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We present a program called potfit which generates an effective atomic interaction potential by matching it to a set of reference data computed in first-principles calculations. It thus allows to perform large-scale atomistic simulations of…

Materials Science · Physics 2007-05-23 Peter Brommer , Franz Gähler

Plotting the residuals is a recommended procedure to diagnose deviations from linear model assumptions, such as non-linearity, heteroscedasticity, and non-normality. The presence of structure in residual plots can be tested using the lineup…

Machine Learning · Statistics 2024-11-05 Weihao Li , Dianne Cook , Emi Tanaka , Susan VanderPlas , Klaus Ackermann

A new dynamical cascade code for decaying hot nuclei is proposed and specially adapted to the synthesis of super-heavy nuclei. For such a case, the interesting channel is the tiny fraction that will decay through particles emission, thus…

Nuclear Theory · Physics 2009-11-10 Bertrand Bouriquet , Yasuhisa Abe , David Boilley

The anomaly detection problem for univariate or multivariate time series is a critical question in many practical applications as industrial processes control, biological measures, engine monitoring, supervision of all kinds of behavior. In…

Statistics Theory · Mathematics 2020-10-16 Marie Cottrell , Cynthia Faure , Jérôme Lacaille , Madalina Olteanu

Quantitative program analysis involves computing numerical quantities about individual or collections of program executions. An example of such a computation is quantitative information flow analysis, where one estimates the amount of…

Logic in Computer Science · Computer Science 2014-05-29 Daniel J. Fremont , Sanjit A. Seshia

We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instant out-of-sample predictions for proton and carbon nuclear chemical shifts, atomic core level excitations, and forces on atoms reach…

Chemical Physics · Physics 2015-08-26 Matthias Rupp , Raghunathan Ramakrishnan , O. Anatole von Lilienfeld

This paper describes the inversion procedure being used operationally at the Norwegian Meteorological Institute for estimating ash emission rates from retrieved satellite ash column amounts and a priori knowledge. The overall procedure…

Atmospheric and Oceanic Physics · Physics 2020-05-21 André R. Brodtkorb , Anna Benedictow , Heiko Klein , Arve Kylling , Agnes Nyiri , Alvaro Valdebenito , Espen Sollum

This report summarizes laboratory measurements of atomic wavelengths, energy levels, hyperfine and isotope structure, energy level lifetimes, and oscillator strengths. Theoretical calculations of lifetimes and oscillator strengths are also…

Solar and Stellar Astrophysics · Physics 2012-11-08 Gillian Nave , Glenn M. Wahlgren , Jeffrey R. Fuhr

Our knowledge of quantum mechanics can satisfactorily describe simple, microscopic systems, but is yet to explain the macroscopic everyday phenomena we observe. Here we aim to shed some light on the quantum-to-classical transition as seen…

Quantum Physics · Physics 2020-08-14 Isadora Veeren , Fernando de Melo

Estimating and quantifying uncertainty in unknown system parameters from limited data remains a challenging inverse problem in a variety of real-world applications. While many approaches focus on estimating constant parameters, a subset of…

Methodology · Statistics 2023-05-09 Andrea Arnold

Development of scientific and engineering software is usually different and could be more challenging than the development of conventional enterprise software. The authors were involved in a technology-transfer project between academia and…

Software Engineering · Computer Science 2020-03-03 Vahid Garousi , Ehsan Abbasi , Bedir Tekinerdogan

In this article we present very intuitive, easy to follow, yet mathematically rigorous, approach to the so called data fitting process. Rather than minimizing the distance between measured and simulated data points, we prefer to find such…

Data Analysis, Statistics and Probability · Physics 2017-08-07 Marek W. Gutowski

We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to…

Data Analysis, Statistics and Probability · Physics 2024-01-30 Martino Trassinelli

Radiative transfer calculations are essential for modeling planetary atmospheres. However, standard methods are computationally demanding and impose accuracy-speed trade-offs. High computational costs force numerical simplifications in…

Earth and Planetary Astrophysics · Physics 2025-11-03 Isaac Malsky , Tiffany Kataria , Natasha E. Batalha , Matthew Graham

We propose a novel family of test statistics to detect the presence of changepoints in a sequence of dependent, possibly multivariate, functional-valued observations. Our approach allows to test for a very general class of changepoints,…

Methodology · Statistics 2023-10-10 B. Cooper Boniece , Lajos Horváth , Lorenzo Trapani

We investigate the transition of a quantum wave-packet through a one-dimensional avoided crossing of molecular energy levels when the energy levels at the crossing point are tilted. Using superadiabatic representations, and an approximation…

Mathematical Physics · Physics 2010-07-16 Volker Betz , Benjamin D. Goddard

Automatic differentiation represents a paradigm shift in scientific programming, where evaluating both functions and their derivatives is required for most applications. By removing the need to explicitly derive expressions for gradients,…

Chemical Physics · Physics 2022-06-29 Muhammad F. Kasim , Susi Lehtola , Sam M. Vinko

We elaborate and validate a generalization of the renowned transition-path-sampling algorithm for a paradigmatic model of active particles, namely the Run-and-Tumble particles. Notwithstanding the non-equilibrium character of these…

Soft Condensed Matter · Physics 2024-11-20 Thomas Kiechl , Thomas Franosch , Michele Caraglio

Atom counting theory can be used to study the role of thermal noise in quantum phase transitions and to monitor the dynamics of a quantum system. We illustrate this for a strongly correlated fermionic system, which is equivalent to an…

Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…

Machine Learning · Computer Science 2025-10-03 Hung Le , Sherif Abbas , Minh Hoang Nguyen , Van Dai Do , Huu Hiep Nguyen , Dung Nguyen