Relevant bibliographies by topics / Quantum Networks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Quantum Networks'

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Published: 4 June 2021
Last updated: 31 August 2024

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Journal articles on the topic "Quantum Networks"

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Meng, Xiangyi, Xinqi Hu, Yu Tian, Gaogao Dong, Renaud Lambiotte, Jianxi Gao, and Shlomo Havlin. "Percolation Theories for Quantum Networks." Entropy 25, no. 11 (November 20, 2023): 1564. http://dx.doi.org/10.3390/e25111564.

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Quantum networks have experienced rapid advancements in both theoretical and experimental domains over the last decade, making it increasingly important to understand their large-scale features from the viewpoint of statistical physics. This review paper discusses a fundamental question: how can entanglement be effectively and indirectly (e.g., through intermediate nodes) distributed between distant nodes in an imperfect quantum network, where the connections are only partially entangled and subject to quantum noise? We survey recent studies addressing this issue by drawing exact or approximate mappings to percolation theory, a branch of statistical physics centered on network connectivity. Notably, we show that the classical percolation frameworks do not uniquely define the network’s indirect connectivity. This realization leads to the emergence of an alternative theory called “concurrence percolation”, which uncovers a previously unrecognized quantum advantage that emerges at large scales, suggesting that quantum networks are more resilient than initially assumed within classical percolation contexts, offering refreshing insights into future quantum network design.
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Miguel-Ramiro, Jorge, Alexander Pirker, and Wolfgang Dür. "Optimized Quantum Networks." Quantum 7 (February 9, 2023): 919. http://dx.doi.org/10.22331/q-2023-02-09-919.

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The topology of classical networks is determined by physical links between nodes, and after a network request the links are used to establish the desired connections. Quantum networks offer the possibility to generate different kinds of entanglement prior to network requests, which can substitute links and allow one to fulfill multiple network requests with the same resource state. We utilize this to design entanglement-based quantum networks tailored to their desired functionality, independent of the underlying physical structure. The kind of entanglement to be stored is chosen to fulfill all desired network requests (i.e. parallel bipartite or multipartite communications between specific nodes chosen from some finite set), but in such a way that the storage requirement is minimized. This can be accomplished by using multipartite entangled states shared between network nodes that can be transformed by local operations to different target states. We introduce a clustering algorithm to identify connected clusters in the network for a given desired functionality, i.e. the required network topology of the entanglement-based network, and a merging algorithm that constructs multipartite entangled resource states with reduced memory requirement to fulfill all desired network requests. This leads to a significant reduction in required time and resources, and provides a powerful tool to design quantum networks that is unique to entanglement-based networks.
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Xu, Zenglin. "Tensor Networks Meet Neural Networks." Journal of Physics: Conference Series 2278, no. 1 (May 1, 2022): 012003. http://dx.doi.org/10.1088/1742-6596/2278/1/012003.

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Abstract As a simulation of the human cognitive system, deep neural networks have achieved great success in many machine learning tasks and are the main driving force of the current development of artificial intelligence. On the other hand, tensor networks as an approximation of quantum many-body systems in quantum physics are applied to quantum physics, statistical physics, quantum chemistry and machine learning. This talk will first give a brief introduction to neural networks and tensor networks, and then discuss the cross-field research between deep neural networks and tensor networks, such as network compression and knowledge fusion, including our recent work on tensor neural networks. Finally, this talk will also discuss the connection to quantum machine learning.
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Zhang, Yulu, and Hua Lu. "Reliability Research on Quantum Neural Networks." Electronics 13, no. 8 (April 16, 2024): 1514. http://dx.doi.org/10.3390/electronics13081514.

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Quantum neural networks (QNNs) leverage the strengths of both quantum computing and neural networks, offering solutions to challenges that are often beyond the reach of traditional neural networks. QNNs are being used in areas such as computer games, function approximation, and big data processing. Moreover, quantum neural network algorithms are finding utility in social network modeling, associative memory systems, and automatic control mechanisms. Nevertheless, ensuring the reliability of quantum neural networks is crucial as it directly influences network performance and stability. To investigate the reliability of quantum neural networks, this paper proposes a methodology wherein operator measurements are performed on the final states of the output quantum states of a quantum neural network. The proximity of these measurements to the target value is compared, and the fidelity value, combined with a quantum gate operation, is utilized to assess the reliability of the quantum neural network. Through network training, the results demonstrate that, under optimal parameters, both the fidelity of the final state measurement value and the target value of the model approach are approximately equal to 1. It indicates that training mitigates the errors stemming from encoding into the initial quantum state, thereby resulting in enhanced system reliability and accuracy.
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Mihály, András, and László Bacsárdi. "Optical transmittance based store and forward routing in satellite networks." Infocommunications journal 15, no. 2 (2023): 8–13. http://dx.doi.org/10.36244/icj.2023.2.2.

