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We show that the quark (not nucleon) based chiral linear $\sigma$ model which receives strong support as a mean field theory for the strong interactions can actually be made asymptotically free by coupling to gluons. It has the further…

High Energy Physics - Phenomenology · Physics 2015-06-25 Vikram Soni

We describe an example of a structurally stable heteroclinic network for which nearby orbits exhibit irregular but sustained switching between the various sub-cycles in the network. The mechanism for switching is the presence of spiralling…

Chaotic Dynamics · Physics 2019-10-03 Vivien Kirk , Emily Lane , Claire M. Postlethwaite , Alastair M. Rucklidge , Mary Silber

Recently, a large class of 3d $\mathcal{N} = 2$ gauge theories with mixed Chern-Simons levels, corresponding to plumbing 3-manifolds, has been identified. In this paper we generalize these theories by including in their content chiral…

High Energy Physics - Theory · Physics 2023-08-25 Shi Cheng , Piotr Sułkowski

A formulation of abelian and non-abelian chiral gauge theories is presented together with arguments for the unitarity and renormalisability in four dimensions. IASSNS-HEP-94/70, UM-P-94/96, and RCHEP-94/26.

High Energy Physics - Theory · Physics 2007-05-23 Tien D Kieu

In this work we consider quantum cascade networks in which quantum systems are connected through unidirectional channels that can mutually interact giving rise to interference effects. In particular we show how to compute master equations…

Quantum Physics · Physics 2017-05-16 Stefano Cusumano , Andrea Mari , Vittorio Giovannetti

In this paper we present a new strategy to model the subgrid-scale scalar flux in a three-dimensional turbulent incompressible flow using physics-informed neural networks (NNs). When trained from direct numerical simulation (DNS) data,…

Fluid Dynamics · Physics 2021-03-03 Hugo Frezat , Guillaume Balarac , Julien Le Sommer , Ronan Fablet , Redouane Lguensat

Constructing systems that exhibit time-scales much longer than those of the underlying components, as well as emergent dynamical and collective behavior, is a key goal in fields such as synthetic biology and materials self-assembly.…

Statistical Mechanics · Physics 2021-07-22 Evelyn Tang , Jaime Agudo-Canalejo , Ramin Golestanian

We present a novel chiral sensing platform that combines a one-dimensional photonic crystal design with a birefringent surface defect. The platform sustains simultaneous transverse electric and transverse magnetic surface modes, which are…

Living systems have evolved to efficiently consume available energy sources using an elaborate circuitry of chemical reactions which, puzzlingly, bear a strict restriction to asymmetric chiral configurations. While autocatalysis is known to…

Chemical Physics · Physics 2022-05-25 William D. Piñeros , Tsvi Tlusty

We present a comprehensive overview of chirality and its optical manifestation in plasmonic nanosystems and nanostructures. We discuss top-down fabricated structures that range from solid metallic nanostructures to groupings of metallic…

Lattice fermions have well-known difficulties with chiral symmetry. To evade them it is possible to couple continuum fermions to lattice gauge fields, by introducing an interpolation of the latter. Following this line of thinking, this…

High Energy Physics - Lattice · Physics 2016-09-01 Andreas S. Kronfeld

Chiral plasmonic nanostructures are rapidly emerging as ideal substrates for enantioselective sensing, chiral near-field engineering, and plasmon-assisted catalysis, owing to their exceptional sensitivity to structural handedness. However,…

Mesoscale and Nanoscale Physics · Physics 2026-03-30 Vasil Saroka , Lorenzo Cupellini , Nicolò Maccaferri , Alessandro Fortunelli , Tommaso Giovannini

Electrons in graphene follow unconventional trajectories at PN junctions, driven by their pseudospintronic degree of freedom. Significant is the prominent angular dependence of transmission, capturing the chiral nature of the electrons and…

Mesoscale and Nanoscale Physics · Physics 2013-05-30 Redwan N. Sajjad , S. Sutar , J. U. Lee , Avik W. Ghosh

The solution of potential-driven steady-state flow in large networks is required in various engineering applications, such as transport of natural gas or water through pipeline networks. The resultant system of nonlinear equations depends…

Computational Physics · Physics 2026-03-20 Shriram Srinivasan , Kaarthik Sundar

Heteroclinic connections are trajectories that link invariant sets for an autonomous dynamical flow: these connections can robustly form networks between equilibria, for systems with flow-invariant spaces. In this paper we examine the…

Dynamical Systems · Mathematics 2019-09-04 Peter Ashwin , Sofia Castro , Alexander Lohse

The irreducible complexity of natural phenomena has led Graph Neural Networks to be employed as a standard model to perform representation learning tasks on graph-structured data. While their capacity to capture local and global patterns is…

Machine Learning · Computer Science 2024-02-13 Lorenzo Giusti

The chiral anomaly is based on a non-conserved chiral charge and can happen in Dirac fermion systems under the influence of external electromagnetic fields. In this case, the spectral flow leads to a transfer of right- to left-moving…

Mesoscale and Nanoscale Physics · Physics 2017-01-04 Christoph Fleckenstein , Niccolò Traverso Ziani , Björn Trauzettel

A multigrid scheme is proposed for the pressure equation of the incompressible unsteady fluid flow equations, allowing efficient implementation on clusters of modern CPUs, many integrated core devices (MICs), and graphics processing units…

Numerical Analysis · Mathematics 2014-08-19 György Tegze , Gyula I. Tóth

The convergence rate of a multigrid method depends on the properties of the smoother and the so-called grid transfer operator. In this paper we define and analyze new grid transfer operators with a generic cutting size which are applicable…

Numerical Analysis · Mathematics 2016-08-12 Maria Charina , Marco Donatelli , Lucia Romani , Valentina Turati

Understanding the structural complexity and predictability of complex networks is a central challenge in network science. Although recent studies have revealed a relationship between compression-based entropy and link prediction…

Social and Information Networks · Computer Science 2025-10-14 Sebastián Brzovic , Cristóbal Rojas , Andrés Abeliuk
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