaldual path in MoreauYosidabased pathfollowing for stateconstrained optimal control, SIAM J. Optimization 24(1), 108126, 2014 [bib]
 M. Hintermüller, R.H.W. Hoppe, C. Löbhard, A dualweighted residual approach to goaloriented adaptivity for optimal control of elliptic variational inequalities, ESAIM: Control, Optimisation and Calculus of Variations 20(2), 2014, pp. 524546 [bib]
 M. Hintermüller, T. Wu, A superlinearly convergent Rregularized Newton scheme for variational models with concave sparsitypromoting priors, Computational Optimization and Applications 57(1), pp. 125, 2014 [bib]
 M. Hintermüller, A. Langer, Subspace Correction Methods for a Class of Nonsmooth and Nonadditive Convex Variational Problems with Mixed $L^1/L^2$ DataFidelity in Image Processing, SIAM J. Imaging Sci., 6(4), 21342173, 2013 [bib]
 M. Hintermüller, C.N. Rautenberg, Parabolic quasivariational inequalities with gradienttype constraints, SIAM J. on Optimization 23(4), pp. 20902123, 2013 [bib]
 M. Hintermüller, T. Wu, A Smoothing Descent Method for Nonconvex TV^qModels, Lecture Notes in Computer Science 8293 (Efficient Algorithms for Global Optimization Methods in Computer Vision), pp. 119133, 2014 [bib]
 M. Hintermüller, T. Wu, Nonconvex TV^qModels in Image Restoration: Analysis and a TrustRegion Regularization Based Superlinearly Convergent Solver, SIAM Journal on Imaging Science 6, 2013, pp. 13851415 [bib]
 M. Hintermüller, T. Surowiec, A PDEconstrained generalized Nash equilibrium problem with pointwise control and state constraints, Pacific Journal on Optimization 9(2), pp. 251273, 2013 [bib]
 M. Hintermüller, D. Marahrens, P.A. Markowich, C. Sparber, Optimal bilinear control of GrossPitaevskii equations, SIAM J. Control and Optimization 51(3), pp. 25092543, 2013 [bib]
 M. Freiberger, M. Hintermüller, A. Laurain, H. Scharfetter, Topological sensitivity analysis in fluorescence optical tomography, Inverse Problems 29(2), 2013 [bib]
 M. Hintermüller, M. Hinze, C. Kahle, An adaptive finite element MoreauYosidabased solver for a coupled CahnHilliard/NavierStokes system, Journal of Computational Physics, 2012 [bib]
 M. Hintermüller, C.N. Rautenberg, A Sequential Minimization Technique for Elliptic QuasiVariational Inequalities with Gradient Constraints, SIAM Journal on Optimization 22(4), 2012, pp. 12241257 [bib]
 K. Bredies, Y. Dong, M. Hintermüller, Spatially dependent regularization parameter selection in total generalized variation models for image restoration, International Journal of Computer Mathematics 90(1), 2013, pp. 109123 [bib]
 M. Hintermüller, D. Wegner, Distributed optimal control of the CahnHilliard system including the case of a doubleobstacle homogeneous free energy density [pdf], SIAM J. Control Optim. 50, 2012, pp. 388418 [bib]
 M. Hintermüller, C.Y. Kao, A. Laurain, Principal Eigenvalue Minimization for an Elliptic Problem with Indefinite Weight and Robin Boundary Conditions, Applied Mathematics & Optimization 65(1), 111146, 2012, DOI 10.1007/s002450119153x [bib]
 M. Hintermüller, J.C. de los Reyes, A DualityBased Semismooth Newton Framework for Solving Variational Inequalities of the Second Kind, Interfaces and Free Boundaries 13, 2011, pp. 437462 [bib]
 M. Hintermüller, T. Surowiec, First Order Optimality Conditions for Elliptic Mathematical Programs with Equilibrium Constraints via Variational Analysis, SIAM J. Optim. 21(4), pp. 15611593, 2012 [bib]
 C. Elliott, M. Hintermüller, G. Leugering, J. Sokolowski, Advances in Shape and Topology Optimization: Theory, Numerics and New Application Areas., Optimization Methods and Software 26, Special Journal Issue 45, 2011, pp. 511894
 M. Hintermüller, M. Hinze, R.H.W. Hoppe, WeakDuality Based Adaptive Finite Element Methods for PDEConstrained Optimization with Pointwise Gradient StateConstraints, J. Comp. Math. 30, 2012, pp. 101123 [bib]
