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Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for…

Cosmology and Nongalactic Astrophysics · Physics 2010-12-23 David Parkinson , Andrew R. Liddle

We analyze the posterior contraction rates of parameters in Bayesian models via the Langevin diffusion process, in particular by controlling moments of the stochastic process and taking limits. Analogous to the non-asymptotic analysis of…

Statistics Theory · Mathematics 2022-08-18 Wenlong Mou , Nhat Ho , Martin J. Wainwright , Peter Bartlett , Michael I. Jordan

Bayesian methods which utilize Bayes' theorem to update the knowledge of desired parameters after each measurement, are used in a wide range of quantum science. For various applications in quantum science, efficiently and accurately…

Quantum Physics · Physics 2021-07-02 Chengyin Han , Jiahao Huang , Xunda Jiang , Ruihuan Fang , Yuxiang Qiu , Bo Lu , Chaohong Lee

Statistical modeling can involve a tension between assumptions and statistical identification. The law of the observable data may not uniquely determine the value of a target parameter without invoking a key assumption, and, while…

Methodology · Statistics 2022-12-06 Paul Gustafson

A theoretical method for the estimation of cross sections and rates for excitation and charge transfer processes in low-energy hydrogen atom collisions with neutral atoms, based on an asymptotic two-electron model of ionic-covalent…

Atomic Physics · Physics 2016-05-04 Paul S. Barklem

An imprecise Bayesian nonparametric approach to system reliability with multiple types of components is developed. This allows modelling partial or imperfect prior knowledge on component failure distributions in a flexible way through…

Methodology · Statistics 2016-09-19 Gero Walter , Louis J. M. Aslett , Frank P. A. Coolen

The propagation of uncertainties in reaction cross sections and rates of neutron-, proton-, and alpha-induced reactions into the final isotopic abundances obtained in nucleosynthesis models is an important issue in studies of…

High Energy Astrophysical Phenomena · Physics 2025-01-07 T. Rauscher , N. Nishimura , G. Cescutti , R. Hirschi , A. St. J. Murphy , C. Travaglio

We present a theoretical framework to quantify statistical uncertainties in covariant density functional theory (CDFT) for both nuclear matter and finite nuclei, based on a relativistic point-coupling energy density functional (EDF). By…

Nuclear Theory · Physics 2026-04-10 X. Zhang , C. C. Wang , C. R. Ding , J. M. Yao

Bayesian model mixing (BMM) is a statistical technique that can combine constraints from different regions of an input space in a principled way. Here we extend our BMM framework for the equation of state (EOS) of strongly interacting…

Nuclear Theory · Physics 2025-05-27 A. C. Semposki , C. Drischler , R. J. Furnstahl , D. R. Phillips

The roles of nuclear deformation and neutron transfer in sub-barrier capture process are studied within the quantum diffusion approach. The change of the deformations of colliding nuclei with neutron exchange can crucially influence the…

Nuclear Theory · Physics 2015-05-30 V. V. Sargsyan , G. G. Adamian , N. V. Antonenko , W. Scheid , H. Q. Zhang

Breakup reactions are one of the favored probes to study loosely bound nuclei, particularly those in the limit of stability forming a halo. In order to interpret such breakup experiments, the continuum discretized coupled channel method is…

Nuclear Theory · Physics 2022-11-08 Özge Sürer , Filomena M. Nunes , Matthew Plumlee , Stefan M. Wild

The characterization of drug-protein interactions is crucial in the high-throughput screening for drug discovery. The deep learning-based approaches have attracted attention because they can predict drug-protein interactions without…

Machine Learning · Computer Science 2020-12-22 QHwan Kim , Joon-Hyuk Ko , Sunghoon Kim , Nojun Park , Wonho Jhe

A lower bound is an important tool for predicting the performance that an estimator can achieve under a particular statistical model. Bayesian bounds are a kind of such bounds which not only utilizes the observation statistics but also…

Statistics Theory · Mathematics 2023-03-02 Shuo Tang , Gerald LaMountain , Tales Imbiriba , Pau Closas

Understanding the uncertainty of a neural network's (NN) predictions is essential for many purposes. The Bayesian framework provides a principled approach to this, however applying it to NNs is challenging due to large numbers of parameters…

Machine Learning · Statistics 2020-02-27 Tim Pearce , Felix Leibfried , Alexandra Brintrup , Mohamed Zaki , Andy Neely

Recent measurements for fusion cross section at energies around the Coulomb barrier have systematically indicated a significant deviation of fusion cross sections from a prediction of double-folding model. It has been argued that the…

Nuclear Theory · Physics 2009-11-11 K. Hagino , K. Washiyama

We review the status and prospects of theoretical studies of neutrino-nucleus interactions, and discuss the influence of the treatment of nuclear effects on the determination of oscillation parameters. The models developed to describe the…

Nuclear Theory · Physics 2017-11-01 Omar Benhar , Patrick Huber , Camillo Mariani , Davide Meloni

We consider linear reaction--diffusion problems with mixed Diriclet-Neumann-Robin conditions. The diffusion matrix, reaction coefficient, and the coefficient in the Robin boundary condition are defined with an uncertainty which allow…

Numerical Analysis · Mathematics 2014-07-29 O. Mali , S. Repin

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments -- such as PREX and CREX -- provide a clean and largely model-independent…

Nuclear Theory · Physics 2021-08-11 Giuliani Pablo , Piekarewicz Jorge

We consider elastic reflection and transmission of electrons by a disordered system characterized by a $2N\!\times\!2N$ scattering matrix $S$. Expressing $S$ in terms of the $N$ radial parameters and of the four $N\!\times\!N$ unitary…

Condensed Matter · Physics 2009-10-22 Rodolfo A. Jalabert , Jean-Louis Pichard

We study the evolution of the (e,e'p) cross section on nuclei with increasing asymmetry between the number of neutrons and protons. The calculations are done within the framework of the distorted-wave impulse approximation, by adopting…

Nuclear Theory · Physics 2011-09-02 C. Giusti , A. Meucci , F. D. Pacati , G. Co' , V. De Donno
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