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Quantum computing will play a crucial part in our security infrastructure for the coming years. Quantum networks can consist of direct optical fiber or free-space links. With the use of satellite channels, we can create a quantum network with higher coverage than using optical fibers where the distances are limited due to the properties of the fiber. One of the highest drivers of cost for satellite networks, apart from the cost of the technology needed for such systems, are the costs of launching and maintaining said satellites. By minimizing the satellites needed for a well-functioning quantum network, we can decrease said network’s cost, thus enabling a cheaper quantum internet. In this paper, we present an optical transmittance-based routing algorithm with which it is possible to conduct successful quantum entanglement transfer between terrestrial nodes.
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Zhang, Chang-Yue, Zhu-Jun Zheng, Shao-Ming Fei, and Mang Feng. "Dynamics of Quantum Networks in Noisy Environments." Entropy 25, no. 1 (January 12, 2023): 157. http://dx.doi.org/10.3390/e25010157.

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Noise exists inherently in realistic quantum systems and affects the evolution of quantum systems. We investigate the dynamics of quantum networks in noisy environments by using the fidelity of the quantum evolved states and the classical percolation theory. We propose an analytical framework that allows us to characterize the stability of quantum networks in terms of quantum noises and network topologies. The calculation results of the framework determine the maximal time that quantum networks with different network topologies can maintain the ability to communicate under noise. We demonstrate the results of the framework through examples of specific graphs under amplitude damping and phase damping noises. We further consider the capacity of the quantum network in a noisy environment according to the proposed framework. The analytical framework helps us better understand the evolution time of a quantum network and provides a reference for designing large quantum networks.
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Curcic, Tatjana, Mark E. Filipkowski, Almadena Chtchelkanova, Philip A. D'Ambrosio, Stuart A. Wolf, Michael Foster, and Douglas Cochran. "Quantum networks." ACM SIGCOMM Computer Communication Review 34, no. 5 (October 15, 2004): 3–8. http://dx.doi.org/10.1145/1039111.1039117.

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Hirche, Christoph. "Quantum Network Discrimination." Quantum 7 (July 25, 2023): 1064. http://dx.doi.org/10.22331/q-2023-07-25-1064.

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Discrimination between objects, in particular quantum states, is one of the most fundamental tasks in (quantum) information theory. Recent years have seen significant progress towards extending the framework to point-to-point quantum channels. However, with technological progress the focus of the field is shifting to more complex structures: Quantum networks. In contrast to channels, networks allow for intermediate access points where information can be received, processed and reintroduced into the network. In this work we study the discrimination of quantum networks and its fundamental limitations. In particular when multiple uses of the network are at hand, the rooster of available strategies becomes increasingly complex. The simplest quantum network that capturers the structure of the problem is given by a quantum superchannel. We discuss the available classes of strategies when considering n copies of a superchannel and give fundamental bounds on the asymptotically achievable rates in an asymmetric discrimination setting. Furthermore, we discuss achievability, symmetric network discrimination, the strong converse exponent, generalization to arbitrary quantum networks and finally an application to an active version of the quantum illumination problem.
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Trahan, Corey, Mark Loveland, and Samuel Dent. "Quantum Physics-Informed Neural Networks." Entropy 26, no. 8 (July 30, 2024): 649. http://dx.doi.org/10.3390/e26080649.

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In this study, the PennyLane quantum device simulator was used to investigate quantum and hybrid, quantum/classical physics-informed neural networks (PINNs) for solutions to both transient and steady-state, 1D and 2D partial differential equations. The comparative expressibility of the purely quantum, hybrid and classical neural networks is discussed, and hybrid configurations are explored. The results show that (1) for some applications, quantum PINNs can obtain comparable accuracy with less neural network parameters than classical PINNs, and (2) adding quantum nodes in classical PINNs can increase model accuracy with less total network parameters for noiseless models.
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Franco, Mario, Octavio Zapata, David A. Rosenblueth, and Carlos Gershenson. "Random Networks with Quantum Boolean Functions." Mathematics 9, no. 8 (April 7, 2021): 792. http://dx.doi.org/10.3390/math9080792.