 C. Clason, M. Hintermüller, S.L. Keeling, F. Knoll, A. Laurain, G. Von Winckel, An image space approach to Cartesian based parallel MR imaging with total variation regularization, Medical Image Analysis 16(1), pp. 189200, 2012 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, Obstacle Problems with Cohesion: A HemiVariational Inequality Approach and its Efficient Numerical Solution [pdf], SIAM Journal on Optimization 21 (2), 2011, pp. 491516 [bib]
 S.L. Keeling, M. Hintermüller, F. Knoll, D. Kraft, A. Laurain, A Total Variation Based Approach to Correcting Surface Coil Magnetic Resonance Images, Applied Mathematics and Computation 218(2), 2011, pp. 219232 [bib]
 K. Chen, Y. Dong, M. Hintermüller, A Nonlinear Multigrid Solver with Line GaussSeidelSemismoothNewtonSmoother for the FenchelPreDual in Total Variation based Image Restoration, Inverse Problems and Imaging 5(2), pp. 323  339, 2011 [bib]
 M. Hintermüller, A. Laurain, A.A. Novotny, SecondOrder Topological Expansion for Electrical Impedance Tomography, Advances in Computational Mathematics 36(2), pp. 235265, 2012, DOI: 10.1007/s1044401192054 [bib]
 M. Hintermüller, M. Hinze, M.H. Tber, An Adaptive FiniteElement MoreauYosidaBased Solver for a Nonsmooth CahnHilliard Problem, Optimization Methods and Software 26 (45), Special Issue: Advances in Shape and Topology Optimization: Theory, Numerics and New Applications Areas, 2011, pp. 777811 [bib]
 M. Hintermüller, A. Laurain, Optimal Shape Design Subject to Elliptic Variational Inequalities, SIAM J. Control Optim. 49 (3), 2011, pp. 1015  1047 [bib]
 M. Hintermüller, Y. Dong, M.M. RinconCamacho, Automated Regularization Parameter Selection in MultiScale Total Variation Models for Image Restoration, Journal of Mathematical Imaging and Vision 40 (1), 2011, pp. 82104 [bib]
 M. Hintermüller, V.A. Kovtunenko, From Shape Variation to Topology Changes in Constrained Minimization: A Velocity MethodBased Concept, Optimization Methods and Software 26 (45), Special Issue: Advances in Shape and Topology Optimization: Theory, Numerics and New Applications Areas, 2011, pp. 513532 [bib]
 F. Knoll, Y. Dong, M. Hintermüller, C. Langkammer, R. Stollberger, Total Variation Denoising with Spatially Dependent Regularization [pdf], ISMRM 18th Annual Scientific Meeting and Exhibition 2010 Proceedings, p. 5088 [bib]
 Y. Dong, M. Hintermüller, M.M. RinconCamacho, A MultiScale Vectorial LtauTV Framework for Color Image Restoration, International Journal of Computer Vision 92 (3), 2011, pp. 296  307, DOI: 10.1007/s1126301003591 [bib]
 M. Hintermüller, R.H.W. Hoppe, GoalOriented Adaptivity in Pointwise State Constrained Optimal Control of Partial Differential Equations, SIAM J. Control Optim. 48, p. 54685487 (2010) [bib]
 M. Hintermüller, M.M. RinconCamacho, Expected Absolute Value Estimators for a Spatially Adapted Regularization Parameter Choice Rule in L1TVBased Image Restoration, Inverse Problems, Vol. 26, No. 8 (2010) [bib]
 M. Hintermüller, R.H.W. Hoppe, Goaloriented mesh adaptivity for mixed controlstate constrained elliptic optimal control problems, Computational Methods in Applied Sciences 15, 2010, pp. 97111, DOI: 10.1007/9789048132393_8 [bib]
 M. Hintermüller, M.H. Tber, An inverse problem in American options as a mathematical program with equilibrium constraints: Cstationarity and an activesetNewton solver., SIAM J. on Control and Optimization 48, 2010 [bib]
 R. H. Chan, Y. Dong, M. Hintermüller, An efficient twophase L1TV method for restoring blurred images with impulse noise, IEEE Transactions on Image Processing 19 (4), 2010 [bib]
 M. Hintermüller, I. Yousept, A sensitivitybased extrapolation technique for the numerical solution of stateconstrained optimal control problems, ESAIM Control, Optimization and Calculus of Variations 16 (3), 2010, pp. 503522 [bib]
