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Feature modeling is a widely used formalism to characterize a set of products (also called configurations). As a manual elaboration is a long and arduous task, numerous techniques have been proposed to reverse engineer feature models from…

Software Engineering · Computer Science 2015-02-17 Guillaume Bécan , Razieh Behjati , Arnaud Gotlieb , Mathieu Acher

Highly dynamic computing environments, like ubiquitous and pervasive computing environments, require frequent adaptation of applications. This has to be done in a timely fashion, and the adaptation process must be as fast as possible and…

Software Engineering · Computer Science 2011-11-09 Nicolas Ferry , Jean-Yves Tigli , Stéphane Lavirotte , Gaëtan Rey , Michel Riveill

Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an…

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based planning approach for…

Complexity is an interdisciplinary concept which, first of all, addresses the question of how order emerges out of randomness. For many reasons matrices provide a very practical and powerful tool in approaching and quantifying the related…

Soft Condensed Matter · Physics 2008-12-18 S. Drozdz , J. Kwapien , J. Speth , M. Wojcik

Orbit-finite models of computation generalise the standard models of computation, to allow computation over infinite objects that are finite up to symmetries on atoms, denoted by $\mathbb{A}$. Set theory with atoms is used to reason about…

Logic · Mathematics 2025-12-03 Jake Masters

Machine learning has proven to be a valuable tool to approximate functions in high-dimensional spaces. Unfortunately, analysis of these models to extract the relevant physics is never as easy as applying machine learning to a large dataset…

Materials Science · Physics 2020-05-06 Conrad W. Rosenbrock , Eric R. Homer , Gábor Csányi , Gus L. W. Hart

The volume of data that will be produced by the next generation of astrophysical instruments represents a significant opportunity for making unplanned and unexpected discoveries. Conversely, finding unexpected objects or phenomena within…

Instrumentation and Methods for Astrophysics · Physics 2019-09-11 Gary Segal , David Parkinson , Ray P. Norris , Jesse Swan

Topological constraint theory has become an increasingly popular tool to predict the compositional dependence of glass properties or pinpoint promising compositions with tailored functionalities. This approach reduces complex disordered…

Disordered Systems and Neural Networks · Physics 2020-06-16 Mathieu Bauchy

Advanced engineering materials design involves the exploration of massive multidimensional feature spaces, the correlation of materials properties and the processing parameters derived from disparate sources. The search for alternative…

Artificial Intelligence · Computer Science 2013-01-03 Doreswamy , M. N. Vanajakshi

Atom probe tomography (APT) is a 3D analysis technique that offers unique chemical accuracy and sensitivity with sub-nanometer spatial resolution. Recently, there is an increasing interest in the application of APT to complex oxides…

An increasing variety of crystal structures has been observed in soft condensed matter over the past two decades, surpassing most expectations for the diversity of arrangements accessible through classical driving forces. Here, we survey…

Soft Condensed Matter · Physics 2022-03-01 Julia Dshemuchadse

Density Functional Theory (DFT) is one of the most used ab initio theoretical frameworks in materials science. It derives the ground state properties of a multi-atomic ensemble directly from the computation of its one-particle density \nr…

Computational Physics · Physics 2015-05-30 Edoardo Di Napoli , Stefan Blügel , Paolo Bientinesi

Mixed atomistic and continuum methods offer the possibility of carrying out simulations of material properties at both larger length scales and longer times than direct atomistic calculations. The quasi-continuum method links atomistic and…

Materials Science · Physics 2007-05-23 V. B. Shenoy , R. Miller , E. B. Tadmor , D. Rodney , R. Phillips , M. Ortiz

Characterizing complexity and criticality in quantum systems requires diagnostics that are both computationally tractable and physically insightful. We apply a measure of quantum state complexity for n-qubit systems, defined as the…

Quantum Physics · Physics 2026-02-10 Imre Varga

Criticality has been proposed as a mechanism for the emergence of complexity, life, and computation, as it exhibits a balance between robustness and adaptability. In classic models of complex systems where structure and dynamics are…

Statistical Mechanics · Physics 2026-02-04 Fernanda Sánchez-Puig , Octavio Zapata , Omar K. Pineda , Gerardo Iñiguez , Carlos Gershenson

Complex crystal structures are composed of multiple local environments, and how this type of order emerges spontaneously during crystal growth has yet to be fully understood. We study crystal growth across various structures and along…

Soft Condensed Matter · Physics 2024-06-03 Maya M. Martirossyan , Matthew Spellings , Hillary Pan , Julia Dshemuchadse

Diversity is a fundamental feature of ecosystems, even when the concept of ecosystem is extended to sociology or economics. Diversity can be intended as the count of different items, animals, or, more generally, interactions. There are two…

Physics and Society · Physics 2016-09-14 Andrea Tacchella , Riccardo Di Clemente , Andrea Gabrielli , Luciano Pietronero

Many standard structural quantities, such as order parameters and correlation functions, exist for common condensed matter systems, such as spherical and rod-like particles. However, these structural quantities are often insufficient for…

Soft Condensed Matter · Physics 2012-01-18 Aaron S. Keys , Christopher R. Iacovella , Sharon C. Glotzer

The best way to model, understand, and quantify the information contained in complex systems is an open question in physics, mathematics, and computer science. The uncertain relationship between entropy and complexity further complicates…

Machine Learning · Computer Science 2022-11-10 Stephen Casey
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