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Steady technological advances and recent milestones such as intercontinental quantum communication and the first implementation of medium-scale quantum networks are paving the way for the establishment of the quantum internet, a network of…

Quantum Physics · Physics 2023-12-15 Rute Oliveira , Raabe Oliveira , Nadja K. Bernardes , Rafael Chaves

We study multi-qubit variational quantum states that can be considered as vertex- and edge-weighted graph. These states are constructed as single-layer variational circuits with $RX$ rotations and $RZZ$ entangling gates, corresponding to…

Quantum Physics · Physics 2026-04-22 Kh. P. Gnatenko , A. Kaczmarek

We study a quantum network that distributes entangled quantum states to multiple sets of users that are connected to the network. Each user is connected to a switch of the network via a link. All the links of the network generate bipartite…

Quantum Physics · Physics 2021-06-03 Thirupathaiah Vasantam , Don Towsley

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

We address the problem of routing quantum and classical information from one sender to many possible receivers in a network. By employing the formalism of quantum walks, we describe the dynamics on a discrete structure based on a complete…

The increasing complexity and interdependency of today's networks highlight the importance of studying network robustness to failure and attacks. Many large-scale networks are prone to cascading effects where a limited number of initial…

Social and Information Networks · Computer Science 2016-07-27 Khashayar Kamran , Edmund Yeh

Variational hybrid quantum-classical algorithms are promising candidates for near-term implementation on quantum computers. In these algorithms, a quantum computer evaluates the cost of a gate sequence (with speedup over classical cost…

Quantum Physics · Physics 2019-06-27 Ryan LaRose , Arkin Tikku , Étude O'Neel-Judy , Lukasz Cincio , Patrick J. Coles

Quantum walks provide a natural framework to approach graph problems with quantum computers, exhibiting speedups over their classical counterparts for tasks such as the search for marked nodes or the prediction of missing links.…

Quantum Physics · Physics 2023-06-27 Duarte Magano , João Moutinho , Bruno Coutinho

Graph states are a class of important multiparty entangled states, of which bell pairs are the special case. Realizing a robust and fast distribution of arbitrary graph states in the downstream layer of the quantum network can be essential…

Quantum Physics · Physics 2025-06-09 Yuexun Huang , Xiangyu Ren , Bikun Li , Yat Wong , Zhiding Liang , Liang Jiang

Continuous variable remote state preparation and teleportation are analyzed using Wigner functions in phase space. We suggest a remote squeezed state preparation scheme between two parties sharing an entangled twin beam, where homodyne…

Quantum Physics · Physics 2009-11-07 Matteo G. A. Paris , Mary Cola , Rodolfo Bonifacio

Network architecture design is very important for the optimization of industrial networks. The type of network architecture can be divided into small-scale network and large-scale network according to its scale. Graph theory is an efficient…

Social and Information Networks · Computer Science 2022-09-20 Chao Dong , Xiaoxiong Xiong , Qiulin Xue , Zhengzhen Zhang , Kai Niu , Ping Zhang

Quantum communication is a growing area of research, with quantum internet being one of the most promising applications. Studying the statistical properties of this network is essential to understanding its connectivity and the efficiency…

We extend the previously observed scaling equation connecting the internode distances and nodes' degrees onto the case of weighted networks. We show that the scaling takes a similar form in the empirical data obtained from networks…

Physics and Society · Physics 2010-08-25 Julian Sienkiewicz , Janusz A. Holyst

Entanglement, one of the clearest manifestations of non-classical physics, holds significant promise for technological applications such as more secure communications and faster computations. In this paper we explore the use of…

Quantum Physics · Physics 2024-02-14 Karl Pelka , Matteo Aquilina , André Xuereb

Distributing entanglement to distant parties in a network is a central task in quantum information processing and quantum networking. The sensitivity of entangled states to loss necessitates the use of entanglement routing strategies.…

Quantum Physics · Physics 2026-05-28 Xin-An Chen , Caitao Zhan , Joaquin Chung , Jeffrey Larson

We introduce a heterogeneous connection model for network formation to capture the effect of cost heterogeneity on the structure of efficient networks. In the proposed model, connection costs are assumed to be separable, which means the…

Economics · Quantitative Finance 2015-12-14 Babak Heydari , Mohsen Mosleh , Kia Dalili

We introduce a non-interacting boson model to investigate topological structure of complex networks in the present paper. By exactly solving this model, we show that it provides a powerful analytical tool in uncovering the important…

Physics and Society · Physics 2015-05-13 Xin Jiang , Hailong Wang , Lili Ma , Zhanli Zhang , Shaoting Tang , Guangshan Tian , Zhiming Zheng

The practical utility of a quantum network depends on its ability to establish entanglement between arbitrary node pairs with quality sufficient to execute entanglement enabled tasks. This capability can be assessed globally, through…

Quantum Physics · Physics 2026-04-01 Md Sohel Mondal , Shashank Shekhar , Siddhartha Santra

This dissertation is a study on the design and analysis of novel, optimal routing and rate control algorithms in wireless, mobile communication networks. Congestion control and routing algorithms upto now have been designed and optimized…

Networking and Internet Architecture · Computer Science 2012-01-20 Jung Ryu

Graph Convolutional Networks (GCNs) are extensively utilized for deep learning on graphs. The large data sizes of graphs and their vertex features make scalable training algorithms and distributed memory systems necessary. Since the…

Machine Learning · Computer Science 2022-12-14 Gunduz Vehbi Demirci , Aparajita Haldar , Hakan Ferhatosmanoglu
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