 M. Hintermüller, A. Laurain, A shape and topology optimization technique for solving a class of linear complementarity problems in function space, Computational Optimization and Applications 46 (3), 2010, pp. 535569 [bib]
 F. Knoll, Y. Dong, M. Hintermüller, R. Stollberger, Automatic spatially dependent parameter selection for TV denoising of MR images with nonuniform noise distribution, Biomed Tech 55 (Suppl. 1), 2010, pp. 198  202 [bib]
 M. Hintermüller, S.L. Keeling, Image registration and segmentation based on energy minimization, Handbook of Optimization in Medicine. Series: Springer Optimization and Its Applications , Vol. 26 Pardalos, P.M.; Romeijn, H.E.(Eds.) 2009, XI I I, 442 p. 129 illus., Hardcover ISBN: 9780387097695 [bib]
 M. Hintermüller, M. Hinze, MoreauYosida Regularization in State Constrained Elliptic Control Problems: Error Estimates and Parameter Adjustment, SIAM J. on Numerical Analysis, 47 (3), 2009, pp. 16661683 [bib]
 M. Hintermüller, I. Kopacka, A smooth penalty approach and a nonlinear multigrid algorithm for elliptic MPECs, Computational Optimization and Applications 50 (1), 2011, pp. 111145 [bib]
 Y. Dong, M. Hintermüller, M. Neri, An Efficient PrimalDual Method for L1TV Image Restoration., SIAM J. Imaging Science, Vol. 2, Issue 4, pp. 11681189 (2009) [bib]
 M. Hintermüller, K. Kunisch, PDEConstrained Optimization Subject to Pointwise Constraints on the Control, the State and its Derivative, SIAM J. Optim., Vol. 20, Issue 3, pp. 11331156 (2009) [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, A PapkovichNeuberbased approach to cracks with contact in 3D, IMA J. Appl. Math. 74 (2009), pp. 325343 [bib]
 M. Hintermüller, I. Kopacka, Mathematical Programs with Complementarity Constraints in Function Space: C and Strong Stationarity and a PathFollowing Algorithm, SIAM J. Optim. Volume 20, Issue 2, pp. 868902 (2009) [bib]
 Y. Dong, M. Hintermüller, MultiScale Vectorial Total Variation with Automated Regularization Parameter Selection for Color Image Restoration, Springer Lecture Notes in Computer Science, no. 5567 (2009), pp.271281 [bib]
 M. Hintermüller, A.Laurain, Multiphase Image Segmentation and Modulation Recovery Based on Shape and Topological Sensitivity, Journal of Mathematical Imaging and Vision, 35 (2009) 1, pp. 122 [bib]
 M. Hintermüller, I. Kopacka, S. Volkwein, Meshindependence and preconditioning for solving parabolic control problems with mixed controlstate constraints, ESAIM: COCV 15 3 (2009), 626652, DOI: 10.1051/cocv:2008042 [bib]
 M. Hintermüller, R.H.W. Hoppe, Adaptive finite element methods for control constrained distributed and boundary optimal control problems. Numerical PDE Constrained Optimization., Series: Lecture Notes in Computational Science and Engineering , Vol. 72 Heinkenschloss, Matthias; Vicente, Luis Nunes; Fernandes, Luis Merca (Eds.) 2009, Softcover ISBN: 9783540773283 [bib]
 M. Hintermüller, K. Kunisch, Stationary optimal control problems with pointwise state constraints. Numerical PDE Constrained Optimization., Series: Lecture Notes in Computational Science and Engineering , Vol. 72 Heinkenschloss, Matthias; Vicente, Luis Nunes; Fernandes, Luis Merca (Eds.) 2009, Softcover ISBN: 9783540773283 [bib]
 M. Hintermüller, A. Laurain, Electrical Impedance Tomography: From Topology to Shape., Control and Cybernetics, Vol. 37, No. 4 (2008) [bib]
 M. Hintermüller, An activeset equality constrained Newton solver with feasibility restoration for inverse coefficient problems in elliptic variational inequalities, Inverse Problems 24 (2008), no. 3, 034017 [bib]
 M. Hintermüller, R.H.W. Hoppe, Goaloriented adaptivity in control constrained optimal control of partial differential equations, SIAM Journal on Control and Optimization, 47 (2008), pp. 17211743 [bib]
 M. Hintermüller, F. Tröltzsch, I. Yousept, Meshindependence of semismooth Newton methods for Lavrentievregularized state constrained nonlinear optimal control problems, Numerische Mathematik, 108 (2008), no. 4, pp. 571603 [bib]
