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Developing a theoretical framework for conducting electronic fluids qualitatively distinct from those described by Landau's Fermi-liquid theory is of central importance to many outstanding problems in condensed matter physics. One such…

We present the first correlated-electron theory of metamagnetism in strongly anisotropic antiferromagnets. Quantum-Monte-Carlo techniques are used to calculate the field vs. temperature phase diagram of the infinite-dimensional Hubbard…

Condensed Matter · Physics 2015-06-25 K. Held , M. Ulmke , D. Vollhardt

Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated electronic systems often reveal complex pattern formation on multiple length scales. By studying the universal…

Strongly Correlated Electrons · Physics 2019-04-03 L. Burzawa , Shuo Liu , E. W. Carlson

In many materials, ordered phases and their order parameters are easily characterized by standard experimental methods. "Hidden order" refers to a phase transition in which an ordered state emerges without such an easily detectable order…

Heavy fermion materials are compounds in which localized $f$-orbitals hybridize with delocalized $d$ ones, leading to quasiparticles with large renormalized masses. The presence of strongly correlated $f$-electrons at the Fermi level may…

Strongly Correlated Electrons · Physics 2023-03-22 Wiliam S. Oliveira , Thereza Paiva , Richard T. Scalettar , Natanael C. Costa

In strongly correlated materials, interacting electrons are entangled and form collective quantum states, resulting in rich low-temperature phase diagrams. Notable examples include cuprate superconductors, in which superconductivity emerges…

The detection of phase transitions is a fundamental challenge in condensed matter physics, traditionally addressed through analytical methods and direct numerical simulations. In recent years, machine learning techniques have emerged as…

Disordered Systems and Neural Networks · Physics 2025-01-14 Djenabou Bayo , Burak Çivitcioğlu , Joseph J Webb , Andreas Honecker , Rudolf A. Römer

Unconventional strongly correlated phases of the repulsive Fermi-Hubbard model, which could be emulated by ultracold vapors loaded in optical lattices, are investigated by means of energy minimizations with quantum number projection before…

Quantum Gases · Physics 2015-10-20 A. Leprévost , O. Juillet , R. Frésard

The integration of artificial intelligence (AI) into fundamental science has opened new possibilities to address long-standing scientific challenges rooted in mathematical limitations. For example, topological invariants are used to…

Mesoscale and Nanoscale Physics · Physics 2025-11-18 Yang Long , Haoran Xue , Baile Zhang

Anomalous metals are observed in numerous experiments on disordered two-dimensional systems proximate to superconductivity. A characteristic feature of an anomalous metal is that its low temperature conductivity has a weakly temperature…

Strongly Correlated Electrons · Physics 2021-03-31 Chenyuan Li , Darshan G. Joshi , Subir Sachdev

The theory of correlated electron systems is formulated in a form which allows to use as a reference point an ab initio band structure theory (AIBST). The theory is constructed in two steps. As a first step the total Hamiltonian is…

Strongly Correlated Electrons · Physics 2007-05-23 Igor Sandalov , Borje Johansson , Olle Eriksson

The magnetic phases induced by the interplay between disorder acting only on particles with a given spin projection ("spin-dependent disorder") and a local repulsive interaction is explored. To this end the magnetic ground state phase…

Strongly Correlated Electrons · Physics 2024-04-26 J. Skolimowski , D. Vollhardt , K. Byczuk

We describe two dimensional models with a metallic Fermi surface which display quantum phase transitions controlled by strongly interacting critical field theories below their upper critical dimension. The primary examples involve…

Strongly Correlated Electrons · Physics 2007-05-23 Subir Sachdev , Takao Morinari

The attractive Fermi-Hubbard model is the simplest theoretical model for studying pairing and superconductivity of fermions on a lattice. Although its s-wave pairing symmetry excludes it as a microscopic model for high-temperature…

Originating from image recognition, methods of machine learning allow for effective feature extraction and dimensionality reduction in multidimensional datasets, thereby providing an extraordinary tool to deal with classical and quantum…

Statistical Mechanics · Physics 2019-01-16 Albert A. Shirinyan , Valerii K. Kozin , Johan Hellsvik , Manuel Pereiro , Olle Eriksson , Dmitry Yudin

Drawing the quantum phase diagram of a many-body system in the parameter space of its Hamiltonian can be seen as a learning problem, which implies labelling the corresponding ground states according to some classification criterium that…

Quantum Physics · Physics 2025-10-17 Mehran Khosrojerdi , Alessandro Cuccoli , Paola Verrucchi , Leonardo Banchi

The application of state-of-the-art machine learning techniques to statistical physic problems has seen a surge of interest for their ability to discriminate phases of matter by extracting essential features in the many-body wavefunction or…

Strongly Correlated Electrons · Physics 2017-07-04 Peter Broecker , Fakher F. Assaad , Simon Trebst

Nontrivial symmetry of order parameters is crucial in some of the most interesting quantum many-body states of ultracold atoms and condensed matter systems. Examples in cold atoms include p-wave Feshbach molecules and d-wave paired states…

Quantum Gases · Physics 2011-05-02 Takuya Kitagawa , Alain Aspect , Marcus Greiner , Eugene Demler

Two-dimensional metallic altermagnets are rare, and no correlated 2D material has been established to host large nonrelativistic spin splitting. Here we show that spontaneous orbital order, driven by electronic correlations and Fermi…

Mesoscale and Nanoscale Physics · Physics 2026-03-27 Nirmalya Jana , Atasi Chakraborty , Anamitra Mukherjee , Amit Agarwal

Artificial intelligence (AI) has been increasingly applied in scientific activities for decades; however, it is still far from an insightful and trustworthy collaborator in the scientific process. Most existing AI methods are either too…

Artificial Intelligence · Computer Science 2022-02-08 Morad Behandish , John Maxwell , Johan de Kleer