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Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical…

Nuclear Theory · Physics 2017-03-01 A. E. Lovell , F. M. Nunes , J. Sarich , S. M. Wild

Starting from a set of different two- and three-nucleon interactions from chiral effective field theory, we use the importance-truncated no-core shell model for ab initio calculations of excitation energies as well as electric quadrupole…

Nuclear Theory · Physics 2016-08-08 Angelo Calci , Robert Roth

Experimental isomeric ratios of light (A$\le$4) particle-induced nuclear reactions were compiled for the product nuclides having metastable states with half-lives longer than 0.1 sec. The experimental isomeric ratio data were taken from the…

Nuclear Experiment · Physics 2023-08-09 A. Rodrigo , N. Otuka , S. Takács , A. J. Koning

With the advance of efficient analytical methods for sensitivity analysis ofprobabilistic networks, the interest in the sensitivities revealed by real-life networks is rekindled. As the amount of data resulting from a sensitivity analysis…

Artificial Intelligence · Computer Science 2013-01-14 Linda C. van der Gaag , Silja Renooij

This review article provides an overview of structurally oriented experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear magnetic resonance (NMR) spectroscopy and room temperature…

Sampling is an established technique to scale graph neural networks to large graphs. Current approaches however assume the graphs to be homogeneous in terms of relations and ignore relation types, critically important in biomedical graphs.…

Machine Learning · Computer Science 2021-05-31 Arthur Feeney , Rishabh Gupta , Veronika Thost , Rico Angell , Gayathri Chandu , Yash Adhikari , Tengfei Ma

Reaction networks are a general formalism for describing collections of classical entities interacting in a random way. While reaction networks are mainly studied by chemists, they are equivalent to Petri nets, which are used for similar…

Mathematical Physics · Physics 2021-11-23 John C. Baez

Network analysis is currently used in a myriad of contexts: from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies, and from finding friends to uncovering criminal activity.…

Data Analysis, Statistics and Probability · Physics 2010-04-28 R. Guimera , M. Sales-Pardo

Extremal Graph Theory aims to determine bounds for graph invariants as well as the graphs attaining those bounds. We are currently developping PHOEG, an ecosystem of tools designed to help researchers in Extremal Graph Theory. It uses a big…

Discrete Mathematics · Computer Science 2017-12-22 Gauvain Devillez , Pierre Hauweele , Hadrien Mélot

We present calculations of neutron thermal cross sections, Westcott factors, resonance integrals, Maxwellian-averaged cross sections and astrophysical reaction rates for 843 ENDF materials using data from the major evaluated nuclear…

Solar and Stellar Astrophysics · Physics 2013-09-13 B. Pritychenko , S. F. Mughabghab

Graphs are commonly used to characterise interactions between objects of interest. Because they are based on a straightforward formalism, they are used in many scientific fields from computer science to historical sciences. In this paper,…

Machine Learning · Statistics 2015-06-24 Pierre Latouche , Fabrice Rossi

We study a model for a statistical network formed by interactions between its nodes and links. Each node can be in one of two states (Ising spin up or down) and the node-link interaction facilitates linking between the like nodes. For high…

Statistical Mechanics · Physics 2009-11-11 A. E. Allahverdyan , K. G. Petrosyan

Study of the fusion reactions between hydrogen isotopes in muonic molecules is the first example of the accurate accounting of the nucleus charge screening by a muon in the fusion process. At LUNA installation the measurements of…

Nuclear Theory · Physics 2008-04-25 L. N. Bogdanova

Equivariant graph neural networks force fields (EGraFFs) have shown great promise in modelling complex interactions in atomic systems by exploiting the graphs' inherent symmetries. Recent works have led to a surge in the development of…

To study the effects of Online Social Network (OSN) activity on real-world offline events, researchers need access to OSN data, the reliability of which has particular implications for social network analysis. This relates not only to the…

Social and Information Networks · Computer Science 2022-02-28 Derek Weber , Mehwish Nasim , Lewis Mitchell , Lucia Falzon

Accurate atomic physics reference data are a crucial requirement for analysis and interpretation of observed spectra, even more so for observations with high spectral resolution. This document provides a curated list of atomic physics…

Instrumentation and Methods for Astrophysics · Physics 2025-06-23 N. Hell , G. V. Brown , M. E. Eckart , A. J. Fairchild , C. A. Kilbourne , M. A. Leutenegger , F. S. Porter , M. C. Witthoeft

In this paper we present a computational model which decodes the spatio-temporal data from electro-physiological measurements of neuronal networks and reconstructs the network structure on a macroscopic domain, representing the connectivity…

Quantitative Methods · Quantitative Biology 2025-02-14 Ilya Auslender , Lorenzo Pavesi

The phenomenal growth of graph data from a wide variety of real-world applications has rendered graph querying to be a problem of paramount importance. Traditional techniques use structural as well as node similarities to find matches of a…

Databases · Computer Science 2021-05-14 Jithin Vachery , Akhil Arora , Sayan Ranu , Arnab Bhattacharya

Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements…

We present the state-of-the-art single-zone nuclear reaction network WinNet that is capable of calculating the nucleosynthetic yields of a large variety of astrophysical environments and conditions. This ranges from the calculation of the…