Sample-efficient adaptive calibration of quantum networks using Bayesian optimization

• URL: http://arxiv.org/abs/2106.06113v1
• Date: Fri, 11 Jun 2021 01:35:04 GMT
• Title: Sample-efficient adaptive calibration of quantum networks using Bayesian optimization
• Authors: Cristian L. Cortes, Pascal Lefebvre, Nikolai Lauk, Michael J. Davis, Neil Sinclair, Stephen K. Gray, and Daniel Oblak
• Abstract summary: Indistinguishable photons are imperative for advanced quantum communication networks. Indistinguishability is difficult to obtain because of environment-induced photon transformations and loss imparted by communication channels. We propose and develop resource-efficient Bayesian optimization techniques to rapidly calibrate the indistinguishability of individual photons for quantum networks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Indistinguishable photons are imperative for advanced quantum communication networks. Indistinguishability is difficult to obtain because of environment-induced photon transformations and loss imparted by communication channels, especially in noisy scenarios. Strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g. adding noise), infeasible (e.g. on a satellite), or time-consuming for deployed networks. Here we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons -- a central task in quantum networking -- finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.

Related papers

• A Hybrid Approach to Mitigate Errors in Linear Photonic Bell-State Measurement for Quantum Interconnects [0.0]
  We introduce a novel hybrid detection scheme for Bell-state measurement. We derive explicit fidelities for quantum teleportation and entanglement swapping processes. This work provides a new tool for linear optics schemes, with applications to quantum state engineering and quantum interconnects.
  arXiv  Detail & Related papers  (2024-06-14T18:00:00Z)
• Near-Term Distributed Quantum Computation using Mean-Field Corrections and Auxiliary Qubits [77.04894470683776]
  We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production. We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
  arXiv  Detail & Related papers  (2023-09-11T18:00:00Z)
• Quantum time transfer: a practical method for lossy and noisy channels [0.0]
  This article explores the utility of low-performance quantum-photon sources for quantum networking. It provides picosecond-level timing precision even under high loss and high noise channel conditions representative of daytime space-Earth links. This method is relevant for daytime space-Earth quantum networking and/or providing high-precision secure timing in GPS denied environments.
  arXiv  Detail & Related papers  (2022-11-01T20:33:52Z)
• On-chip quantum information processing with distinguishable photons [55.41644538483948]
  Multi-photon interference is at the heart of photonic quantum technologies. Here, we experimentally demonstrate that detection can be implemented with a temporal resolution sufficient to interfere photons detuned on the scales necessary for cavity-based integrated photon sources. We show how time-resolved detection of non-ideal photons can be used to improve the fidelity of an entangling operation and to mitigate the reduction of computational complexity in boson sampling experiments.
  arXiv  Detail & Related papers  (2022-10-14T18:16:49Z)
• Amplification of cascaded downconversion by reusing photons with a switchable cavity [62.997667081978825]
  We propose a scheme to amplify triplet production rates by using a fast switch and a delay loop. Our proof-of-concept device increases the rate of detected photon triplets as predicted.
  arXiv  Detail & Related papers  (2022-09-23T15:53:44Z)
• Switch networks for photonic fusion-based quantum computing [0.0]
  Fusion-based quantum computing (FBQC) offers a powerful approach to building a fault-tolerant universal quantum computer. FBQC uses single-photon sources, linear-optical circuits, single-photon detectors, and optical switching with feedforward control. New techniques and schemes enable major improvements in terms of muxing efficiency and reductions in hardware requirements.
  arXiv  Detail & Related papers  (2021-09-28T14:31:30Z)
• Entanglement Rate Optimization in Heterogeneous Quantum Communication Networks [79.8886946157912]
  Quantum communication networks are emerging as a promising technology that could constitute a key building block in future communication networks in the 6G era and beyond. Recent advances led to the deployment of small- and large-scale quantum communication networks with real quantum hardware. In quantum networks, entanglement is a key resource that allows for data transmission between different nodes.
  arXiv  Detail & Related papers  (2021-05-30T11:34:23Z)
• Conditional preparation of non-Gaussian quantum optical states by mesoscopic measurement [62.997667081978825]
  Non-Gaussian states of an optical field are important as a proposed resource in quantum information applications. We propose a novel approach involving displacement of the ancilla field into the regime where mesoscopic detectors can be used. We conclude that states with strong Wigner negativity can be prepared at high rates by this technique under experimentally attainable conditions.
  arXiv  Detail & Related papers  (2021-03-29T16:59:18Z)
• Rapid characterisation of linear-optical networks via PhaseLift [51.03305009278831]
  Integrated photonics offers great phase-stability and can rely on the large scale manufacturability provided by the semiconductor industry. New devices, based on such optical circuits, hold the promise of faster and energy-efficient computations in machine learning applications. We present a novel technique to reconstruct the transfer matrix of linear optical networks.
  arXiv  Detail & Related papers  (2020-10-01T16:04:22Z)
• Spatial Mode Correction of Single Photons using Machine Learning [1.8086378019947618]
  We exploit the self-learning and self-evolving features of artificial neural networks to correct the complex spatial profile of distorted Laguerre-Gaussian modes at the single-photon level. Our results have important implications for real-time turbulence correction of structured photons and single-photon images.
  arXiv  Detail & Related papers  (2020-06-14T01:25:17Z)
• Improving resolution-sensitivity trade off in sub-shot noise imaging [0.0]
  We show how the SSNI protocol can be optimized to significantly improve the resolution without giving up the quantum advantage in the sensitivity. We show a linear resolution improvement (up to a factor 3) with respect to the simple protocol used in previous demonstrations.
  arXiv  Detail & Related papers  (2020-04-01T06:35:42Z)

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.