Gaussian quantum metrology for mode-encoded parameters

• URL: http://arxiv.org/abs/2202.10355v2
• Date: Tue, 14 Feb 2023 13:23:23 GMT
• Title: Gaussian quantum metrology for mode-encoded parameters
• Authors: Giacomo Sorelli, Manuel Gessner, Nicolas Treps, and Mattia Walschaers
• Abstract summary: We identify ultimate sensitivity bounds for the estimation parameters encoded into quantum states of the electromagnetic field. We show how the estimation sensitivity can be enhanced by adding squeezing into specific modes.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Quantum optical metrology aims to identify ultimate sensitivity bounds for the estimation of parameters encoded into quantum states of the electromagnetic field. In many practical applications, including imaging, microscopy, and remote sensing, the parameter of interest is not only encoded in the quantum state of the field, but also in its spatio-temporal distribution, i.e. in its mode structure. In this mode-encoded parameter estimation setting, we derive an analytical expression for the quantum Fisher information valid for arbitrary multimode Gaussian fields. To illustrate the power of our approach, we apply our results to the estimation of the transverse displacement of a beam and to the temporal separation between two pulses. For these examples, we show how the estimation sensitivity can be enhanced by adding squeezing into specific modes.

Related papers

• Exploring quantum localization with machine learning [39.58317527488534]
  We introduce an efficient neural network (NN) architecture for classifying wave functions in terms of their localization. Our approach integrates a versatile quantum phase space parametrization leading to a custom 'quantum' NN, with the pattern recognition capabilities of a modified convolutional model.
  arXiv  Detail & Related papers  (2024-06-01T08:50:26Z)
• Universal quantum frequency comb measurements by spectral mode-matching [39.58317527488534]
  We present the first general approach to make arbitrary, one-shot measurements of a multimode quantum optical source. This approach uses spectral mode-matching, which can be understood as interferometry with a memory effect.
  arXiv  Detail & Related papers  (2024-05-28T15:17:21Z)
• Variational quantum metrology for multiparameter estimation under dephasing noise [0.8594140167290099]
  We present a hybrid quantum-classical variational scheme to enhance precision in quantum metrology. We discuss specific applications to 3D magnetic field sensing under several dephasing noise modes.
  arXiv  Detail & Related papers  (2023-05-15T01:09:58Z)
• Variational waveguide QED simulators [58.720142291102135]
  Waveguide QED simulators are made by quantum emitters interacting with one-dimensional photonic band-gap materials. Here, we demonstrate how these interactions can be a resource to develop more efficient variational quantum algorithms.
  arXiv  Detail & Related papers  (2023-02-03T18:55:08Z)
• Neural networks for Bayesian quantum many-body magnetometry [0.0]
  Entangled quantum many-body systems can be used as sensors that enable the estimation of parameters with a precision larger than that achievable with ensembles of individual quantum detectors. This entails a complexity that can hinder the applicability of Bayesian inference techniques. We show how to circumvent these issues by using neural networks that faithfully reproduce the dynamics of quantum many-body sensors.
  arXiv  Detail & Related papers  (2022-12-22T22:13:49Z)
• Retrieving space-dependent polarization transformations via near-optimal quantum process tomography [55.41644538483948]
  We investigate the application of genetic and machine learning approaches to tomographic problems. We find that the neural network-based scheme provides a significant speed-up, that may be critical in applications requiring a characterization in real-time. We expect these results to lay the groundwork for the optimization of tomographic approaches in more general quantum processes.
  arXiv  Detail & Related papers  (2022-10-27T11:37:14Z)
• Estimation of a parameter encoded in the modal structure of a light beam: a quantum theory [0.0]
  Quantum light is described not only by a quantum state but also by the shape of the electromagnetic modes on which the state is defined. Optical precision measurements often estimate a mode parameter'' that determines properties such as frequency, temporal shape and the spatial distribution of the light field. By deriving quantum precision limits, we establish the fundamental bounds for mode parameter estimation.
  arXiv  Detail & Related papers  (2022-01-11T16:53:14Z)
• Numerical Simulations of Noisy Quantum Circuits for Computational Chemistry [51.827942608832025]
  Near-term quantum computers can calculate the ground-state properties of small molecules. We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
  arXiv  Detail & Related papers  (2021-12-31T16:33:10Z)
• Bosonic field digitization for quantum computers [62.997667081978825]
  We address the representation of lattice bosonic fields in a discretized field amplitude basis. We develop methods to predict error scaling and present efficient qubit implementation strategies.
  arXiv  Detail & Related papers  (2021-08-24T15:30:04Z)
• Quantum-limited Localisation and Resolution in Three Dimensions [10.824994978916815]
  We determine the ultimate potential of quantum-limited imaging for improving the resolution of a far-field, diffraction-limited approximation. Our results give the upper bounds on certain far-field imaging technology and will find wide applications from microscopy to astrometry.
  arXiv  Detail & Related papers  (2020-12-09T14:44:56Z)
• Entanglement Enhanced Estimation of a Parameter Embedded in Multiple Phases [1.0828616610785522]
  Quantum-enhanced sensing promises to improve the performance of sensing tasks using non-classical probes and measurements. We propose a distributed distributed sensing framework that uses an entangled quantum probe to estimate a scene- parameter encoded within an array of phases. We apply our framework to examples as diverse as radio-frequency phased-array directional radar, beam-displacement tracking for atomic-force microscopy, and fiber-based temperature gradiometry.
  arXiv  Detail & Related papers  (2020-04-08T17:59:33Z)

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.