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Quantum networks are important for quantum communication, enabling tasks such as quantum teleportation, quantum key distribution, quantum sensing, and quantum error correction, often utilizing graph states, a specific class of multipartite…

Quantum Physics · Physics 2025-11-19 Aniruddha Sen , Kenneth Goodenough , Don Towsley

We present an alternative approach to unveil a different kind of entanglement in bipartite quantum states whose diagonal zero patterns in suitable matrix representations admit a nice description in terms of triangle-free graphs. Upon…

Quantum Physics · Physics 2021-03-30 Satvik Singh

We consider families of finite quantum graphs of increasing size and we are interested in how eigenfunctions are distributed over the graph. As a measure for the distribution of an eigenfunction on a graph we introduce the entropy, it has…

Mathematical Physics · Physics 2014-05-23 Lionel Kameni , Roman Schubert

We consider the canonical ensemble of $N$-vertex Erd\H{o}s-R\'enyi (ER) random topological graphs with quenched vertex degree, and with fugacity $\mu$ for each closed triple of bonds. We claim complete defragmentation of large-$N$ graphs…

Statistical Mechanics · Physics 2016-12-28 V. Avetisov , M. Hovhannisyan , A. Gorsky , S. Nechaev , M. Tamm , O. Valba

Generalised degrees provide a natural bridge between local and global topological properties of networks. We define the generalised degree to be the number of neighbours of a node within one and two steps respectively. Tailored random graph…

Disordered Systems and Neural Networks · Physics 2013-09-17 Ekaterina S. Roberts , Anthonius C. C. Coolen

Exponential random graph models have attracted significant research attention over the past decades. These models are maximum-entropy ensembles under the constraints that the expected values of a set of graph observables are equal to given…

Statistics Theory · Mathematics 2015-10-30 Konstantin Zuev , Or Eisenberg , Dmitri Krioukov

Motivated by studies of typical properties of quantum states in statistical mechanics, we introduce phase-random states, an ensemble of pure states with fixed amplitudes and uniformly distributed phases in a fixed basis. We first show that…

Quantum Physics · Physics 2015-03-19 Yoshifumi Nakata , Peter S. Turner , Mio Murao

Statistical properties of ensembles of random density matrices are investigated. We compute traces and von Neumann entropies averaged over ensembles of random density matrices distributed according to the Bures measure. The eigenvalues of…

Quantum Physics · Physics 2009-11-10 Hans-Juergen Sommers , Karol Zyczkowski

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…

Statistical Mechanics · Physics 2009-10-31 M. E. J. Newman , S. H. Strogatz , D. J. Watts

A fundamental problem in quantum information is to describe efficiently multipartite quantum states. An efficient representation in terms of graphs exists for several families of quantum states (graph, cluster, stabilizer states),…

Quantum Physics · Physics 2012-07-04 Radu Ionicioiu , Tim P. Spiller

We introduce a new random graph model motivated by biological questions relating to speciation. This random graph is defined as the stationary distribution of a Markov chain on the space of graphs on $\{1, \ldots, n\}$. The dynamics of this…

Probability · Mathematics 2019-06-24 François Bienvenu , Florence Débarre , Amaury Lambert

We propose the following model of a random graph on n vertices. Let F be a distribution in R_+^{n(n-1)/2} with a coordinate for every pair i$ with 1 \le i,j \le n. Then G_{F,p} is the distribution on graphs with n vertices obtained by…

Combinatorics · Mathematics 2011-08-09 Alan Frieze , Santosh Vempala , Juan Vera

We study the entanglement properties of randomized mixed hypergraph states, extending the concept of randomized mixed graph states to encompass hypergraph-based quantum states. In our model, imperfect generalized multi-qubit gates are…

Quantum Physics · Physics 2026-04-13 Vinícius Salem , Alison A. Silva , Fabiano M. Andrade

Random graph models have played a dominant role in the theoretical study of networked systems. The Poisson random graph of Erdos and Renyi, in particular, as well as the so-called configuration model, have served as the starting point for…

Statistical Mechanics · Physics 2014-12-03 M. E. J. Newman , Travis Martin

We investigate the joint distribution of the vertex degrees in three models of random bipartite graphs. Namely, we can choose each edge with a specified probability, choose a specified number of edges, or specify the vertex degrees in one…

Combinatorics · Mathematics 2022-12-22 Brendan D. McKay , Fiona Skerman

We show, through local estimates and simulation, that if one constrains simple graphs by their densities $\varepsilon$ of edges and $\tau$ of triangles, then asymptotically (in the number of vertices) for over $95\%$ of the possible range…

Combinatorics · Mathematics 2017-03-16 Charles Radin , Kui Ren , Lorenzo Sadun

For any graph, we define a rank-1 operator on a bipartite tensor product space, with components associated to the set of vertices and edges respectively. We show that the partial traces of the operator are the Laplacian and the…

Combinatorics · Mathematics 2013-05-01 Niel de Beaudrap , Vittorio Giovannetti , Simone Severini , Richard Wilson

In quantum statistical mechanics, it is of fundamental interest to understand how close the bipartite entanglement entropy of eigenstates of quantum chaotic Hamiltonians is to maximal. For random pure states in the Hilbert space, the…

Statistical Mechanics · Physics 2017-11-30 Lev Vidmar , Marcos Rigol

We consider the number of crossings in a graph which is embedded randomly on a convex set of points. We give an estimate to the normal distribution in Kolmogorov distance which implies a convergence rate of order $n^{-1/2}$ for various…

Combinatorics · Mathematics 2022-08-26 Santiago Arenas-Velilla , Octavio Arizmendi

We propose a distribution-free approach to the study of random geometric graphs. The distribution of vertices follows a Poisson point process with intensity function $nf(\cdot)$, where $n\in \mathbb{N}$, and $f$ is a probability density…

Probability · Mathematics 2012-10-22 Srikanth K. Iyer , Debleena Thacker
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