accurate computations
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Atoms ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Stephan Fritzsche

Open f-shell elements still constitute a great challenge for atomic theory owing to their (very) rich fine-structure and strong correlations among the valence-shell electrons. For these medium and heavy elements, many atomic properties are sensitive to the correlated motion of electrons and, hence, require large-scale computations in order to deal consistently with all relativistic, correlation and rearrangement contributions to the electron density. Often, different concepts and notations need to be combined for just classifying the low-lying level structure of these elements. With Jac, the Jena Atomic Calculator, we here provide a toolbox that helps to explore and deal with such elements with open d- and f-shell structures. Based on Dirac’s equation, Jac is suitable for almost all atoms and ions across the periodic table. As an example, we demonstrate how reasonably accurate computations can be performed for the low-lying level structure, transition probabilities and lifetimes for Th2+ ions with a 5f6d ground configuration. Other, and more complex, shell structures are supported as well, though often for a trade-off between the size and accuracy of the computations. Owing to its simple use, however, Jac supports both quick estimates and detailed case studies on open d- or f-shell elements.


Author(s):  
Yi-Han Wang ◽  
Nathan W C Leigh ◽  
Bin Liu ◽  
Rosalba Perna

Abstract We present the open source few-body gravity integration toolkit SpaceHub. SpaceHub offers a variety of algorithmic methods, including the unique algorithms AR-Radau, AR-Sym6, AR-ABITS and AR-chain+ which we show out-perform other methods in the literature and allow for fast, precise and accurate computations to deal with few-body problems ranging from interacting black holes to planetary dynamics. We show that AR-Sym6 and AR-chain+, with algorithmic regularization, chain algorithm, active round-off error compensation and a symplectic kernel implementation, are the fastest and most accurate algorithms to treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. AR-Radau, the first regularized Radau integrator with round off error control down to 64 bits floating point machine precision, has the ability to handle extremely eccentric orbits and close approaches in long-term integrations. AR-ABITS, a bit efficient arbitrary precision method, achieves any precision with the least CPU cost compared to other open source arbitrary precision few-body codes. With the implementation of deep numerical and code optimization, these new algorithms in SpaceHub prove superior to other popular high precision few-body codes in terms of performance, accuracy and speed.


CALCOLO ◽  
2021 ◽  
Vol 58 (1) ◽  
Author(s):  
E. Mainar ◽  
J. M. Peña ◽  
B. Rubio

Author(s):  
Verdiana Iorio ◽  
Giorgio Bellotti ◽  
Claudia Cecioni ◽  
Stephan Grilli

Submarine landslides can pose serious tsunami hazard to coastal communities, occurring frequently near the coast itself. The properties of the tsunami and the consequent inundation depend on many factors, such as the geometry, the rheology and the kinematic of the landslide and the local bathymetry. However, when evaluating the risk related to landslide tsunamis, it is very difficult to accurately predict all of the above mentioned parameters. It is therefore useful to carry out many simulations of tsunami generation and propagation, with reference to different landslide scenarios, in order to deal with such uncertainties (see for example the probabilistic approach by Grilli et al. 2009). Accurate computations of landslide tsunami generation, propagation, and inundation, however, is computationally expensive, thus limiting the possible maximum number of scenarios. To partially overcome this difficulty, in the present research, a numerical model is proposed that can efficiently compute a large number of tsunami simulations triggered by different landslides. The main goal is to provide a numerical tool that can be used in a Monte Carlo approach framework. Following the study by Ward (2001), we propose a methodology taking advantage of the linear superposition of elementary tsunami solutions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/uYOvdsutmBw


Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6282
Author(s):  
Corentin Friedrich ◽  
Sébastien Bourguignon ◽  
Jérôme Idier ◽  
Yves Goussard

This paper considers the microwave imaging reconstruction problem, based on additive penalization and gradient-based optimization. Each evaluation of the cost function and of its gradient requires the resolution of as many high-dimensional linear systems as the number of incident fields, which represents a large amount of computations. Since all such systems involve the same matrix, we propose a block inversion strategy, based on the block-biconjugate gradient stabilized (BiCGStab) algorithm, with efficient implementations specific to the microwave imaging context. Numerical experiments performed on synthetic data and on real measurements show that savings in computing time can reach a factor of two compared to the standard, sequential, BiCGStab implementation. Improvements brought by the block approach are even more important for the most difficult reconstruction problems, that is, with high-frequency illuminations and/or highly contrasted objects. The proposed reconstruction strategy is shown to achieve satisfactory estimates for objects of the Fresnel database, even on the most contrasted ones.


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