Related papers: Mass generation in graphs
Constrained propagation of massless fields is ubiquitous in physical systems, arising from boundaries, material structure, or other restrictions on admissible modes. This paper shows that such constraints generically induce mass-like terms…
We investigate the creation of massless quasiparticle pairs from the vacuum state in graphene by the space homogeneous time-dependent electric field. For this purpose the formalism of (2+1)-dimensional quantum electrodynamics is applied to…
In this paper we describe the emergence of scale-free degree distributions from statistical mechanics principles. We define an energy associated to a degree sequence as the logarithm of the number of indistinguishable simple networks it is…
Recent work on the structure of social networks and the internet has focussed attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in…
We give a constructive method for realizing an arbitrary directed graph (with no one-cycles) as a heteroclinic or an excitable dynamic network in the phase space of a system of coupled cells of two types. In each case, the system is…
Dynamical generation of 4d gauge theories and gravity at low energy from the 3d ones at high energy is studied, based on the fermion condensation mechanism recently proposed by Arkani-Hamed, Cohen and Georgi. For gravity, 4d Einstein…
Quantum entanglement plays an important role in quantum information processes, such as quantum computation and quantum communication. Experiments in laboratories are unquestionably crucial to increase our understanding of quantum systems…
The self-gravitating systems are formed by particles interacting through gravity. They describe structure formation in the universe. As a consequence of the long range interaction of gravity, they are inhomogeneous even at thermal…
Recent experiments (R. A. Baragiola and C. A. Dukes, Phys. Rev. Lett. {\bf 76}, 2547 (1996)) with slow ions incident at grazing angle on metal surfaces have shown that bulk plasmons are excited under conditions where the ions do not…
The graph structure is a commonly used data storage mode, and it turns out that the low-dimensional embedded representation of nodes in the graph is extremely useful in various typical tasks, such as node classification, link prediction ,…
We consider possible mechanical masses that could appear in supersymmetry, other than by direct Higgs coupling to fermions and we speculate that the existence of such a type of mass would allow one to have the Higgs mass of the $u$ quark…
We show how a gradient in the motility properties of non-interacting point-like active particles can cause a pressure gradient that pushes a large inert object. We calculate the force on an object inside a system of active particles with…
Graph states possess significant practical value in measurement-based quantum computation, with complete graph states that exhibit exceptional performance in quantum metrology. In this work, we introduce a method for generating…
A Higgs mechanism for Abelian theories over non-trivial background flat connections is proposed. It is found that the mass generated for the spin 1 excitation is the same as the one obtained from the standard Higgs mechanism over trivial…
Hypergraphs effectively model higher-order relationships in natural phenomena, capturing complex interactions beyond pairwise connections. We introduce a novel hypergraph message passing framework inspired by interacting particle systems,…
We investigate the equidistribution of the eigenfunctions on quantum graphs in the high-energy limit. Our main result is an estimate of the deviations from equidistribution for large well-connected graphs. We use an exact field-theoretic…
Highly energetic ions traversing a two-dimensional material such as graphene produce strong electronic excitations. Electrons excited to energy states above the work function can give rise to secondary electron emission, reducing the amount…
We introduce the Graph Mixture Density Networks, a new family of machine learning models that can fit multimodal output distributions conditioned on graphs of arbitrary topology. By combining ideas from mixture models and graph…
We study at the microscopic level the dynamics of a one-dimensional gravitationally interacting sticky gas. Initially, N identical particles of mass m with uncorrelated, randomly distributed velocities fill homogeneously a finite region of…
We study computational aspects of repulsive Gibbs point processes, which are probabilistic models of interacting particles in a finite-volume region of space. We introduce an approach for reducing a Gibbs point process to the hard-core…