基于Fisher信息矩阵的点扩散函数拟合半径对光度不确定度的影响

IF 5.8 2区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
Sebastian Espinosa, Mario L. Vicuña, Rene A. Mendez, Jorge F. Silva, Marcos Orchard
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引用次数: 0

摘要

上下文。在点扩散函数(PSF)测光中,拟合孔径半径的选择对通量和背景估计精度起着至关重要的作用。传统的方法往往依赖于最大化信噪比(S/N)作为孔径选择的标准。然而,基于S/ n的方法并不一定能为联合估计问题提供最佳精度,因为它们没有考虑到cram - rao下界(CRLB)背景下Fisher信息施加的统计限制。本研究旨在建立一种基于Fisher信息而非信噪比选择最优拟合半径的替代准则。费雪信息是估计精度的基本度量,为参数估计可达到的精度提供了理论保证。通过利用Fisher信息,我们试图定义一种孔径选择策略,使精度损失最小化。我们进行了一系列数值实验,分析了费雪信息的行为和估计器的性能作为PSF孔径半径的函数。具体来说,我们重新审视了基本的光度模型,并探讨了孔径大小与信息含量之间的关系。我们比较了经典估计量的经验方差,如最大似然和随机加权最小二乘,与由Fisher信息矩阵导出的理论CRLB。结果表明,基于Fisher信息的孔径选择为获得最佳估计精度提供了一个更稳健的框架。研究结果表明,基于S/ n的孔径选择可能导致显著的差异,潜在的精度损失高达70%。相比之下,Fisher基于信息的选择允许更准确和一致的估计过程,确保经验方差与理论极限紧密一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of the point spread function fitting radius on photometric uncertainty based on the Fisher information matrix
Context. In point spread function (PSF) photometry, the selection of the fitting aperture radius plays a critical role in determining the precision of flux and background estimations. Traditional methods often rely on maximizing the signal-to-noise ratio (S/N) as a criterion for aperture selection. However, S/N-based approaches do not necessarily provide the optimal precision for joint estimation problems as they do not account for the statistical limits imposed by the Fisher information in the context of the Cramér-Rao lower bound (CRLB).Aims. This study aims to establish an alternative criterion for selecting the optimal fitting radius based on Fisher information rather than S/N. Fisher information serves as a fundamental measure of estimation precision, providing theoretical guarantees on the achievable accuracy for parameter estimation. By leveraging Fisher information, we seek to define an aperture selection strategy that minimizes the loss of precision.Methods. We conducted a series of numerical experiments that analyze the behavior of Fisher information and estimator performance as a function of the PSF aperture radius. Specifically, we revisited fundamental photometric models and explored the relationship between aperture size and information content. We compared the empirical variance of classical estimators, such as maximum likeli-hood and stochastic weighted least squares, against the theoretical CRLB derived from the Fisher information matrix.Results. Our results indicate that aperture selection based on the Fisher information provides a more robust framework for achieving optimal estimation precision. The findings reveal that S/N-based aperture selection may lead to significant discrepancies, with potential precision losses of up to 70%. In contrast, Fisher information-based selection allows a more accurate and consistent estimation process, ensuring that the empirical variance closely aligns with the theoretical limits.
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来源期刊
Astronomy & Astrophysics
Astronomy & Astrophysics 地学天文-天文与天体物理
CiteScore
10.20
自引率
27.70%
发文量
2105
审稿时长
1-2 weeks
期刊介绍: Astronomy & Astrophysics is an international Journal that publishes papers on all aspects of astronomy and astrophysics (theoretical, observational, and instrumental) independently of the techniques used to obtain the results.
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