Results 81 to 90 of about 1,886,623 (400)

Nematicity with a twist: Rotational symmetry breaking in a moiré superlattice [PDF]

open access: yesScience Advances, 2019
Twisted 2D materials realize a unique electronic nematic state, quite different from its counterpart in bulk quantum materials. Motivated by recent reports of nematic order in twisted bilayer graphene (TBG), we investigate the impact of the triangular ...
R. Fernandes, J. Venderbos
semanticscholar   +1 more source

R Symmetry Breaking Versus Supersymmetry Breaking

open access: yes, 1993
We point out a connection between R symmetry and \susy\ breaking. We show that the existence of an R symmetry is a necessary condition for \susy\ breaking and a spontaneously broken R symmetry is a sufficient condition provided two conditions are ...
Abbott   +42 more
core   +1 more source

Analysis of Temperature and Stress Distribution on the Bond Properties of Hybrid Tailored Formed Components

open access: yesAdvanced Engineering Materials, EarlyView.
Hybrid materials enable high‐performance components but are challenging to process. This study explores an inductive heating concept with spray cooling for steel–aluminum specimens in a two‐step process including friction welding and cup backward extrusion.
Armin Piwek   +7 more
wiley   +1 more source

Effective field theory for spacetime symmetry breaking [PDF]

open access: yesPhys. Rev. D 92, 045020 (2015), 2014
We discuss the effective field theory for spacetime symmetry breaking from the local symmetry point of view. By gauging spacetime symmetries, the identification of Nambu-Goldstone (NG) fields and the construction of the effective action are performed based on the breaking pattern of diffeomorphism, local Lorentz, and (an)isotropic Weyl symmetries as ...
arxiv   +1 more source

Time-reversal symmetry breaking type-II Weyl state in YbMnBi2

open access: yesNature Communications, 2019
Spectroscopic detection of Dirac and Weyl fermions in real materials is vital for both, promising applications and fundamental bridge between high-energy and condensed-matter physics.
S. Borisenko   +14 more
semanticscholar   +1 more source

Breaking Anti-PT Symmetry by Spinning a Resonator.

open access: yesNano letters (Print), 2020
Non-Hermitian systems, with symmetric or antisymmetric Hamiltonians under the parity-time (PT) operations, can have entirely real or imaginary eigenvalues.
Huilai Zhang   +6 more
semanticscholar   +1 more source

Nature of Symmetry Breaking at the Excitonic Insulator Transition: Ta_{2}NiSe_{5}. [PDF]

open access: yesPhysical Review Letters, 2019
Ta_{2}NiSe_{5} is one of the most promising materials for hosting an excitonic insulator ground state. While a number of experimental observations have been interpreted in this way, the precise nature of the symmetry breaking occurring in Ta_{2}NiSe_{5},
G. Mazza   +7 more
semanticscholar   +1 more source

Breaking Value Symmetry [PDF]

open access: yes, 2007
Symmetry is an important factor in solving many constraint satisfaction problems. One common type of symmetry is when we have symmetric values. In a recent series of papers, we have studied methods to break value symmetries. Our results identify computational limits on eliminating value symmetry. For instance, we prove that pruning all symmetric values
openaire   +4 more sources

Symmetry, Symmetry Breaking and Topology [PDF]

open access: yesSymmetry, 2010
The ground state of a system with symmetry can be described by a group G. This symmetry group G can be discrete or continuous. Thus for a crystal G is a finite group while for the vacuum state of a grand unified theory G is a continuous Lie group. The ground state symmetry described by G can change spontaneously from G to one of its subgroups H as the ...
openaire   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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