Optimized experimental optical tomography of quantum states of room-temperature alkali-metal vapor

• URL: http://arxiv.org/abs/2307.01160v1
• Date: Mon, 3 Jul 2023 17:10:27 GMT
• Title: Optimized experimental optical tomography of quantum states of room-temperature alkali-metal vapor
• Authors: Marek Kopciuch, Magdalena Smolis, Adam Miranowicz, Szymon Pustelny
• Abstract summary: We demonstrate a novel experimental technique for quantum-state tomography of the collective density matrix. It is based on measurements of the polarization of light, traversing the atomic vapor. To assess the technique's robustness against errors, experimental investigations are supported with numerical simulations.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We demonstrate a novel experimental technique for quantum-state tomography of the collective density matrix. It is based on measurements of the polarization of light, traversing the atomic vapor. To assess the technique's robustness against errors, experimental investigations are supported with numerical simulations. This not only allows to determine the fidelity of the reconstruction, but also to analyze the quality of the reconstruction for specific experimental parameters light tuning and number of measurements). By utilizing the so-called conditional number, we demonstrate that the reconstruction can be optimized for a specific tuning of the system parameters, and further improvement is possible by selective repetition of the measurements. Our results underscore the potential high-fidelity quantum-state reconstruction while optimizing measurement resources.

Related papers

• Reconstruction of quantum states by applying an analytical optimization model [1.0499611180329804]
  We show that when restricting the measurement sample size, improvement over existing algorithms can be achieved. Our findings underline the multiplicity of solutions in the reconstruction problem, depending upon the generated state and measurement model utilized.
  arXiv  Detail & Related papers  (2025-01-13T15:21:08Z)
• Optimal Allocation of Pauli Measurements for Low-rank Quantum State Tomography [26.844092519401617]
  A key challenge of quantum state tomography (QST) is to find out how the accuracy of the reconstruction depends on the number of state copies used in the measurements. We establish a theoretical understanding of the trade-off between the number of measurement settings and the number of repeated measurements per setting in QST.
  arXiv  Detail & Related papers  (2024-11-07T05:59:04Z)
• Spatial super-resolution in nanosensing with blinking emitters [79.16635054977068]
  We propose a method of spatial resolution enhancement in metrology with blinking fluorescent nanosensors. We believe that blinking fluorescent sensing agents being complemented with the developed image analysis technique could be utilized routinely in the life science sector.
  arXiv  Detail & Related papers  (2024-02-27T10:38:05Z)
• Fourier Quantum Process Tomography [0.0]
  We introduce a new technique, referred to as Fourier Quantum Process Tomography, which requires a reduced number of measurements. We experimentally test the technique on different space-dependent polarization transformations, reporting average fidelities higher than 90%.
  arXiv  Detail & Related papers  (2023-12-20T22:17:56Z)
• Optimised Bayesian system identification in quantum devices [3.72081359624651]
  We present a closed-loop Bayesian learning algorithm for estimating unknown parameters in a dynamical model. We demonstrate the performance of the algorithm in both simulated calibration tasks and in an experimental single-qubit ion-trap system.
  arXiv  Detail & Related papers  (2022-11-16T18:12:46Z)
• 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)
• Multi-Channel Convolutional Analysis Operator Learning for Dual-Energy CT Reconstruction [108.06731611196291]
  We develop a multi-channel convolutional analysis operator learning (MCAOL) method to exploit common spatial features within attenuation images at different energies. We propose an optimization method which jointly reconstructs the attenuation images at low and high energies with a mixed norm regularization on the sparse features.
  arXiv  Detail & Related papers  (2022-03-10T14:22:54Z)
• Regularization by Denoising Sub-sampled Newton Method for Spectral CT Multi-Material Decomposition [78.37855832568569]
  We propose to solve a model-based maximum-a-posterior problem to reconstruct multi-materials images with application to spectral CT. In particular, we propose to solve a regularized optimization problem based on a plug-in image-denoising function. We show numerical and experimental results for spectral CT materials decomposition.
  arXiv  Detail & Related papers  (2021-03-25T15:20:10Z)
• Benchmarking adaptive variational quantum eigensolvers [63.277656713454284]
  We benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves. We find both methods provide good estimates of the energy and ground state. gradient-based optimization is more economical and delivers superior performance than analogous simulations carried out with gradient-frees.
  arXiv  Detail & Related papers  (2020-11-02T19:52:04Z)
• Neural network quantum state tomography in a two-qubit experiment [52.77024349608834]
  Machine learning inspired variational methods provide a promising route towards scalable state characterization for quantum simulators. We benchmark and compare several such approaches by applying them to measured data from an experiment producing two-qubit entangled states. We find that in the presence of experimental imperfections and noise, confining the variational manifold to physical states greatly improves the quality of the reconstructed states.
  arXiv  Detail & Related papers  (2020-07-31T17:25:12Z)

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.