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The concept of the order parameter is extremely useful in physics. Here, I discuss extensions of this concept to cases when the order parameter is no longer a constant but fluctuates or oscillates in space and time. This allows one to…

Strongly Correlated Electrons · Physics 2019-12-20 Konstantin B. Efetov

Structure-property relationships in ordered materials have long been a core principle in materials design. However, the intentional introduction of disorder into materials provides structural flexibility and thus access to material…

We use the isoconfigurational (IC) ensemble to show the connection between emerging heterogeneities in the tetrahedral order parameter and the dynamic propensity in a mildly undercooled glass-forming liquid. We observe that spatially…

Soft Condensed Matter · Physics 2021-01-18 M Shajahan G Razul , Gurpreet S Matharoo , Balakrishnan Viswanathan

The confluence of quantum mechanics and complexity, which leads to the emergence of rich, exotic states of matter, motivates the extension of our concepts of quantum ordering. The twin concepts of spontaneously broken symmetry, described in…

Strongly Correlated Electrons · Physics 2019-01-15 Yashar Komijani , Anna Toth , Premala Chandra , Piers Coleman

In this work, we present the novel mathematical framework of latent dynamics models (LDMs) for reduced order modeling of parameterized nonlinear time-dependent PDEs. Our framework casts this latter task as a nonlinear dimensionality…

Numerical Analysis · Mathematics 2024-12-02 Nicola Farenga , Stefania Fresca , Simone Brivio , Andrea Manzoni

A large class of quantum phase transitions for quantum lattice systems are characterized by local order parameters. It is shown that local order parameters may be systematically constructed from tensor network representations of quantum…

Statistical Mechanics · Physics 2008-03-06 Huan-Qiang Zhou

Because of the isotropic and disordered nature of liquids, the anisotropy hidden in intermolecular interactions are often neglected. Accordingly, the order parameter describing a simple liquid has so far been believed to be only density. In…

Soft Condensed Matter · Physics 2008-02-03 Hajime Tanaka

Amorphous ice phases are key constituents of water's complex structural landscape. This study investigates the polyamorphic nature of water, focusing on the complexities within low-density amorphous ice (LDA), high-density amorphous ice…

Disordered Systems and Neural Networks · Physics 2023-12-25 Zoé Faure Beaulieu , Volker L. Deringer , Fausto Martelli

Rings comprising chemically bonded atoms are essential topological motifs for the structural ordering of network-forming materials. Quantification of such larger motifs beyond short-range pair correlation is essential for understanding the…

Materials Science · Physics 2023-11-15 Motoki Shiga , Akihiko Hirata , Yohei Onodera , Hirokazu Masai

The orientational correlation scheme introduced earlier for tetrahedral molecules is extended for being able to classify orientational correlations between pairs of high symmetry molecules. While in the original algorithm a given…

Chemical Physics · Physics 2021-08-13 László Temleitner

An idealized high entropy oxide is characterized by perfect chemical disorder and perfect positional order. In this work, we investigate the extent to which short-range order (SRO) and local structural distortions impede that idealized…

We introduce a multidimensional, neural-network approach to reveal and measure urban segregation phenomena, based on the Self-Organizing Map algorithm (SOM). The multidimensionality of SOM allows one to apprehend a large number of variables…

Physics and Society · Physics 2018-06-06 Madalina Olteanu , Aurélien Hazan , Marie Cottrell , Julien Randon-Furling

The efficient condition assessment of engineered systems requires the coupling of high fidelity models with data extracted from the state of the system `as-is'. In enabling this task, this paper implements a parametric Model Order Reduction…

Numerical Analysis · Mathematics 2024-07-25 Konstantinos Vlachas , Konstantinos Tatsis , Konstantinos Agathos , Adam R. Brink , Eleni Chatzi

We introduce the concept of {\it self-referential order} which provides a way to quantify structural organization in non crystalline materials. The key idea consists in the observation that, in a disordered system, where there is no ideal,…

Statistical Mechanics · Physics 2014-03-05 T. Aste , P. Butler , T. Di Matteo

Image ranking is to rank images based on some known ranked images. In this paper, we propose an improved linear ordinal distance metric learning approach based on the linear distance metric learning model. By decomposing the distance metric…

Machine Learning · Computer Science 2019-02-28 Panpan Yu , Qingna Li

This work concerns the analysis and design of distributed first-order optimization algorithms over time-varying graphs. The goal of such algorithms is to optimize a global function that is the average of local functions using only local…

Optimization and Control · Mathematics 2020-02-17 Akhil Sundararajan , Bryan Van Scoy , Laurent Lessard

We demonstrate that a weak disorder in atomic positions introduces spatially localized optical modes in a dense three-dimensional ensemble of immobile two-level atoms arranged in a diamond lattice and coupled by the electromagnetic field.…

Disordered Systems and Neural Networks · Physics 2020-10-21 S. E. Skipetrov

Finite element based simulation of phenomena governed by partial differential equations is a standard tool in many engineering workflows today. However, the simulation of complex geometries is computationally expensive. Many engineering…

Numerical Analysis · Mathematics 2019-08-07 Andreas Buhr

The primary distinction between solid and liquid phases is mechanical rigidity, with liquids having a disordered atomic structure that allows flow. While melting is a common phase transition, its microscopic mechanisms still remain unclear.…

Self-Organising Maps (SOM) are Artificial Neural Networks used in Pattern Recognition tasks. Their major advantage over other architectures is human readability of a model. However, they often gain poorer accuracy. Mostly used metric in SOM…

Machine Learning · Computer Science 2014-07-07 Piotr Płoński , Krzysztof Zaremba
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