 M. Hintermüller, R.H.W. Hoppe, Y. Iliash, M. Kieweg, An a posteriori error analysis of adaptive finite element methods for distributed elliptic control problems with control constraints, ESAIM: Control, Optimisation and Calculus of Variations (COCV), 14 3 (2008), pp. 540560 [bib]
 M. Hintermüller, A. Laurain, Where to create a hole?, European Consortium for Mathematics in Industry, ECMI Newsletter 41, 2007 [bib]
 M. Hintermüller, S. Volkwein, F. Diwoky, Fast solution techniques in constrained optimal boundary control of the semilinear heat equation, Internat. Ser. Numer. Math., 155, Birkhäuser, Basel, 2007, pp. 119147 [bib]
 M. Hintermüller, Meshindependence and fast local convergence of a primaldual activeset method for mixed controlstate constrained elliptic control problems, ANZIAM Journal, 49 (2007), no. 1, pp. 138 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, Constrained optimization for interface cracks in composite materials subject to nonpenetration conditions, Engineering Mathematics, 59 (2007), no. 3, pp. 301321 [bib]
 M. Hintermüller, A combined shape Newton and topology optimization technique in real time image segmentation, RealTime PDEConstrained Optimization, Comput. Sci. Eng., 3, SIAM, Philadelphia, PA, 2007, pp. 253  274 [bib]
 M. Hintermüller, K. Kunisch, Feasible and noninterior pathfollowing in constrained minimization with low multiplier regularity, SIAM J. Control and Optimization 45 (2006) 4, pp. 11981221 [bib]
 M. Hintermüller, K. Kunisch, Pathfollowing methods for a class of constrained minimization problems in function space, SIAM J. Optimization, 17 (2006) 1, pp. 159187 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, An optimization approach for the delamination of a composite material with nonpenetration, In Free and Moving Boundaries: Analysis, Simulation and Control, eds. R. Glowinski and J.P. Zolesio, Lecture Notes in Pure and Applied Mathematics, no. 252, Taylor & Francis CRC Press, London, 2006. [bib]
 M. Hintermüller, G. Stadler, A primaldual algorithm for TVbased infconvolutiontype image restoration, SIAM J. Scientific Computing, 28 (2006) 1, pp. 123 [bib]
 M. Hintermüller, M. Hinze, A SQPsemismooth Newtontype algorithm applied to control of the instationary NavierStokes system sub ject to control constraints, SIAM J. Optimization, 16 (2006) 4, pp. 11772000 [bib]
 M. Hintermüller, R. Griesse, M. Hinze, Differential stability of optimal control problems for the Navier Stokes equations, Numerical Functional Analysis and Optimization, 26 (2005) 78, pp. 829850 [bib]
 M. Hintermüller, M. Burger, Projected gradient flows for BV/Level set relaxation, Proc. Appl. Math. Mech., 5 (2005), pp. 1114 [bib]
 M. Hintermüller, Fast levelset based algorithms using shape and topological sensitivity information, Control and Cybernetics, 34 (2005) 1, pp. 305324 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, Generalized Newton methods for crack problems with nonpenetration condition, Numerical Methods for Partial Differential Equations, 21 (2005) 3, pp. 586610 [bib]
 M. Hintermüller, L.N. Vicente, Space mapping for optimal control of partial differential equations, SIAM J. Optimization, 15 (2005), pp. 10021025 [bib]
 M. Hintermüller, K. Kunisch, Totally bounded variation regularization as bilaterally constrained optimization problem, SIAM J. Applied Mathematics, 64 (2004), pp.13111333 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, Semismooth Newton methods for a class of unilaterally constrained variational problems, Advances in Mathematical Sciences and Applications, 14 (2004) 2, pp. 513535 [bib]
 M. Hintermüller, M. Ulbrich, A mesh independence result for semismooth Newton methods, Mathematical Programming, 101 (2004) 1, pp. 151184 [bib]
