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The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimisation of…

This study investigates the convergence properties of a collection of iterative electron ptychography methods, under low electron doses ($<$ 10$^3$ $e^-/A^2$) and gives particular attention to the impact of the user-defined update…

Existing high-dimensional Bayesian optimization (BO) methods aim to overcome the curse of dimensionality by carefully encoding structural assumptions, from locality to sparsity to smoothness, into the optimization procedure. Surprisingly,…

Machine Learning · Computer Science 2026-04-10 Colin Doumont , Donney Fan , Natalie Maus , Jacob R. Gardner , Henry Moss , Geoff Pleiss

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during…

Machine Learning · Statistics 2017-11-22 Peter I. Frazier , Jialei Wang

Ptychography is a popular technique to achieve diffraction limited resolution images of a two or three dimensional sample using high frame rate detectors. We introduce a relaxation of common projection algorithms to account for…

Inverse problems are prevalent in numerous scientific and engineering disciplines, where the objective is to determine unknown parameters within a physical system using indirect measurements or observations. The inherent challenge lies in…

Computational Physics · Physics 2025-02-06 Georgios E. Pavlou , Vasiliki Pavlidou , Vagelis Harmandaris

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning…

In this paper, Bayesian optimisation is used to simultaneously search the optimal values of the shape parameter and the radius in radial basis function partition of unity interpolation problem. It is a probabilistic iterative approach that…

Numerical Analysis · Mathematics 2023-11-08 Roberto Cavoretto , Alessandra De Rossi , Sandro Lancellotti , Federico Romaniello

Physico-chemical continuum battery models are typically parameterized by manual fits, relying on the individual expertise of researchers. In this article, we introduce a computer algorithm that directly utilizes the experience of battery…

Data Analysis, Statistics and Probability · Physics 2023-02-08 Yannick Kuhn , Hannes Wolf , Arnulf Latz , Birger Horstmann

Aberration-corrected optics have made electron microscopy at atomic-resolution a widespread and often essential tool for nanocharacterization. Image resolution is dominated by beam energy and the numerical aperture of the lens ({\alpha}),…

With the development of deep learning, the single super-resolution image reconstruction network models are becoming more and more complex. Small changes in hyperparameters of the models have a greater impact on model performance. In the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-14 Yibo Guo , Haidi Wang , Yiming Fan , Shunyao Li , Mingliang Xu

Advances in predictive modeling across multiple disciplines have yielded generative models capable of high veracity in predicting macroscopic functional responses of materials. Correspondingly, of interest is the inverse problem of finding…

Disordered Systems and Neural Networks · Physics 2020-08-11 Sergei V. Kalinin , Maxim Ziatdinov , Rama K. Vasudevan

Antenna array calibration is necessary to maintain the high fidelity of beam patterns across a wide range of advanced antenna systems and to ensure channel reciprocity in time division duplexing schemes. Despite the continuous development…

Signal Processing · Electrical Eng. & Systems 2023-05-26 Sergey S. Tambovskiy , Gábor Fodor , Hugo M. Tullberg

These days we live in a world with a permanent electromagnetic field. This raises many questions about our health and the deployment of new equipment. The problem is that these fields remain difficult to visualize easily, which only some…

Signal Processing · Electrical Eng. & Systems 2022-03-04 Angesom Ataklity Tesfay , Laurent Clavier

Bayesian optimization (BO) recently became popular in robotics to optimize control parameters and parametric policies in direct reinforcement learning due to its data efficiency and gradient-free approach. However, its performance may be…

Robotics · Computer Science 2019-10-14 Noémie Jaquier , Leonel Rozo , Sylvain Calinon , Mathias Bürger

Electron tomography is a technique used in both materials science and structural biology to image features well below optical resolution limit. In this work, we present a new algorithm for reconstructing the three-dimensional(3D)…

Signal Processing · Electrical Eng. & Systems 2018-07-12 David Ren , Michael Chen , Laura Waller , Colin Ophus

Parameter reconstructions are indispensable in metrology. Here, the objective is to to explain $K$ experimental measurements by fitting to them a parameterized model of the measurement process. The model parameters are regularly determined…

Computational Physics · Physics 2022-10-17 Matthias Plock , Kas Andrle , Sven Burger , Philipp-Immanuel Schneider

Ptychography is a promising phase retrieval technique for visible light, X-ray and electron beams. Conventional ptychography reconstructs the amplitude and phase of an object light from a set of the diffraction intensity patterns obtained…

We develop a Bayesian approach called Bayesian projected calibration to address the problem of calibrating an imperfect computer model using observational data from a complex physical system. The calibration parameter and the physical…

Methodology · Statistics 2019-02-08 Fangzheng Xie , Yanxun Xu

Electron microscopy is a powerful tool for studying the properties of materials down to their atomic structure. In many cases, the quantitative interpretation of images requires simulations based on atomistic structure models. These…