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We propose quantum Boolean networks, which can be classified as deterministic reversible asynchronous Boolean networks. This model is based on the previously developed concept of quantum Boolean functions. A quantum Boolean network is a Boolean network where the functions associated with the nodes are quantum Boolean functions. We study some properties of this novel model and, using a quantum simulator, we study how the dynamics change in function of connectivity of the network and the set of operators we allow. For some configurations, this model resembles the behavior of reversible Boolean networks, while for other configurations a more complex dynamic can emerge. For example, cycles larger than 2N were observed. Additionally, using a scheme akin to one used previously with random Boolean networks, we computed the average entropy and complexity of the networks. As opposed to classic random Boolean networks, where “complex” dynamics are restricted mainly to a connectivity close to a phase transition, quantum Boolean networks can exhibit stable, complex, and unstable dynamics independently of their connectivity.
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Dissertations / Theses on the topic "Quantum Networks"

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Dai, Wenhan. "Quantum networks : state transmission and network operation." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128289.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2020
Cataloged from student-submitted the PDF of thesis.
Includes bibliographical references (pages 147-155).
Quantum information science is believed to create the next technological revolution. As key ingredients of quantum information science, quantum networks enable various technologies such as secure communication, distributed quantum sensing, quantum cloud computing, and next-generation positioning, navigation, and timing. The main task of quantum networks is to enable quantum communication among different nodes in the network. This includes the topics such as the transmission of quantum states involving multiple parties, the processing of quantum information at end nodes, and the distribution of entanglement among remote nodes. Since quantum communication has its own peculiar properties that have no classical counterparts, the protocols and strategies designed for classical communication networks are not well-suited for quantum ones. This calls for new concepts, paradigms, and methodologies tailored for quantum networks.
To that end, this thesis studies the design and operation of quantum networks, with focus on the following three topics: state transmission, queueing delay, and remote entanglement distribution. The first part develops protocols to broadcast quantum states from a transmitter to N different receivers. The protocols exhibit resource tradeoffs between multiparty entanglement, broadcast classical bits (bcbits), and broadcast quantum bits (bqubits), where the latter two are new types of resources put forth in this thesis. We prove that to send 1 bqubit to N receivers using shared entanglement, O(logN) bcbits are both necessary and sufficient. We also show that the protocols can be implemented using poly(N) basic gates composed of single-qubit gates and CNOT gates. The second part introduces a tractable model for analyzing the queuing delay of quantum data, referred to as quantum queuing delay (QQD).
The model employs a dynamic programming formalism and accounts for practical aspects such as the finite memory size. Using this model, we develop a cognitive-memory-based policy for memory management and show that this policy can decrease the average queuing delay exponentially with respect to memory size. The third part offers a design of remote entanglement distribution (RED) protocols that maximize the entanglement distribution rate (EDR). We introduce the concept of enodes, representing the entangled quantum bit (qubit) pairs in the network. This concept enables us to design the optimal RED protocols based on the solutions of some linear programming problems. Moreover, we investigate RED in a homogeneous repeater chain, which is a building block for many quantum networks. In particular, we determine the maximum EDR for homogeneous repeater chains in a closed form. The contributions of this work provide guidelines for the design and implementation of quantum networks.
by Wenhan Dai.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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Valentini, Lorenzo. "Quantum Error Correction for Quantum Networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Le quantum networks e molte altre tecnologie, quali i quantum computer, necessitano di qubit affidabili per il loro funzionamento. Per ottenere ciò, in questo elaborato, si presenta il tema della quantum error correction ponendo particolare attenzione ai codici quantum low-density parity-check (QLDPC). In aggiunta, vengono testati alcuni algoritmi su IBMQ, la serie di computer quantistici resi disponibili online da IBM, per comprenderne le problematiche. Si conclude l'elaborato con alcune riflessioni su come i codici presentati possono arginare alcune delle problematiche riscontrate durante l'implementazione su quantum computer.
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Rafiei, Nima. "Quantum Communication Networks." Thesis, Stockholms universitet, Fysikum, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-186606.

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Quantum communication protocols invoke one of the most fundamentallaws of quantum mechanics, namely the superposition principle whichleads to the no-cloning theorem. During the last three decades, quantumcryptography have gone from prospective theories to practical implementationsscalable for real communication. Scientist from all over the world havecontributed to this major progress, starting from Stephen Wiesner, CharlesH. Bennett and Gilles Brassard who all developed the theory of QuantumKey Distribution (QKD). QKD lets two users share a key through a quantumchannel (free space or fiber link) under unconditionally secure circumstances.They can use this key to encode a message which they thereaftershare through a public channel (internet, telephone,...). Research developmentshave gone from the ordinary 2-User Quantum Key Distribution oververy small free space distances to distances over 200 km in optical fiber andQuantum Key Distribution Networks.As great experimental achievements have been made regarding QKDprotocols, a new quantum communication protocol have been developed,namely Quantum Secret Sharing. Quantum Secret Sharing is an extensionof an old cryptography scheme called Secret Sharing. The aim of secretsharing is to split a secret amongst a set of users in such a way that thesecret is only revealed if every user of this set is ready to collaborate andshare their part of the secret with other users.We have developed a 5-User QKD Network through birefringent singlemode fiber in two configurations. One being a Tree configuration and theother being a Star configuration. In both cases, the number of users, thedistances between them and the stability of our setup are all well competitivewith the current worldwide research involving similar work.We have also developed a Single Qubit Quantum Secret Sharing schemewith phase encoding through single mode fiber with 3, 4 and 5 parties. Thelatter is, to the best of our knowledge, the first time a 5-Party Single QubitQuantum Secret Sharing experiment has been realized.
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Maring, Nicolas. "Quantum frecuency conversion for hybrid quantum networks." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/663202.

