Quantum Metrological Power of Continuous-Variable Quantum Networks

• URL: http://arxiv.org/abs/2107.14251v4
• Date: Tue, 22 Feb 2022 16:33:56 GMT
• Title: Quantum Metrological Power of Continuous-Variable Quantum Networks
• Authors: Hyukgun Kwon, Youngrong Lim, Liang Jiang, Hyunseok Jeong, and Changhun Oh
• Abstract summary: We show that most continuous-variable quantum networks provide entanglement to quantum states in distant nodes. We numerically demonstrate that even when CV quantum networks are composed of local beam splitters, the quantum enhancement can be attained when the depth is sufficiently large.
• Score: 2.175441462022736
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We investigate the quantum metrological power of typical continuous-variable (CV) quantum networks. Particularly, we show that most CV quantum networks provide an entanglement to quantum states in distant nodes that enables one to achieve the Heisenberg scaling in the number of modes for distributed quantum displacement sensing, which cannot be attained using an unentangled probe state. Notably, our scheme only requires local operations and measurements after generating an entangled probe using the quantum network. In addition, we find a tolerable photon-loss rate that maintains the quantum enhancement. Finally, we numerically demonstrate that even when CV quantum networks are composed of local beam splitters, the quantum enhancement can be attained when the depth is sufficiently large.

Related papers

• Distributed Quantum Computation via Entanglement Forging and Teleportation [13.135604356093193]
  Distributed quantum computation is a practical method for large-scale quantum computation on quantum processors with limited size. In this paper, we demonstrate the methods to implement a nonlocal quantum circuit on two quantum processors without any quantum correlations.
  arXiv  Detail & Related papers  (2024-09-04T08:10:40Z)
• The curse of random quantum data [62.24825255497622]
  We quantify the performances of quantum machine learning in the landscape of quantum data. We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits. Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
  arXiv  Detail & Related papers  (2024-08-19T12:18:07Z)
• Enhanced quantum state transfer: Circumventing quantum chaotic behavior [35.74056021340496]
  We show how to transfer few-particle quantum states in a two-dimensional quantum network. Our approach paves the way to short-distance quantum communication for connecting distributed quantum processors or registers.
  arXiv  Detail & Related papers  (2024-02-01T19:00:03Z)
• Robust Parallel Laser Driving of Quantum Dots for Multiplexing of Quantum Light Sources [0.1806830971023738]
  We show the simultaneous triggering of >10 quantum dots using adiabatic rapid passage. We show that high-fidelity quantum state is possible in a system of quantum dots with a 15meV range of optical transition energies.
  arXiv  Detail & Related papers  (2023-11-28T17:32:45Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Quantum Optical Memory for Entanglement Distribution [52.77024349608834]
  Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Over the past two decades, quantum optical memories with high fidelity, high efficiencies, long storage times, and promising multiplexing capabilities have been developed.
  arXiv  Detail & Related papers  (2023-04-19T03:18:51Z)
• Cavity-enhanced quantum network nodes [0.0]
  A future quantum network will consist of quantum processors that are connected by quantum channels. I will describe how optical resonators facilitate quantum network nodes.
  arXiv  Detail & Related papers  (2022-05-30T18:50:35Z)
• Efficient criteria of quantumness for a large system of qubits [58.720142291102135]
  We discuss the dimensionless combinations of basic parameters of large, partially quantum coherent systems. Based on analytical and numerical calculations, we suggest one such number for a system of qubits undergoing adiabatic evolution.
  arXiv  Detail & Related papers  (2021-08-30T23:50:05Z)
• Detecting Quantum Capacities of Continuous-Variable Quantum Channels [0.7614628596146599]
  We introduce a method for detecting the quantum capacity of continuous variable communication channels and memories without performing a full process tomography. Our method works in the general scenario where the devices are used a finite number of times, can exhibit correlations across multiple uses, and can change dynamically under the control of a malicious adversary.
  arXiv  Detail & Related papers  (2021-08-30T16:18:39Z)
• Entanglement transfer, accumulation and retrieval via quantum-walk-based qubit-qudit dynamics [50.591267188664666]
  Generation and control of quantum correlations in high-dimensional systems is a major challenge in the present landscape of quantum technologies. We propose a protocol that is able to attain entangled states of $d$-dimensional systems through a quantum-walk-based it transfer & accumulate mechanism. In particular, we illustrate a possible photonic implementation where the information is encoded in the orbital angular momentum and polarization degrees of freedom of single photons.
  arXiv  Detail & Related papers  (2020-10-14T14:33:34Z)
• Experimental Quantum Generative Adversarial Networks for Image Generation [93.06926114985761]
  We experimentally achieve the learning and generation of real-world hand-written digit images on a superconducting quantum processor. Our work provides guidance for developing advanced quantum generative models on near-term quantum devices.
  arXiv  Detail & Related papers  (2020-10-13T06:57:17Z)

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.