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Quantum communication brings radically new capabilities that are provably impossible to attain in any classical network. Here, we take the first step from a physics experiment to a fully fledged quantum internet system. We propose a…

Entanglement distribution is a key functionality of the Quantum Internet. However, quantum entanglement is very fragile, easily degraded by decoherence, which strictly constraints the time horizon within the distribution has to be…

Quantum Physics · Physics 2024-09-05 Angela Sara Cacciapuoti , Jessica Illiano , Michele Viscardi , Marcello Caleffi

We present a stack model for breaking down the complexity of entanglement-based quantum networks. More specifically, we focus on the structures and architectures of quantum networks and not on concrete physical implementations of network…

Quantum Physics · Physics 2019-03-27 A. Pirker , W. Dür

We study the limits of bipartite entanglement distribution using a chain of quantum repeaters that have quantum memories. To generate end-to-end entanglement, each node can attempt the generation of an entangled link with a neighbor, or…

Quantum Physics · Physics 2023-05-11 Álvaro G. Iñesta , Gayane Vardoyan , Lara Scavuzzo , Stephanie Wehner

Building large-scale quantum computers, essential to demonstrating quantum advantage, is a key challenge. Quantum Networks (QNs) can help address this challenge by enabling the construction of large, robust, and more capable quantum…

Quantum Physics · Physics 2025-03-20 Xiaojie Fan , Caitao Zhan , Himanshu Gupta , C. R. Ramakrishnan

Quantum networks will allow to implement communication tasks beyond the reach of their classical counterparts. A pressing and necessary issue for the design of quantum network protocols is the quantification of the rates at which these…

Quantum Physics · Physics 2020-04-22 Stefan Bäuml , Koji Azuma , Go Kato , David Elkouss

Markov Decision Processes (MDPs) have been used to formulate many decision-making problems in science and engineering. The objective is to synthesize the best decision (action selection) policies to maximize expected rewards (or minimize…

Optimization and Control · Mathematics 2015-07-07 Mahmoud El Chamie , Behcet Acikmese

In Markov decision processes (MDPs), quantile risk measures such as Value-at-Risk are a standard metric for modeling RL agents' preferences for certain outcomes. This paper proposes a new Q-learning algorithm for quantile optimization in…

Machine Learning · Computer Science 2024-11-01 Jia Lin Hau , Erick Delage , Esther Derman , Mohammad Ghavamzadeh , Marek Petrik

We present a framework to address a class of sequential decision making problems. Our framework features learning the optimal control policy with robustness to noisy data, determining the unknown state and action parameters, and performing…

Machine Learning · Computer Science 2022-01-20 Amber Srivastava , Srinivasa M Salapaka

Entangled states shared among distant nodes are frequently used in quantum network applications. When quantum resources are abundant, entangled states can be continuously distributed across the network, allowing nodes to consume them…

Quantum Physics · Physics 2024-02-01 Álvaro G. Iñesta , Stephanie Wehner

Quantum computing holds a great promise and this work proposes to use new quantum data networks (QDNs) to connect multiple small quantum computers to form a cluster. Such a QDN differs from existing QKD networks in that the former must…

Networking and Internet Architecture · Computer Science 2021-05-27 Yangming Zhao , Chunming Qiao

Efficient entanglement distribution is the foundational challenge in realizing large-scale Quantum Networks. However, state-of-the-art solutions are frequently limited by restrictive operational assumptions, prohibitive computational…

The efficacy of a communication network hinges upon both its physical architecture and the protocols that are employed within it. In the context of quantum communications, there exists a fundamental rate-loss tradeoff for point-to-point…

Quantum Physics · Physics 2025-12-18 Cillian Harney , Stefano Pirandola

Quantum networks, capable of transmitting arbitrary quantum states, provide a foundation for a wide range of quantum applications, including distributed quantum computing, distributed quantum sensing, and quantum communication. Photons are…

Quantum Physics · Physics 2025-08-28 Tian-Xiang Zhu , Xiao Liu , Zong-Quan Zhou , Chuan-Feng Li

Quantum networks are envisioned to enable reliable distribution and manipulation of quantum information across distances, forming the foundation of a future quantum internet. The fair and efficient allocation of communication resources in…

Quantum Physics · Physics 2026-03-13 Sounak Kar , Arpan Mukhopadhyay

Markov decision processes (MDPs) describe sequential decision-making processes; MDP policies return for every state in that process an advised action. Classical algorithms can efficiently compute policies that are optimal with respect to,…

Logic in Computer Science · Computer Science 2025-05-23 Roman Andriushchenko , Milan Češka , Sebastian Junges , Filip Macák

Quantum networks facilitate numerous applications such as secure communication and distributed quantum computation by performing entanglement distribution. Multi-user quantum applications where quantum information is shared between multiple…

Quantum Physics · Physics 2024-02-16 Evan Sutcliffe , Alejandra Beghelli

We analyze how the performance of a quantum-repeater network depends on the protocol employed to distribute entanglement, and we find that the choice of repeater-to-repeater link protocol has a profound impact on communication rate as a…

Quantum Physics · Physics 2016-08-24 Cody Jones , Danny Kim , Matthew T. Rakher , Paul G. Kwiat , Thaddeus D. Ladd

In quantum networks multipath entanglement purification (MEP) between a pair of source-destination nodes can substantially strengthen their entanglement connection. An efficient MEP strategy can therefore increase the size of the network…

Quantum Physics · Physics 2024-08-28 Md Sohel Mondal , Siddhartha Santra

We introduce a framework for approximate analysis of Markov decision processes (MDP) with bounded-, unbounded-, and infinite-horizon properties. The main idea is to identify a "core" of an MDP, i.e., a subsystem where we provably remain…

Systems and Control · Electrical Eng. & Systems 2023-06-22 Jan Křetínský , Tobias Meggendorfer