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The ability to control the optical frequency of quantum state carriers (i.e. photons) is an important functionality for future quantum networks. It allows all matter quantum systems - nodes of the network - to be compatible with the telecommunication C-band, therefore enabling long distance fiber quantum communication between them. It also allows dissimilar nodes to be connected with each other, thus resulting in heterogeneous networks that can take advantage of the different capabilities offered by the diversity of its constituents. Quantum memories are one of the building blocks of a quantum network, enabling the storage of quantum states of light and the entanglement distribution over long distances. In our group, two different types of memories are investigated: a cold atomic ensemble and an ion-doped crystal. In this thesis I investigate the quantum frequency conversion of narrow-band photons, emitted or absorbed by optical quantum memories, with two different objectives: the first one is to connect quantum memories emitting or absorbing visible single photons with the telecommunication wavelengths, where fiber transmission loss is minimum. The second and main goal is to study the compatibility between disparate quantum nodes, emitting or absorbing photons at different wavelengths. More precisely the objective is to achieve a quantum connection between the two optical memories studied using quantum frequency conversion techniques. The main core of this work is the quantum frequency conversion interface that bridges the gap between the cold ensemble of Rubidium atoms, emitting photons at 780nm, and the Praseodymium ion doped crystal, absorbing photons at 606nm. This interface is composed of two different frequency conversion devices, where a cascaded conversions takes place: the first one converts 780nm photons to the telecommunication C-band, and the second one converts them back to visible, at 606nm. This comes with several challenges such as conversion efficiency, phase stability and parasitic noise reduction, which are important considerations to show the conservation of quantum behaviors through the conversion process. This work can be divided in three parts. In a first one, we built a quantum frequency conversion interface between 606nm and the C-band wavelength, capable of both up and down-conversion of single photon level light. We also characterized the noise processes involved in this specific conversion. In the down-conversion case we showed that memory compatible heralded single photons emitted from a photon pair source preserve their non-classical properties through the conversion process. In the up-conversion case, we showed the storage of converted telecom photons in the praseodymium doped crystal, and their retrieval with high signal to noise ratio. The second part of the work was devoted to the conversion of photons from an emissive Rubidium atomic quantum memory to the telecom C band. In this work we converted the heralding photons from the atomic ensemble and measured non-classical correlations between a stored excitation and a C-band photon, necessary for quantum repeater applications. In the last part of the thesis, we setup the full frequency conversion interface and showed that heralded photons emitted by the atomic ensemble are converted, stored in the solid state memory and retrieved with high signal to noise ratio. We demonstrated that a single collective excitation stored in the atomic ensemble is transfered to the crystal by mean of a single photon at telecom wavelength. We also showed time-bin qubit transfer between the two quantum memories. This work represents the first proof of principle of a photonic quantum connection between disparate quantum memory nodes. The results presented in this thesis pave the way towards the realization of modular and hybrid quantum networks.
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Menneer, Tamaryn Stable Ia. "Quantum artificial neural networks." Thesis, University of Exeter, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286530.

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FAROOQ, UMER. "Decoherence in Quantum Networks." Doctoral thesis, Università degli Studi di Camerino, 2015. http://hdl.handle.net/11581/401743.