 M. Hintermüller, K. Kunisch, Y. Spasov, S. Volkwein, Dynamical system based optimal control of incompressible fluids, International Journal for Numerical Methods in Fluids, 46 (2004), pp. 345359 [bib]
 M. Hintermüller, V. Kovtunenko, K. Kunisch, The primaldual active set method for a crack problem with nonpenetration, IMA J. on Applied Mathematics, 69 (2004), pp. 126 [bib]
 M. Hintermüller, W. Ring, An inexact NewtonCGtype active contour approach for the minimization of the MumfordShah functional, Journal of Mathematical Imaging and Vision, 20 (2004), pp. 1942 [bib]
 M. Hintermüller, W. Ring, A level set approach for the solution of a stateconstrained optimal control problem, Numerische Mathematik 98 (2004) 1, pp. 135166 [bib]
 M. Hintermüller, G. Stadler, A semismooth Newton method for constrained linearquadratic control problems, ZAMM, 83 (2003)4, pp. 219237 [bib]
 M. Hintermüller, W. Ring, Numerical aspects for a level set based algorithm for state constrained optimal control problems, CAMESComputer Assisted Mechanics and Engineering Sciences, 10 (2003)2, pp. 149161 [bib]
 M. Hintermüller, W. Ring, A second order shape optimization approach for image segmentation, SIAM J. on Applied Mathematics, 64 (2003)2, pp. 442467 [bib]
 M. Hintermüller, W. Hinterberger, K. Kunisch, M. von Oehsen, O. Scherzer, Tube methods for BV regularization, Journal of Mathematical Imaging and Vision, 19 (2003)3, pp.219235 [bib]
 M. Hintermüller, K. Ito, K. Kunisch, The primaldual active set strategy as a semismooth Newton method, SIAM J. Optimization, 13 (2003) 3, pp. 865888 [bib]
 M. Hintermüller, A primaldual active set algorithm for bilaterally control constrained optimal control problems, Quarterly of Applied Mathematics, LXI 1 (2003), pp. 131161 [bib]
 M. Hintermüller, M. Hinze, Globalization of SQPmethods in control of the instationary NavierStokes equations, M2AN  Mathematical Modelling and Numerical Analysis, 36 (2002), pp. 725746 [bib]
 M. Hintermüller, Solving nonlinear programming problems with noisy function values and gradients, JOTA, 114 (2002)1, pp. 133169 [bib]
 M. Hintermüller, K. Kunisch, Inverse problems for elastohydrodynamic models, ZAMM, 81 (2001) Suppl.1, pp. S17S20 [bib]
 M. Hintermüller, On a globalized augmented Lagrangian SQPalgorithm for nonlinear optimal control problems with box constraints, in: Fast solution methods for discretized optimization problems. K.H. Hoffmann, R.H.W. Hoppe, V. Schulz (eds.), International Series of Numerical Mathematics 138, Birkhäuser publishers, Basel, 2001, pp. 139153 [bib]
 M. Hintermüller, P. Bachhiesl, H. Hutten, F. Kappel, H. Scharfetter, Efficient computation of optimal controls for the exchange process during the dialysis therapy, Computational Optimization and Applications, 18 (2001),pp.161175 [bib]
 M. Hintermüller, A proximal bundle method based on approximate subgradients, Computational Optimization and Applications, 20 (2001), pp. 245266. [bib]
 M. Hintermüller, Inverse coefficient problems for variational inequalities: optimality conditions and numerical realization, Mathematical Modelling and Numerical Analysis (M2AN), 35 (2001), pp. 129152 [bib]
 M. Hintermüller, K. Stüwe, Topology and isotherms revisited: the influence of laterally migrating drainage divides, Earth and Planetary Science Letters, 184 (2000), pp. 287303 [bib]
 M. Hintermüller, M. Bergounioux, M. Haddou, K. Kunisch, A comparison of a MoreauYosida based active set strategy and interior point methods for constrained optimal control problems, SIAM Journal on Optimization, 11 (2000), pp. 495521. [bib]
 M. Hintermüller, An algorithm for solving nonlinear programs with noisy inequality constraints, Nonlinear Optimization and Related Topics, Kluwer, 1999, pp. 143168. [bib]
 M. Hintermüller, Algorithms for Solving Nonlinear Programming Problems with Noisy Data, University publisher R. Trauner, Series C  Technology and Science, No. 23, 1998, 224 pp. [bib]