From the 1 of 6 linked papers with an AI index.
6 papers
State constrained convex Nash equilibrium problems coupled with linear hyperbolic PDEs
Marcelo Bongarti, Michael Hintermüller
The paper proves the existence of equilibria for convex generalized Nash equilibrium problems with state constraints that are coupled to linear hyperbolic PDEs, and derives first‑o…
Noisy quantum circuit simulation with the tensor jump method
Maximilian Fröhlich, Aaron Sander, Martin Eigel +2
Classical simulation of noisy quantum circuits is essential for validating algorithms, benchmarking hardware, and assessing error-mitigation strategies, but remains limited by the…
Constrained Neural Parameterization for Optimization in Function Spaces
Michael Hintermüller, Jianfeng Ning
We propose constrained neural parameterization schemes for several classes of constraints arising in optimization problems in function spaces. This is achieved by constructing smoo…
Structure versus regularity of set-valued maps in convex generalized Nash equilibrium problems in Banach spaces
Marcelo Bongarti, Michael Hintermüller
A generalized Nash equilibrium problem (GNEP) in Banach space consists of optimal control problems with couplings in both the objective functions and, most importantly, in th…
Quantum circuit simulation with a local time-dependent variational principle
Aaron Sander, Maximilian Fröhlich, Mazen Ali +6
Classical simulations of quantum circuits are vital for assessing potential quantum advantage and benchmarking devices, yet they require sophisticated methods to avoid the exponent…
Risk-averse optimal control of random elliptic variational inequalities
Amal Alphonse, Caroline Geiersbach, Michael Hintermüller +1
We consider a risk-averse optimal control problem governed by an elliptic variational inequality (VI) subject to random inputs. By deriving KKT-type optimality conditions for a pen…