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The title of the present dissertation Decoherence in Quantum Network sounds very general and all-inclusive. Indeed it embraces two topics (decoherence and quantum network) from the area of Quantum Mechanics each of which is described in all respects by a huge literature developed in the last three decades [...]. Quantum decoherence, as the name lets it mean, is the mechanism that makes a quantum system loose its coherence properties, and with them the capability of giving rise to interference phenomena or to other interesting quantum effects [...]. The key idea promoted by decoherence is the insight that realistic quantum systems are never isolated, but are immersed in the surrounding environment and interact continuously with it [...]. As an example one may consider a two-level quantum system (i.e. a quantum bit, usually shortened with a terminology from information science to \qubit" ) in contact with a wide environment. Hence, quantum systems are open systems, and continuously interact or exchange information with an external environment whose degrees of freedom are too numerous to be monitored. The resulting correlation between the system and the environment spoils quantum coherence and brings about the transition from a pure quantum state to a mixture of quantum state resulting a classical state. To describe decoherence different kind of approaches can be used (for example Master equation, random matrix, etc). A quantum network typically consists of a number of quantum objects (e.g., atoms, ions, quantum dots, cavities, etc.), to be referred to hereafter as the sites or the nodes of the network. They can interact and the interactions (or their correlations) will be usually described by the edges of a graph. Quantum networks can address different information processing tasks. For instance a quantum state can be transferred from qubit to qubit down a chain solely due to the interactions, that is according to the laws of quantum physics [...]. Quantum networks offer us new opportunities and phenomena as compared to classical networks. An extension to large scale of the idea of a quantum network could lead to a futurible quantum internet [...]. The study of networks has traditionally been the territory of graph theory [...], also with the advent of their quantum versions. Within simple quantum network model information processing is usually described by assuming perfect control of the underlying graph. However, this is not much realistic since randomness is often present and it leads to decoherence effects [...]. In contrast, the conservation of coherence is essential for any quantum information process [...], hence there is a persistent interest in decoherence effects in quantum networks, which motivate us to study models for describing such noisy effects. We consider a simple model of quantum network, employing qubits (spin-1/2 particles) attached to the nodes of an underlying graph and we study the simplest task, namely information storage (on a single and two qubits), when the graph randomly changes in time. Actually we randomly add edges to an initially disconnected graph according to the Gilbert model characterized by a weighting parameter ex [...] and in an identically and independent way at each time step. We find that by increasing ex the dynamics of relevant quantities like fidelity, entropy or concurrence, gradually transforms from damped to damped oscillatory and finally to purely oscillatory. That leads to the paper [see, Information dissipation in random quantum networks, by U. Farooq and S. Mancini, OSID 21(3), 1450004, 2014]. We also study a system composed by pairs of qubits attached to each node of a linear chain, a model that stems from quantum dot arrays. Here we use the approach of evolution with a stochastic Hamiltonian to describe the noisy effects. We then evaluate the effect of two most common disorders, namely exchange coupling and hyperfine interaction fluctuations, in adiabatic preparation of ground state in such model. We show that the adiabatic ground state preparation is highly robust against these disorders making the chain a good analog simulator. Moreover, we also study the adiabatic information transfer, using singlet-triplet states, across the chain. In contrast to ground state preparation the transfer mechanism is highly affected by disorders. This suggested that for communication tasks across such chains adiabatic evolution is not as effective and quantum quenches would be preferable. That leads to the paper [see, Adiabatic many-body state preparation and information transfer in quantum dot arrays, by U. Farooq, A. Bayat, S. Mancini and S. Bose Phys. Rev. B 91, 134303, 2015]. The present work is organized as follows. In chapter 1, we shall give a survey of the various types of approach which can be employed to analyse the dynamics of open quantum systems that leads to decoherence effects. In chapter 2, we shall give a general description about quantum network and its possible applications. In chapter 3, we shall discuss the problem of quantum state transfer in qubit network and shall give a brief overview of some scheme that enable nearly prefect state transfer. In chapter 4, we shall discuss singlet-triplet networks, that is networks having on each site a pair of (generally entangled) qubit. Then within this framework we propose a model stemming from quantum dot array. There we shall address the problem of ground state preparation and state transfer. Finally we shall describe the inherent entanglement of the ground state of strongly correlated systems can be exploited for both classical and quantum communications. In chapter 5, we shall propose a decoherence model for qubit networks based on edges representing XY interactions randomly added to a disconnected graph accordingly to a suitable probability distribution. In this way we shall describe dissipation of information initially localize in single or two qubits all over the network. In chapter 6 we shall model the noisy effects in the quantum dot array introduced in chapter 4 and investigate their consequences on the preparation of ground state and quantum state transfer mechanism. Finally we shall draw conclusions.
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Andersson, Erika. "Quantum information and atomic networks." Doctoral thesis, Stockholm, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3068.

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Meignant, Clément. "Multipartite communications over quantum networks." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS342.

