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We investigate the efficient learning of magnetic phases using artificial neural networks trained on synthetic data, combining computational simplicity with physics-informed strategies. Focusing on the diluted Ising model, which lacks an…

Strongly Correlated Electrons · Physics 2026-04-29 Agustin Medina , Marcelo Arlego , Carlos A. Lamas

The Ruddlesden-Popper ($A_{n+1}B_{n}\text{O}_{3n+1}$) compounds are a highly tunable class of materials whose functional properties can be dramatically impacted by their structural phase $n$. The negligible energetic differences associated…

Successful scientific applications of large-scale molecular dynamics often rely on automated methods for identifying the local crystalline structure of condensed phases. Many existing methods for structural identification, such as Common…

Materials Science · Physics 2016-05-24 Peter Mahler Larsen , Søren Schmidt , Jakob Schiøtz

As machine learning becomes increasingly important in engineering and science, it is inevitable that machine learning techniques will be applied to the investigation of materials, and in particular the structural phase transitions common in…

Materials Science · Physics 2021-03-30 Jiale Zhang , Danni Wei , Feng Zhang , Xi Chen , Dawei Wang

A review of the present state of investigations of the pseudospin-electron model (PEM), which is used in the theory of strongly correlated electron systems, is given. The model is used to describe the systems with the locally anharmonic…

Strongly Correlated Electrons · Physics 2016-11-23 Ihor Stasyuk

For atoms and crystals with an ideal symmetry, the optical selection rules for electronic transitions are well covered in physics textbooks. However, in studies of material systems one often encounters systems with a weakly distorted…

Atomic Physics · Physics 2018-10-16 G. J. J. Lof , C. H. van der Wal , R. W. A. Havenith

A general system of particles (of one or several species) on a one dimensional lattice with boundaries is considered. Two general behaviors of such systems are investigated. The stationary behavior of the system, and the dominant way of the…

Statistical Mechanics · Physics 2015-06-24 Mohammad Khorrami , Amir Aghamohammadi

We use theory and first-principles calculations to explore mechanisms for control of the translational and point group symmetries of crystals in ultrafast optical experiments. We focus in particular on mechanisms that exploit anharmonic…

Materials Science · Physics 2025-04-28 Guru Khalsa , Jeffrey Z. Kaaret , Nicole A. Benedek

Neural network based machine learning is emerging as a powerful tool for obtaining phase diagrams when traditional regression schemes using local equilibrium order parameters are not available, as in many-body localized or topological…

Disordered Systems and Neural Networks · Physics 2018-06-27 Jordan Venderley , Vedika Khemani , Eun-Ah Kim

We apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lattice spin models: the Ising, square ice, XY, and…

Statistical Mechanics · Physics 2021-10-04 Alex Cole , Gregory J. Loges , Gary Shiu

Polymer-derived ceramics combine the thermal stability of ceramics with the versatile properties of carbon domains, but modeling their atomic-scale evolution during processing remains elusive due to the limitations of traditional…

In the present work, we discuss how the functional form of thermodynamic observables can be deduced from the geometric properties of subsets of phase space. The geometric quantities taken into account are mainly extrinsic curvatures of the…

Statistical Mechanics · Physics 2020-05-01 Ghofrane Bel-Hadj-Aissa , Matteo Gori , Vittorio Penna , Giulio Pettini , Roberto Franzosi

We analyze the energy spectrum and eigenstates of cold atoms in a tilted brick-wall optical lattice. When the tilt is applied, the system exhibits a sequence of topological phase transitions reflected in an abrupt change of the eigenstates.…

Quantum Gases · Physics 2018-07-11 Andrey R. Kolovsky

Electron energy loss spectroscopy is consolidating as a powerful tool to explore electronic (as well as vibrational) excitations of matter, including molecules. Performed in a scanning transmission electron microscope, this technique is…

Chemical Physics · Physics 2021-03-05 Ciro A. Guido , Enzo Rotunno , Matteo Zanfrognini , Stefano Corni , Vincenzo Grillo

Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is…

Quantum Physics · Physics 2020-12-08 Alexander Lidiak , Zhexuan Gong

We analyse biased ensembles of trajectories for a two-dimensional system of particles, evolving by Langevin dynamics in a channel geometry. This bias controls the degree of particle clustering. On biasing to large clustering, we observe a…

Statistical Mechanics · Physics 2022-09-05 Jakub Dolezal , Robert L. Jack

Scanning transmission electron microscopy is a common tool used to study the atomic structure of materials. It is an inherently multimodal tool allowing for the simultaneous acquisition of multiple information channels. Despite its…

Multi-technique high resolution X-ray mapping enhanced by the recent advent of 4th generation synchrotron facilities can produce colossal datasets, challenging traditional analysis methods. Such difficulty is clearly materialized when…

A local criterion of topological phase transitions is established based on the Morse theory: a topological phase transition occurs when the count of Morse critical points of the order function changes. The locations in space where this…

Statistical Mechanics · Physics 2023-09-22 Yangfan Hu

Phase transitions are the macroscopic manifestation of microscopic processes that drive a system towards a new state. The detailed evolution of these processes, particularly in abrupt phase transitions, are currently not fully understood.…

Physics and Society · Physics 2026-01-21 Leyang Xue , Shengling Gao , Bnaya Gross , Orr Levy , Daqing Li , Zengru Di , Lazaros K. Gallos , Shlomo Havlin