Combination of object-oriented programming with automatic differentiation techniques facilitates the solution of data fitting, control, and design problems driven by explicit time stepping schemes for initial-boundary value problems. The C++ class fdtd takes a complete specification of a single step, along with some associated code, and assembles from it a complete simulator, along with the linearized and adjoint simulations. The result is a (nonlinear) operator in the sense of the Hilbert Class Library (HCL), a C++ software package for optimization. The HCL operator so produced links directly with any of the HCL optimization algorithms. Moreover the performance of simulators constructed in this way is equivalent to that of optimized Fortra...
This work was also published as a Rice University thesis/dissertation.The adjoint-state method is wi...
AbstractParametric ordinary differential equations (ODE) arise in many engineering applications. We ...
This paper presents a number of algorithm developments for adjoint meth-ods using the `discrete &apo...
Combination of object-oriented programming with automatic differentiation techniques facilitates the...
The C++ class fdtd uses automatic differentiation techniques to implement an abstract time stepping ...
Adaptive grids in inverse and control problems can lead to computed objective functions that are non...
This dissertation is concerned with the computation of arbitrary-order derivative projections (tange...
The object-oriented programming paradigm can be used to overcome the incompatibilities between off-t...
Adjoint state method is a well-known method to efficiently compute the gradient of a cost or objecti...
This report introduces the "Time Stepping Package for Optimization", or TSOpt, which is an interface...
International audienceThis paper proposes a strategy to derive an adjoint-based optimization code fr...
The last decade has established the adjoint method as an effective way in Computational Fluid Dynami...
When using simulation codes, one often has the task of minimizing a scalar objective function with r...
The adjoint-state method is widely used for computing gradients in simulation-driven optimization pr...
ABSTRACT. Adjoint methods are the choice approach to obtain gradients of large simulation codes. Aut...
This work was also published as a Rice University thesis/dissertation.The adjoint-state method is wi...
AbstractParametric ordinary differential equations (ODE) arise in many engineering applications. We ...
This paper presents a number of algorithm developments for adjoint meth-ods using the `discrete &apo...
Combination of object-oriented programming with automatic differentiation techniques facilitates the...
The C++ class fdtd uses automatic differentiation techniques to implement an abstract time stepping ...
Adaptive grids in inverse and control problems can lead to computed objective functions that are non...
This dissertation is concerned with the computation of arbitrary-order derivative projections (tange...
The object-oriented programming paradigm can be used to overcome the incompatibilities between off-t...
Adjoint state method is a well-known method to efficiently compute the gradient of a cost or objecti...
This report introduces the "Time Stepping Package for Optimization", or TSOpt, which is an interface...
International audienceThis paper proposes a strategy to derive an adjoint-based optimization code fr...
The last decade has established the adjoint method as an effective way in Computational Fluid Dynami...
When using simulation codes, one often has the task of minimizing a scalar objective function with r...
The adjoint-state method is widely used for computing gradients in simulation-driven optimization pr...
ABSTRACT. Adjoint methods are the choice approach to obtain gradients of large simulation codes. Aut...
This work was also published as a Rice University thesis/dissertation.The adjoint-state method is wi...
AbstractParametric ordinary differential equations (ODE) arise in many engineering applications. We ...
This paper presents a number of algorithm developments for adjoint meth-ods using the `discrete &apo...