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Le domaine des réseaux quantiques est actuellement un champ d'investigation majeur dans les technologies quantiques. Des recherches sont en cours à tous les niveaux. L'un des actes les plus simples de la communication quantique, la distribution d'un état unique bipartite intriqué, a été très étudié car il s'agit d'un problème simple à caractériser, simuler et mettre en œuvre. Il est également utile pour une application importante des réseaux quantiques : la distribution sécurisée d'une clé cryptographique. Cependant, l'utilisation des réseaux quantiques va bien au-delà, dans le domaine multipartite. Dans ce manuscrit, nous étudions d'abord le recyclage de ressources précédemment distribuées dans le régime asymptotique par l'utilisation du peignage d'intrication et de la fusion d'états quantiques. Ensuite, nous caractérisons la distribution des états quantiques en utilisant le formalisme du réseau tensoriel. Nous caractérisons également une large classe de protocoles de distribution classiques et utilisons cette similitude pour comparer la distribution des corrélations classiques sur les réseaux classiques à la distribution des états quantiques sur les réseaux quantiques. Enfin, nous mettons en œuvre les protocoles précédents dans un cadre plus réaliste et participons à l'élaboration de fonctionnalités multipartites pour un simulateur de réseau quantique : QuISP. Nous avons également cherché à vulgariser et à diffuser les notions d'information quantique auprès d'un large public. Nous rendons compte de la création d'un jeu vidéo basé sur l'optique quantique, s'ajoutant à la vulgarisation ludographique existante
The field of quantum networks is currently a major area of investigation in quantum technologies. One of the simplest acts of quantum communication, the distribution of a single bipartite entangled state, has been highly studied as it is a simple problem to characterize, simulate and implement. It is also useful for a prominent quantum network application: the secured distribution of a cryptographic key. However, the use of quantum networks goes far beyond. We need to study the simultaneous distribution of multipartite states over quantum networks. In this manuscript, we report on several works of progress in the domain. We first study the recycling of previously distributed resources in the asymptotic regime by the use of entanglement combing and quantum state merging. Then, we characterize the distribution of quantum states using the tensor network formalism. We also characterize a broad class of classical distribution protocols by the same formalism and use this similarity to compare the distribution of classical correlations over classical networks to a the distribution of quantum state over quantum networks. We also build protocols to distribute specific classes of states over quantum networks such as graph states and GHZ states by using the graph state formalism and a bit of graph theory. Finally, we implement the previous protocols in a more realistic setting and participate in the elaboration of multipartite features for a quantum network simulator: QuISP. We also aimed to popularize the notions of quantum information to a broad audience. We report on the creation of a video game based on quantum optics, adding to the existing popularization ludography
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Pesah, Arthur. "Learning quantum state properties with quantum and classical neural networks." Thesis, KTH, Tillämpad fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252693.

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Román, Rodríguez Víctor. "Quantum Optics Systems for Long-Distance Cryptography and Quantum Networks." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS224.

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La thèse est divisée en deux parties : La première partie s'inscrit dans le domaine de la cryptographie quantique. Dans cette partie, nous développons une étude théorique d'un protocole de distribution de clés quantiques (QKD) dans le scénario d'une liaison satellite-station terrestre. Nous considérons l'ajout des fluctuations quantiques du canal et la possibilité de succès du protocole dans le cadre de variables continues dans une implémentation avec des technologies de pointe. Nous montrons la faisabilité de CVQKD dans le contexte du satellite. Dans la deuxième partie, nous construisons, à partir de zéro, une source d'états quantiques de la lumière de type graphe à variables continues en utilisant des guides d'ondes non linéaires. Ces états sont essentiels pour la mise en œuvre de protocoles de communication et de calcul quantique, car ils peuvent être considérés comme des réseaux quantiques. Nous réalisons une étude théorique des états quantiques multimodes de la lumière après l'interaction dans un guide d'ondes non linéaire qui nous aide à concevoir l'expérience. Enfin, nous présentons les résultats expérimentaux qui démontrent les premiers résultats sur la source quantique d'états quantiques de lumière multimode à variation continue, mesurant jusqu'à 11 états de lumière thermique comprimée
The thesis is divided into two parts: The first part is in the field of Quantum Cryptography. In this part we develop a theoretical study of a Quantum Key Distribution (QKD) protocol in the scenario of a satellite-ground station link. We consider the addition of quantum channel fluctuations and the possibility of success of the protocol in the framework of continuous variables in an implementation with state-of-the-art technologies. We show the feasibility of CVQKD in the satellite context. In the second part, we build, from scratch, a source of continuous-variable graph-like quantum states of light using nonlinear waveguides. These states are essential for the implementation of communication and quantum computing protocol as they can be seen to be quantum networks. We perform a theoretical study for multimode quantum states of light after the interaction in a non-linear waveguide that help us to design the experiment. Finally we present the experimental results that demonstrate the first results on the quantum source of continuous variable multimode quantum states of light, measuring up to 11 squeezed thermal light states
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Books on the topic "Quantum Networks"

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Mahler, Günter, and Volker A. Weberruß. Quantum Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03176-6.

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Mahler, Günter, and Volker A. Weberruß. Quantum Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03669-3.

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Bassoli, Riccardo, Holger Boche, Christian Deppe, Roberto Ferrara, Frank H. P. Fitzek, Gisbert Janssen, and Sajad Saeedinaeeni. Quantum Communication Networks. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62938-0.

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Mehic, Miralem, Stefan Rass, Peppino Fazio, and Miroslav Voznak. Quantum Key Distribution Networks. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06608-5.

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Mastorakis, Nikos E. Networks and quantum computing. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Mahler, Günter. Quantum networks: Dynamics of open nanostructures. Berlin: Springer, 1995.

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Mahler, Günter. Quantum Networks: Dynamics of Open Nanostructures. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998.

