Application range of crosstalk-affected spatial demultiplexing for
resolving separations between unbalanced sources
- URL: http://arxiv.org/abs/2211.09157v2
- Date: Sat, 30 Sep 2023 09:32:52 GMT
- Title: Application range of crosstalk-affected spatial demultiplexing for
resolving separations between unbalanced sources
- Authors: Tomasz Linowski, Konrad Schlichtholz, Giacomo Sorelli, Manuel Gessner,
Mattia Walschaers, Nicolas Treps, {\L}ukasz Rudnicki
- Abstract summary: We show that for an idealized case of two balanced sources, SPADE achieves resolution better than direct imaging even in the presence of measurement crosstalk.
For realistic values of crosstalk strength, SPADE is still the superior method for several orders of magnitude of source separations.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Superresolution is one of the key issues at the crossroads of contemporary
quantum optics and metrology. Recently, it was shown that for an idealized case
of two balanced sources, spatial mode demultiplexing (SPADE) achieves
resolution better than direct imaging even in the presence of measurement
crosstalk [Phys. Rev. Lett. 125, 100501 (2020)]. In this work, we consider
arbitrarily unbalanced sources and provide a systematic analysis of the impact
of crosstalk on the resolution obtained from SPADE. As we dissect, in this
generalized scenario, SPADE's effectiveness depends non-trivially on the
strength of crosstalk, relative brightness and the separation between the
sources. In particular, for any source imbalance, SPADE performs worse than
ideal direct imaging in the asymptotic limit of vanishing source separations.
Nonetheless, for realistic values of crosstalk strength, SPADE is still the
superior method for several orders of magnitude of source separations.
Related papers
- Superresolution in separation estimation between two dynamic incoherent sources using spatial demultiplexing [0.0]
Recently, perfect measurement based on spatial mode demultiplexing (SPADE) in Hermite-Gauss modes allowed one to reach the quantum limit of precision for estimation of separation between two weak incoherent stationary sources.
In this paper, we consider another deviation from the perfect setup by discarding the assumption about the stationarity of the sources.
We formulate a measurement algorithm that allows for the reduction of one parameter for estimation in the stationary sources scenario.
arXiv Detail & Related papers (2024-07-15T07:57:57Z) - Physics-Inspired Degradation Models for Hyperspectral Image Fusion [61.743696362028246]
Most fusion methods solely focus on the fusion algorithm itself and overlook the degradation models.
We propose physics-inspired degradation models (PIDM) to model the degradation of LR-HSI and HR-MSI.
Our proposed PIDM can boost the fusion performance of existing fusion methods in practical scenarios.
arXiv Detail & Related papers (2024-02-04T09:07:28Z) - Single-photon sub-Rayleigh precision measurements of a pair of
incoherent sources of unequal intensity [0.0]
We consider single-photon imaging of two point-like emitters of unequal intensity.
We employ multi-plane light conversion technology to experimentally implement Hermite-Gaussian spatial-mode demultiplexing.
arXiv Detail & Related papers (2023-09-05T14:58:34Z) - Quantum super-resolution for imaging two pointlike entangled photon
sources [9.590696922408775]
We investigate the resolution for imaging two pointlike entangled sources by using the method of the moments and the spatial-mode demultiplexing (SPADE)
We demonstrate that the separation estimation sensitivity is mainly determined by the photon distribution in each detected modes.
In the limiting case of infinitely small source separation, the usage of entangled sources can have better resolution than those using incoherent and coherent sources.
arXiv Detail & Related papers (2023-06-17T02:39:47Z) - Optimal Condition Training for Target Source Separation [56.86138859538063]
We propose a new optimal condition training method for single-channel target source separation.
We show that the complementary information carried by the diverse semantic concepts significantly helps to disentangle and isolate sources of interest.
arXiv Detail & Related papers (2022-11-11T00:04:55Z) - Exploiting Temporal Structures of Cyclostationary Signals for
Data-Driven Single-Channel Source Separation [98.95383921866096]
We study the problem of single-channel source separation (SCSS)
We focus on cyclostationary signals, which are particularly suitable in a variety of application domains.
We propose a deep learning approach using a U-Net architecture, which is competitive with the minimum MSE estimator.
arXiv Detail & Related papers (2022-08-22T14:04:56Z) - Degradation-agnostic Correspondence from Resolution-asymmetric Stereo [96.03964515969652]
We study the problem of stereo matching from a pair of images with different resolutions, e.g., those acquired with a tele-wide camera system.
We propose to impose the consistency between two views in a feature space instead of the image space, named feature-metric consistency.
We find that, although a stereo matching network trained with the photometric loss is not optimal, its feature extractor can produce degradation-agnostic and matching-specific features.
arXiv Detail & Related papers (2022-04-04T12:24:34Z) - Super-resolution of two unbalanced point sources assisted by the
entangled partner [0.0]
Sub-diffraction-limit resolution, or super-resolution, has been successfully demonstrated for two-point sources with ideal equal-brightness and strict incoherenceness.
We consider practical situations of either non-equal brightness (i.e., unbalancenss) or partial coherence to have fatal effects on resolution precision.
We find that the two negative effects can counter affect each other, thus permitting credible super-resolution, when the measurement is analyzed in the entangled partner's rotated basis.
arXiv Detail & Related papers (2021-12-03T05:33:13Z) - False Correlation Reduction for Offline Reinforcement Learning [115.11954432080749]
We propose falSe COrrelation REduction (SCORE) for offline RL, a practically effective and theoretically provable algorithm.
We empirically show that SCORE achieves the SoTA performance with 3.1x acceleration on various tasks in a standard benchmark (D4RL)
arXiv Detail & Related papers (2021-10-24T15:34:03Z) - Back to sources -- the role of losses and coherence in super-resolution
imaging revisited [0.0]
We compute the Quantum Fisher Information for the generic model of optical 4f imaging system.
We prove that the spatial-mode demultiplexing measurement, optimal for non-coherent sources, remains optimal for an arbitrary degree of coherence.
arXiv Detail & Related papers (2021-03-22T18:00:32Z) - Resource Allocation via Model-Free Deep Learning in Free Space Optical
Communications [119.81868223344173]
The paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications.
Under this framework, we propose two algorithms that solve FSO resource allocation problems.
arXiv Detail & Related papers (2020-07-27T17:38:51Z)
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.