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In one calculation, adjoint sensitivity analysis provides the gradient of a quantity of interest with respect to all system's parameters. Conventionally, adjoint solvers need to be implemented by differentiating computational models, which…

Machine Learning · Computer Science 2024-04-19 Defne E. Ozan , Luca Magri

Atomistic-to-Continuum (AtC) coupling methods are a novel means of computing the properties of a discrete crystal structure, such as those containing defects, that combine the accuracy of an atomistic (fully discrete) model with the…

Numerical Analysis · Mathematics 2013-09-25 Derek Olson , Pavel Bochev , Mitchell Luskin , Alexander V. Shapeev

This work focuses on the numerical assessment of the accuracy of an adjoint-based gradient in the perspective of variational data assimilation and parameter identification in glaciology. Using noisy synthetic data, we quantify the ability…

Classical Physics · Physics 2014-03-11 Nathan Martin , Jérôme Monnier

Derivatives of differential equation solutions are commonly for parameter estimation, fitting neural differential equations, and as model diagnostics. However, with a litany of choices and a Cartesian product of potential methods, it can be…

Numerical Analysis · Computer Science 2021-07-21 Yingbo Ma , Vaibhav Dixit , Mike Innes , Xingjian Guo , Christopher Rackauckas

Room geometry inference algorithms rely on the localization of acoustic reflectors to identify boundary surfaces of an enclosure. Rooms with highly absorptive walls or walls at large distances from the measurement setup pose challenges for…

Audio and Speech Processing · Electrical Eng. & Systems 2024-02-12 H. Nazim Bicer , Cagdas Tuna , Andreas Walther , Emanuël A. P. Habets

We present a complete analytical derivation of the equations used for stationary and nonstationary wave systems regarding resonant sound transmission and reflection described by the phenomenological Coupled-Mode Theory. We calculate the…

Classical Physics · Physics 2018-06-11 Theodoros T. Koutserimpas , Romain Fleury

We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions. It is the first on-policy approach that allows significantly more…

Designing free-form photonic devices is fundamentally challenging due to the vast number of possible geometries and the complex requirements of fabrication constraints. Traditional inverse-design approaches--whether driven by human…

Optics · Physics 2025-04-25 Dongjin Seo , Soobin Um , Sangbin Lee , Jong Chul Ye , Haejun Chung

The development of inverse design, where computational optimization techniques are used to design devices based on certain specifications, has led to the discovery of many compact, non-intuitive structures with superior performance. Among…

Optics · Physics 2019-02-25 Tyler W. Hughes , Momchil Minkov , Ian A. D. Williamson , Shanhui Fan

Adjoint variable method in combination with gradient descent optimization has been widely used for the inverse design of nanophotonic devices. In many of such optimizations, the design region is only a small fraction of the total…

Computational Physics · Physics 2019-07-24 Nathan Zhao , Salim Boutami , Shanhui Fan

The design space of dynamic multibody systems (MBSs), particularly those with flexible components, is considerably large. Consequently, having a means to efficiently explore this space and find the optimum solution within a feasible…

Optimization and Control · Mathematics 2025-01-08 Mehran Ebrahimi , Adrian Butscher , Hyunmin Cheong , Francesco Iorio

One-dimensional signal decomposition is a well-established and widely used technique across various scientific fields. It serves as a highly valuable pre-processing step for data analysis. While traditional decomposition techniques often…

Machine Learning · Computer Science 2025-06-09 Samuele Salti , Andrea Pinto , Alessandro Lanza , Serena Morigi

One difficulty in developing numerical methods for hyperbolic systems of conservation laws is the fact that solutions often contain regions where much higher resolution is required than elsewhere in the domain, particularly since the…

Numerical Analysis · Mathematics 2015-11-12 Brisa N. Davis , Randall J. LeVeque

We present a mechanism to explicitly couple the finite-difference discretizations of 2D acoustic and isotropic elastic wave systems that are separated by straight interfaces. Such coupled simulations allow the application of the elastic…

Computational Physics · Physics 2021-04-13 Longfei Gao , David Keyes

We use the adjoint methods to study the static Hamilton-Jacobi equations and to prove the speed of convergence for those equations. The main new ideas are to introduce adjoint equations corresponding to the formal linearizations of…

Analysis of PDEs · Mathematics 2012-01-04 Hung Vinh Tran

With their ability to handle an increased amount of information, multivariate and multichannel signals can be used to solve problems normally not solvable with signals obtained from a single source. One such problem is the decomposition…

Information Theory · Computer Science 2019-04-02 Ljubisa Stankovic , Milos Brajovic , Milos Dakovic , Danilo Mandic

This article explores the generalized analysis-of-variance or ANOVA dimensional decomposition (ADD) for multivariate functions of dependent random variables. Two notable properties, stemming from weakened annihilating conditions, reveal…

Numerical Analysis · Mathematics 2014-08-05 Sharif Rahman

This article presents the experimental characterization of nonreciprocal elastic wave transmission in a single-mode elastic waveguide. This asymmetric system is obtained by coupling a selection layer with a conversion layer: the selection…

Classical Physics · Physics 2015-12-09 Thibaut Devaux , Vincent Tournat , Olivier Richoux , Vincent Pagneux

The implementation of the discrete adjoint method for exponential time differencing (ETD) schemes is considered. This is important for parameter estimation problems that are constrained by stiff time-dependent PDEs when the discretized PDE…

Optimization and Control · Mathematics 2016-10-11 Kai Rothauge , Eldad Haber , Uri Ascher

A mechanism is described to symmetrize the ultraspherical spectral method for self-adjoint problems. The resulting discretizations are symmetric and banded. An algorithm is presented for an adaptive spectral decomposition of self-adjoint…

Numerical Analysis · Mathematics 2020-04-22 Jared Lee Aurentz , Richard Mikael Slevinsky