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Achim, Weberruss Volker, ed. Quantum networks: Dynamics of open nanostructures. 2nd ed. Berlin: Springer, 1998.

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Strathearn, Aidan. Modelling Non-Markovian Quantum Systems Using Tensor Networks. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54975-6.

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1919-, Pribram Karl H., and Eccles, John C. Sir, 1903-, eds. Rethinking neural networks: Quantum fields and biological data. Hillsdale, N.J: Erlbaum, 1993.

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Book chapters on the topic "Quantum Networks"

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James, Matthew R. "Quantum Networks." In Encyclopedia of Systems and Control, 1–8. London: Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-5102-9_100162-1.

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Dowling, Jonathan P. "Quantum Networks." In Schrödinger’s Web, 207–53. Boca Raton : CRC Press, [2020]: CRC Press, 2020. http://dx.doi.org/10.1201/9780367337629-6.

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James, Matthew R. "Quantum Networks." In Encyclopedia of Systems and Control, 1800–1807. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_100162.

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Sawerwain, Marek, and Joanna Wiśniewska. "Quantum Coherence Measures for Quantum Switch." In Computer Networks, 130–41. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92459-5_11.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Statics." In Quantum Networks, 33–185. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03669-3_2.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Dynamics." In Quantum Networks, 187–321. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03669-3_3.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Stochastics." In Quantum Networks, 323–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03669-3_4.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Statics." In Quantum Networks, 31–169. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03176-6_2.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Dynamics." In Quantum Networks, 171–305. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03176-6_3.

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Mahler, Günter, and Volker A. Weberruß. "Quantum Stochastics." In Quantum Networks, 307–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03176-6_4.

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Conference papers on the topic "Quantum Networks"

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Castillo-Veneros, Leonardo, Dounan Du, Dillion Cottrill, Guo-Dong Cui, Dimitrios Katramatos, Julián Martínez-Rincón, Paul Stankus, and Eden Figueroa. "Development of an Experimentally-Inspired Quantum Internet Stack." In Quantum 2.0. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/quantum.2023.qtu3a.16.

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We present a bottom-up design of a Quantum Internet stack. Our concept is based on a quantum/classical approach combining three optical networks: quantum, quantum-enabling, and classical dictating a tripartite stack with individual layers matching each network’s functionality but acting as a whole to enable the overall network operations.
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Johnson, Spencer J., Prajit Dhara, Alexander Lohrmann, Makan Mohageg, Saikat Guha, and Paul G. Kwiat. "Noise Modeling for Entanglement-Swapping Quantum Networks." In Quantum 2.0. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/quantum.2023.qtu3a.30.

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Future quantum networks will require high-fidelity entanglement swapping at fast rates to connect distant nodes. We present a generalizable network model for memoryless entanglement swapping accounting for noise from imperfect sources, links, and detectors.
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Piparo, Nicolo Lo, Michael Hanks, Kae Nemoto, and William J. Munro. "Aggregating Quantum Networks." In Photonic Networks and Devices. Washington, D.C.: OSA, 2021. http://dx.doi.org/10.1364/networks.2021.neth1b.2.

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Martin, V., A. Aguado, P. Salas, A. L. Sanz, J. P. Brito, D. R. Lopez, V. Lopez, et al. "The Madrid Quantum Network: A Quantum-Classical Integrated Infrastructure." In Photonic Networks and Devices. Washington, D.C.: OSA, 2019. http://dx.doi.org/10.1364/networks.2019.qtw3e.5.

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Kauffman, Louis H., and Sam J. Lomonaco. "Quantum diagrams and quantum networks." In SPIE Sensing Technology + Applications, edited by Eric Donkor, Andrew R. Pirich, Howard E. Brandt, Michael R. Frey, Samuel J. Lomonaco, and John M. Myers. SPIE, 2014. http://dx.doi.org/10.1117/12.2051265.

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Nemoto, Kae. "Aggregation in quantum networks." In Quantum Communications and Quantum Imaging XIX, edited by Keith S. Deacon and Ronald E. Meyers. SPIE, 2021. http://dx.doi.org/10.1117/12.2597326.

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Luong, David, and Bhashyam Balaji. "Quantum radar, quantum networks, not-so-quantum hackers." In Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII, edited by Lynne L. Grewe, Erik P. Blasch, and Ivan Kadar. SPIE, 2019. http://dx.doi.org/10.1117/12.2519453.

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Dhara, Prajit, Dirk R. Englund, and Saikat Guha. "Entangling Quantum Memories via Heralded Photonic Bell Measurement." In Quantum 2.0. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/quantum.2023.qm4c.7.

