Hasil untuk "Computer software"

Stefan Maintz, Volker L. Deringer, A. Tchougréeff et al.

The computer program LOBSTER (Local Orbital Basis Suite Towards Electronic‐Structure Reconstruction) enables chemical‐bonding analysis based on periodic plane‐wave (PAW) density‐functional theory (DFT) output and is applicable to a wide range of first‐principles simulations in solid‐state and materials chemistry. LOBSTER incorporates analytic projection routines described previously in this very journal [J. Comput. Chem. 2013, 34, 2557] and offers improved functionality. It calculates, among others, atom‐projected densities of states (pDOS), projected crystal orbital Hamilton population (pCOHP) curves, and the recently introduced bond‐weighted distribution function (BWDF). The software is offered free‐of‐charge for non‐commercial research. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

S. Gates-Rector, T. Blanton

The ICDD's Powder Diffraction File™ (PDF®) is a database of inorganic and organic diffraction data used for phase identification and materials characterization by powder diffraction. The PDF has been available for over 75 years and finds application in X-ray, synchrotron, electron, and neutron diffraction analyses. With entries based on powder and single crystal data, the PDF is the only crystallographic database where every entry is editorially reviewed and marked with a quality mark that alerts the user to the reliability/quality of the submitted data. The editorial processes of ICDD's quality management system are unique in that they are ISO 9001:2015 certified. Initially offered as text on paper cards and books, the PDF evolved to a computer-readable database in the 1960s and today is both computer and web accessible. With data mining and phase identification software available in PDF products, and the databases’ compatibility with vendor (third party) software, the 1 000 000+ published PDF entries serve a wide range of disciplines covering academic, industrial, and government laboratories. Details describing the content of database entries are presented to enhance the use of the PDF.

N. Feamster, J. Rexford, E. Zegura

S. Maas, Benjamin J. Ellis, Gerard A. Ateshian et al.

B. Chapman, Gabriele Jost, R. V. D. Pas

R. Hegger, H. Kantz, T. Schreiber

We describe the implementation of methods of nonlinear time series analysis which are based on the paradigm of deterministic chaos. A variety of algorithms for data representation, prediction, noise reduction, dimension and Lyapunov estimation, and nonlinearity testing are discussed with particular emphasis on issues of implementation and choice of parameters. Computer programs that implement the resulting strategies are publicly available as the TISEAN software package. The use of each algorithm will be illustrated with a typical application. As to the theoretical background, we will essentially give pointers to the literature. (c) 1999 American Institute of Physics.

T. Welch

C. Coffman

T. S. Parker, L. Chua

L. Constantine

E. Chikofsky, J. Cross

M. Speicher, S. G. Ballard, D. Ward

N. Larsen, Karla M. Fogel

M. Wooldridge

T. Roska, L. Chua

W. Schroeder, Kenneth M. Martin

M. Lam

K. Ashelford, N. Chuzhanova, J. Fry et al.

Yury Lysogorskiy, Anton Bochkarev, Ralf Drautz

Abstract Foundational machine learning interatomic potentials that can accurately and efficiently model a vast range of materials are critical for accelerating atomistic discovery. We introduce universal potentials based on the graph atomic cluster expansion (GRACE) framework, trained on several of the largest available materials datasets. Through comprehensive benchmarks, we demonstrate that the GRACE models establish a new Pareto front for accuracy versus efficiency among foundational interatomic potentials. We further showcase their exceptional versatility by adapting them to specialized tasks and simpler architectures via fine-tuning and knowledge distillation, achieving high accuracy while preventing catastrophic forgetting. This work establishes GRACE as a robust and adaptable foundation for the next generation of atomistic modeling, enabling high-fidelity simulations across the periodic table.

Ana Díaz-Muñoz, José A. Cruz-Lemus, Moisés Rodríguez et al.

The analyzability of hybrid software, which integrates both classical and quantum components, is a key factor in ensuring its maintainability and industrial adoption. This article presents the empirical validation, through a family of experiments, of the quantum component of a previously proposed hybrid software analyzability model based on the ISO/IEC 25010 standard. The experimental series consists of four studies involving participants with diverse profiles in both academic and professional settings. In these experiments, the model's ability to effectively measure the analyzability of quantum algorithms is assessed, and the relationship between the analyzability levels computed by the model and the participant's perceptions of the complexity of these algorithms is examined. The results indicate that the proposed model effectively distinguishes between quantum software components with varying levels of analyzability and aligns with human perception, reinforcing its validity in quantum computing.