Temporal limitations and digital data processing in continuous variable measurements of non-Gaussian states

• URL: http://arxiv.org/abs/2603.09698v1
• Date: Tue, 10 Mar 2026 14:05:58 GMT
• Title: Temporal limitations and digital data processing in continuous variable measurements of non-Gaussian states
• Abstract summary: We study how the temporal performances of the detection chain affect the acquisition and treatment of tomographic data.<n>This allows understanding how these features impact the quality of quantum states observed by non-ideal detection chains.
• Score: 30.5491665195957
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Non-Gaussian quantum states and operations are essential tools for multiple quantum information protocols exploiting light as information career. In this context, a key role is played by schemes operating with continuous wave light, in which non-Gaussian states are obtained by photon subtraction/addition and eventually reconstructed by quantum state tomography. In these configurations, the temporal resolution of the homodyne detection and the digital data processing critically affect our ability to faithfully reconstruct the produced non-Gaussian states. In this work, we apply digital data processing to experimental data to study how the temporal performances of the detection chain affect the acquisition and treatment of tomographic data. This allows understanding how these features impact the quality of quantum states observed by non-ideal detection chains. By doing so, we discuss the actual constraints on the acquisition and reconstruction of non-Gaussian states by taking into account the limitations of realistic experimental resources.

Related papers

• Error-mitigated quantum state tomography using neural networks [1.8586091121463546]
  We propose a scalable tomography method based on multilayer perceptron networks that mitigate unknown noise through supervised learning.<n>The proposed method effectively mitigates noise across a broad range of scenarios, compared with the case without mitigation.
  arXiv  Detail & Related papers  (2026-02-10T12:42:23Z)
• Minimal Quantum Reservoirs with Hamiltonian Encoding [72.27323884094953]
  We investigate a minimal architecture for quantum reservoir computing based on Hamiltonian encoding.<n>This approach circumvents many of the experimental overheads typically associated with quantum machine learning.
  arXiv  Detail & Related papers  (2025-05-28T16:50:05Z)
• Enhanced frequency estimation by non-Gaussianity of Fock states [0.0]
  We investigate the impact of non-Gaussianity on the precision of frequency estimation using a quantum probe.<n>Our results demonstrate a significant enhancement in the quantum Fisher information for non-Gaussian states.
  arXiv  Detail & Related papers  (2025-05-20T20:01:09Z)
• Detecting genuine non-Gaussian entanglement [0.0]
  Non-Gaussian entanglement is a central challenge for advancing quantum information processing, photonic quantum computing, and metrology.<n>Here, we put forward continuous-variable counterparts of the recently introduced entanglement criteria based on moments of the partially transposed state.<n>Our multicopy method enables the detection of genuine non-Gaussian entanglement for various relevant state families overlooked by standard approaches.
  arXiv  Detail & Related papers  (2025-04-22T12:22:30Z)
• Learning quantum states of continuous variable systems [4.05533173496439]
  Quantum state tomography is aimed at deriving a classical description of an unknown state from measurement data. We prove that tomography of continuous-variable systems is extremely inefficient in terms of time resources. We also prove that tomography of Gaussian states is efficient.
  arXiv  Detail & Related papers  (2024-05-02T16:19:55Z)
• Correlation-pattern-based Continuous-variable Entanglement Detection through Neural Networks [1.5091188291530049]
  Entanglement in continuous-variable non-Gaussian states provides irreplaceable advantages in many quantum information tasks. We develop a neural network that allows us to use correlation patterns to effectively detect continuous-variable entanglement.
  arXiv  Detail & Related papers  (2023-10-31T16:00:25Z)
• Measurement-induced entanglement and teleportation on a noisy quantum processor [105.44548669906976]
  We investigate measurement-induced quantum information phases on up to 70 superconducting qubits. We use a duality mapping, to avoid mid-circuit measurement and access different manifestations of the underlying phases. Our work demonstrates an approach to realize measurement-induced physics at scales that are at the limits of current NISQ processors.
  arXiv  Detail & Related papers  (2023-03-08T18:41:53Z)
• Characterizing quantum instruments: from non-demolition measurements to quantum error correction [48.43720700248091]
  In quantum information processing quantum operations are often processed alongside measurements which result in classical data. Non-unitary dynamical processes can take place on the system, for which common quantum channel descriptions fail to describe the time evolution. Quantum measurements are correctly treated by means of so-called quantum instruments capturing both classical outputs and post-measurement quantum states.
  arXiv  Detail & Related papers  (2021-10-13T18:00:13Z)
• 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)
• Continuous-time dynamics and error scaling of noisy highly-entangling quantum circuits [58.720142291102135]
  We simulate a noisy quantum Fourier transform processor with up to 21 qubits. We take into account microscopic dissipative processes rather than relying on digital error models. We show that depending on the dissipative mechanisms at play, the choice of input state has a strong impact on the performance of the quantum algorithm.
  arXiv  Detail & Related papers  (2021-02-08T14:55:44Z)
• 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.