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We evaluate the quality of entangled states generated on quantum network links based on entanglement swapping. Network non-idealities in conjunction with physi-cal memory decoherence models are incorporated to demonstrate encoding trade-offs and limitations for quantum networks.
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Kimble, H. Jeff. "Quantum networks enabled by quantum optics." In 2013 Conference on Lasers & Electro-Optics Europe & International Quantum Electronics Conference CLEO EUROPE/IQEC. IEEE, 2013. http://dx.doi.org/10.1109/cleoe-iqec.2013.6801689.

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Kim, Je-Hyung, Christopher J. K. Richardson, Richard P. Leavitt, and Edo Waks. "Semiconductor quantum networks using quantum dots." In 2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS). IEEE, 2017. http://dx.doi.org/10.23919/ursigass.2017.8105102.

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Reports on the topic "Quantum Networks"

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Allende López, Marcos, Diego López, Sergio Cerón, Antonio Leal, Adrián Pareja, Marcelo Da Silva, Alejandro Pardo, et al. Quantum-Resistance in Blockchain Networks. Inter-American Development Bank, June 2021. http://dx.doi.org/10.18235/0003313.

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This paper describes the work carried out by the Inter-American Development Bank, the IDB Lab, LACChain, Cambridge Quantum Computing (CQC), and Tecnológico de Monterrey to identify and eliminate quantum threats in blockchain networks. The advent of quantum computing threatens internet protocols and blockchain networks because they utilize non-quantum resistant cryptographic algorithms. When quantum computers become robust enough to run Shor's algorithm on a large scale, the most used asymmetric algorithms, utilized for digital signatures and message encryption, such as RSA, (EC)DSA, and (EC)DH, will be no longer secure. Quantum computers will be able to break them within a short period of time. Similarly, Grover's algorithm concedes a quadratic advantage for mining blocks in certain consensus protocols such as proof of work. Today, there are hundreds of billions of dollars denominated in cryptocurrencies that rely on blockchain ledgers as well as the thousands of blockchain-based applications storing value in blockchain networks. Cryptocurrencies and blockchain-based applications require solutions that guarantee quantum resistance in order to preserve the integrity of data and assets in their public and immutable ledgers. We have designed and developed a layer-two solution to secure the exchange of information between blockchain nodes over the internet and introduced a second signature in transactions using post-quantum keys. Our versatile solution can be applied to any blockchain network. In our implementation, quantum entropy was provided via the IronBridge Platform from CQC and we used LACChain Besu as the blockchain network.
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Allara, David L., and Brosl Hasslacher. Quantum Random Networks for Type 2 Quantum Computers. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada463556.

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Farhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, December 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.

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We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence of parameter dependent unitary transformations which acts on an input quantum state. For binary classification a single Pauli operator is measured on a designated readout qubit. The measured output is the quantum neural network’s predictor of the binary label of the input state. We show through classical simulation that parameters can be found that allow the QNN to learn to correctly distinguish the two data sets. We then discuss presenting the data as quantum superpositions of computational basis states corresponding to different label values. Here we show through simulation that learning is possible. We consider using our QNN to learn the label of a general quantum state. By example we show that this can be done. Our work is exploratory and relies on the classical simulation of small quantum systems. The QNN proposed here was designed with near-term quantum processors in mind. Therefore it will be possible to run this QNN on a near term gate model quantum computer where its power can be explored beyond what can be explored with simulation.
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Spentzouris, Panagiotis, and Wenji Wu. Illinois-Express Quantum Networks (IEQNET). Office of Scientific and Technical Information (OSTI), April 2020. http://dx.doi.org/10.2172/1616300.

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Lorente, Miguel. Spin Networks in Quantum Gravity. Journal of Geometry and Symmetry in Physics, 2012. http://dx.doi.org/10.7546/jgsp-6-2006-85-100.

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Ryan, Duncan Patrick. Energy Flow through Quantum Dot Networks. Office of Scientific and Technical Information (OSTI), June 2018. http://dx.doi.org/10.2172/1441357.

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Harris, James S. Quantum Well Devices for Photonic Networks. Fort Belvoir, VA: Defense Technical Information Center, October 1999. http://dx.doi.org/10.21236/ada378985.

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Raychev, Nikolay. Precision modeling of applied quantum neural networks. Web of Open Science, April 2020. http://dx.doi.org/10.37686/ser.v1i1.25.

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Ndousse-Fetter, Thomas, Nicholas A. Peters, Warren P. Grice, Prem Kumar, Thomas Chapuran, Saikat Guha, Scott Hamilton, et al. Quantum Networks for Open Science (QNOS) Workshop. Office of Scientific and Technical Information (OSTI), April 2019. http://dx.doi.org/10.2172/1510580.

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Ortiz Marrero, Carlos, Nathan Wiebe, James Furches, and Michael Ragone. Quantum Neural Networks: Issues, Training, and Applications. Office of Scientific and Technical Information (OSTI), September 2023. http://dx.doi.org/10.2172/2337965.

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