Enhanced Quantum Key Distribution using Hybrid Channels and Natural Random Numbers

• URL: http://arxiv.org/abs/2007.14298v1
• Date: Tue, 28 Jul 2020 15:14:59 GMT
• Title: Enhanced Quantum Key Distribution using Hybrid Channels and Natural Random Numbers
• Authors: Hemant Rana, Nitin Verma
• Abstract summary: We propose three secure key distribution protocols based on a blend of classical and quantum channels. The proposed protocols exploits the property of quantum computers to generate natural random numbers that can be easily transmitted.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Since the introduction of quantum computation by Richard Feynman in 1982, Quantum computation has shown exemplary results in various applications of computer science including unstructured database search, factorization, molecular simulations to name a few. Some of the recent developments include quantum machine learning, quantum neural networks, quantum walks on graphs, fault tolerant scalable quantum computers using error correction codes etc. One of the crucial modern applications of quantum information is quantum cryptography and secure key distribution over quantum channels which have several advantages over classical channels, especially detection of eavesdropping. Based on such properties of quantum systems and quantum channels, In this paper we propose three secure key distribution protocols based on a blend of classical and quantum channels. Also the proposed protocols exploits the property of quantum computers to generate natural random numbers that can be easily transmitted using a single qubit over a quantum channel and can be used for distributing keys to the involved parties in a communication network.

Related papers

• Guarantees on the structure of experimental quantum networks [109.08741987555818]
  Quantum networks connect and supply a large number of nodes with multi-party quantum resources for secure communication, networked quantum computing and distributed sensing. As these networks grow in size, certification tools will be required to answer questions regarding their properties. We demonstrate a general method to guarantee that certain correlations cannot be generated in a given quantum network.
  arXiv  Detail & Related papers  (2024-03-04T19:00:00Z)
• A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity [50.387179833629254]
  We introduce a collaborative classical-quantum architecture called co-TenQu. Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting. It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
  arXiv  Detail & Related papers  (2024-02-23T14:09:41Z)
• Entanglement-Assisted Quantum Networks: Mechanics, Enabling Technologies, Challenges, and Research Directions [66.27337498864556]
  This paper presents a comprehensive survey of entanglement-assisted quantum networks. It provides a detailed overview of the network structure, working principles, and development stages. It also emphasizes open research directions, including architecture design, entanglement-based network issues, and standardization.
  arXiv  Detail & Related papers  (2023-07-24T02:48:22Z)
• QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks [124.7972093110732]
  We propose quantum graph convolutional networks (QuanGCN), which learns the local message passing among nodes with the sequence of crossing-gate quantum operations. To mitigate the inherent noises from modern quantum devices, we apply sparse constraint to sparsify the nodes' connections. Our QuanGCN is functionally comparable or even superior than the classical algorithms on several benchmark graph datasets.
  arXiv  Detail & Related papers  (2022-11-09T21:43:16Z)
• Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
  We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources. The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
  arXiv  Detail & Related papers  (2022-09-16T02:37:32Z)
• Machine learning applications for noisy intermediate-scale quantum computers [0.0]
  We develop and study three quantum machine learning applications suitable for NISQ computers. These algorithms are variational in nature and use parameterised quantum circuits (PQCs) as the underlying quantum machine learning model. We propose a variational algorithm in the area of approximate quantum cloning, where the data becomes quantum in nature.
  arXiv  Detail & Related papers  (2022-05-19T09:26:57Z)
• A prototype of quantum von Neumann architecture [0.0]
  We propose a model of universal quantum computer system, the quantum version of the von Neumann architecture. It uses ebits as elements of the quantum memory unit, and qubits as elements of the quantum control unit and processing unit. Our primary study demonstrates the manifold power of quantum information and paves the way for the creation of quantum computer systems.
  arXiv  Detail & Related papers  (2021-12-17T06:33:31Z)
• Probably approximately correct quantum source coding [0.0]
  Holevo's and Nayak's bounds give an estimate of the amount of classical information that can be stored in a quantum state. We show two novel applications in quantum learning theory and delegated quantum computation with a purely classical client.
  arXiv  Detail & Related papers  (2021-12-13T17:57:30Z)
• Quantum Federated Learning with Quantum Data [87.49715898878858]
  Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems. This paper proposes the first fully quantum federated learning framework that can operate over quantum data and, thus, share the learning of quantum circuit parameters in a decentralized manner.
  arXiv  Detail & Related papers  (2021-05-30T12:19:27Z)
• Realising and compressing quantum circuits with quantum reservoir computing [2.834895018689047]
  We show how a random network of quantum nodes can be used as a robust hardware for quantum computing. Our network architecture induces quantum operations by optimising only a single layer of quantum nodes. In the few-qubit regime, sequences of multiple quantum gates in quantum circuits can be compressed with a single operation.
  arXiv  Detail & Related papers  (2020-03-21T03:29:16Z)
• Quantum key distribution based on the quantum eraser [0.0]
  Quantum information and quantum foundations are becoming popular topics for advanced undergraduate courses. We show that the quantum eraser, usually used to study the duality between wave and particle properties, can also serve as a generic platform for quantum key distribution.
  arXiv  Detail & Related papers  (2019-07-07T10:00:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.