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Related papers: How to quantify energy landscapes of solids

200 papers

A variety of methods are developed for characterising the free energy landscapes of continuum, Landau-type free energy models. Using morphologies of lipid vesicles and a multistable liquid crystal device as examples, I show that the methods…

Soft Condensed Matter · Physics 2015-06-23 Halim Kusumaatmaja

We investigate the multi-valley energy landscape of a 3-D on-lattice network model for covalent glasses, numerically determining the shape of the valleys, the local density of states, the density of minima and the local connectivity. We…

Statistical Mechanics · Physics 2009-10-31 J. Christian Schoen , P. Sibani

We study signatures of the energy landscape's evolution through the crystal-to-glass transition by compressing 2D finite aggregates of oil droplets. Droplets of two distinct sizes are used to compose small aggregates in an aqueous…

Ground state structures found in nature are in many cases of high symmetry. But structure prediction methods typically render only a small fraction of high symmetry structures. Especially for large crystalline unit cells there are many low…

Computational Physics · Physics 2022-09-13 Hannes Huber , Martin Sommer , Moritz Gubler , Stefan Goedecker

We propose a way to analyze the landscape geometry explored by a glassy system after a quench solely based on time series of energy values recorded during a simulation. Entry and exit times for landscape `valleys' are defined operationally…

Statistical Mechanics · Physics 2007-05-23 Paolo Sibani , Jesper Dall

We find the minimum and the maximum value for the local energy of an arbitrary finite bipartite system for any given amount of entanglement, also identifying families of states reaching these bounds and sharing formal analogies with thermal…

Quantum Physics · Physics 2023-09-12 Nicolò Piccione , Benedetto Militello , Anna Napoli , Bruno Bellomo

We present a statistical method for complex energy landscape exploration which provides information on the metastable states--or valleys--actually explored by an unperturbed aging process following a quench. Energy fluctuations of record…

Statistical Mechanics · Physics 2009-11-10 Jesper Dall , Paolo Sibani

Defining the energy function as the negative logarithm of the density, we explore the energy landscape of a distribution via the tree of sublevel sets of its energy. This tree represents the hierarchy among the connected components of the…

Applications · Statistics 2009-01-27 Qing Zhou , Wing Hung Wong

Properties of the free energy landscape in phase space of a dense hard sphere system characterized by a discretized free energy functional of the Ramakrishnan-Yussouff form are investigated numerically. A considerable number of glassy local…

Disordered Systems and Neural Networks · Physics 2009-10-31 Chandan Dasgupta , Oriol T. Valls

Disconnectivity graphs are used to visualize the minima and the lowest energy barriers between the minima of complex systems. They give an easy and intuitive understanding of the underlying energy landscape and, as such, are excellent tools…

Disordered Systems and Neural Networks · Physics 2020-04-28 Katja Biswas , Helmut G. Katzgraber

In a recent paper [J. Math. Phys. 47 082303 (2006)], Quantum Energy Inequalities were used to place simple geometrical bounds on the energy densities of quantum fields in Minkowskian spacetime regions. Here, we refine this analysis for…

Mathematical Physics · Physics 2008-11-26 Simon P. Eveson , Christopher J. Fewster

The topography of the free energy landscape in phase space of a dense hard sphere system characterized by a discretized free energy functional of the Ramakrishnan-Yussouff form is investigated numerically using a ``microcanonical'' Monte…

Disordered Systems and Neural Networks · Physics 2007-05-23 Chandan Dasgupta , Oriol T. Valls

It is difficult to relate the properties of liquids and glasses directly to their structure because of complexity in the structure which defies precise definition. The potential energy landscape (PEL) approach is a very insightful way to…

Soft Condensed Matter · Physics 2014-11-27 Takuya Iwashita , Takeshi Egami

The low-temperature driven or thermally activated motion of several condensed matter systems is often modeled by the dynamics of interfaces (co-dimension-1 elastic manifolds) subject to a random potential. Two characteristic quantitative…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Alan Middleton

We analyse the relationship between dynamics and configuration space structure of Ising spin glass systems. The exact knowledge of the structure of the low--energy landscape is used to study the relaxation of the system by random walk in…

Disordered Systems and Neural Networks · Physics 2009-11-07 S. Kobe , J. Krawczyk

A phenomenological free energy model is proposed to describe the behavior of smectic liquid crystals, an intermediate phase that exhibits orientational order and layering at the molecular scale. Advantageous properties render the functional…

Soft Condensed Matter · Physics 2021-05-05 Jingmin Xia , Scott MacLachlan , Timothy J. Atherton , Patrick E. Farrell

Topological phases of matter$\unicode{x2013}$comprising both insulators and semimetals$\unicode{x2013}$offer great potential for quantum applications, but identifying new candidates remains challenging due to expensive first-principles…

Materials Science · Physics 2026-04-08 Xinyu Xu , Arif Ullah , Ming Yang

There is a growing belief that the mode coupling theory is the proper microscopic theory for the dynamics of the undercooled liquid above a critical temperature T_c. In addition, there is some evidence that the system leaves the…

Disordered Systems and Neural Networks · Physics 2009-11-07 U. Buchenau

It is possible to formulate the thermodynamics of a glass forming system in terms of the properties of inherent structures, which correspond to the minima of the potential energy and build up the potential energy landscape in the…

Soft Condensed Matter · Physics 2009-10-31 Stephan Buechner , Andreas Heuer

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

Materials Science · Physics 2026-04-21 V. Torlao , E. A. Fajardo