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This guide offers suggestions/insights on uncertainty quantification of nuclear structure models. We discuss a simple approach to statistical error estimates, strategies to assess systematic errors, and show how to uncover…

Nuclear Theory · Physics 2014-05-26 J. Dobaczewski , W. Nazarewicz , P. -G. Reinhard

The ability to quantify distinctness of a cluster structure is fundamental for certain simulation studies, in particular for those comparing performance of different classification algorithms. The intrinsic integral measure based on the…

Statistics Theory · Mathematics 2014-07-29 Ewa Nowakowska , Jacek Koronacki , Stan Lipovetsky

Cavitation has long been recognized as a crucial predictor, or precursor, to the ultimate failure of various materials, ranging from ductile metals to soft and biological materials. Traditionally, cavitation in solids is defined as an…

Uncertainty estimation, which provides a means of building explainable neural networks for medical imaging applications, have mostly been studied for single deep learning models that focus on a specific task. In this paper, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Leonhard F. Feiner , Martin J. Menten , Kerstin Hammernik , Paul Hager , Wenqi Huang , Daniel Rueckert , Rickmer F. Braren , Georgios Kaissis

Fitting spectral distributions of total fluxes or image intensities are two standard methods for estimating the masses of starless cores and protostellar envelopes. These mass estimates, which are the main source and basis of our knowledge…

Instrumentation and Methods for Astrophysics · Physics 2016-09-28 Alexander Men'shchikov

Thermo-osmotic flows, generated by applying a thermal gradient along a liquid-solid interface, could be harnessed to convert waste heat into electricity. While this phenomenon has been known for almost a century, there is a crucial need to…

Soft Condensed Matter · Physics 2024-07-15 Mehdi Ouadfel , Samy Merabia , Yasutaka Yamaguchi , Laurent Joly

It has been previously shown that any measurement system specific relationship (SSR)/ mathematical-model Y_d = f_d ({X_m}) or so is bracketed with certain parameters which should prefix the achievable-accuracy/ uncertainty (e_d^Y) of a…

General Physics · Physics 2020-03-06 B. P. Datta

In an incoherent dictionary, most signals that admit a sparse representation admit a unique sparse representation. In other words, there is no way to express the signal without using strictly more atoms. This work demonstrates that sparse…

Information Theory · Computer Science 2016-11-18 Joel A. Tropp

Refractory multi-principal element alloys exhibiting promising mechanical properties such as excellent strength retention at elevated temperatures have been attracting increasing attention. Although their inherent chemical complexity is…

Materials Science · Physics 2022-12-28 Ian Geiger , Jian Luo , Enrique J. Lavernia , Penghui Cao , Diran Apelian , Timothy J. Rupert

Exoplanet characterization is one of the main foci of current exoplanetary science. For super-Earths and sub-Neptunes, we mostly rely on mass and radius measurements, which allow to derive the body's mean density and give a rough estimate…

Earth and Planetary Astrophysics · Physics 2021-06-16 J. F. Otegi , C. Dorn , R. Helled , F. Bouchy , J. Haldemann , Y. Alibert

Multiphase flows are commonly found in chemical engineering processes such as distillation columns, bubble columns, fluidized beds and heat exchangers. The physical boundaries of domains in numerical simulations of multiphase flows are…

Fluid Dynamics · Physics 2023-04-21 Tanyakarn Treeratanaphitak , Nasser Mohieddin Abukhdeir

Interferometry is a prime technique for modern precision measurements. Atoms, unlike light, have significant interactions with electric, magnetic, and gravitational fields, making their use in interferometric applications particularly…

Quantum Gases · Physics 2023-07-12 Maren E. Mossman , Ryan A. Corbin , Michael McNeil Forbes , Peter Engels

Introducing accelerated reconstruction algorithms into clinical settings requires measures of uncertainty quantification that accurately assess the relevant uncertainty introduced by the reconstruction algorithm. Many currently deployed…

Image and Video Processing · Electrical Eng. & Systems 2025-08-12 Luca L. C. Trautmann , Peter A. Wijeratne , Itamar Ronen , Ivor J. A. Simpson

Quantum sensing exploits quantum phenomena to enhance the detection and estimation of classical parameters of physical systems and biological entities, particularly so as to overcome the inefficiencies of its classical counterparts. A…

The effect of uncertainties and noise on a quantity of interest (model output) is often better described by its probability density function (PDF) than by its moments. Although density estimation is a common task, the adequacy of…

Numerical Analysis · Mathematics 2019-06-21 Adi Ditkowski , Gadi Fibich , Amir Sagiv

The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surfaces. The technique combines interferometric measurements,…

To simulate the transient enhanced diffusion near the surface or interface, a set of equations describing the impurity diffusion and quasichemical reactions of dopant atoms and point defects in ion-implanted layers is proposed and analyzed.…

Materials Science · Physics 2007-05-23 O. I. Velichko , Yu. P. Shaman , A. K. Fedotov , A. V. Masanik

This paper presents a method for performing Uncertainty Quantification in high-dimensional uncertain spaces by combining arbitrary polynomial chaos with a recently proposed scheme for sensitivity enhancement (1). Including available…

Numerical Analysis · Mathematics 2024-02-09 Nick Pepper , Francesco Montomoli , Kyriakos Kantarakias

We show how impurity atoms can measure moments of ultracold atomic gas densities, using the example of bosons in a one-dimensional lattice. This builds on a body of work regarding the probing of systems by measuring the dephasing of an…

Quantum Gases · Physics 2016-04-12 Thomas J. Elliott , Tomi H. Johnson

In this second part of our two-part paper, we provide a detailed, frequentist framework for propagating uncertainties within our multivariate linear least squares model. This permits us to quantify the impact of uncertainties in…

Applications · Statistics 2019-08-09 Pranay Seshadri , Andrew Duncan , Duncan Simpson , George Thorne , Geoffrey Parks