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.

Authors

Publication Details

Journal
Astronomy and Astrophysics
Published
2025-09-23
DOI
https://doi.org/10.1051/0004-6361/202555342
Citations
1
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
4.99

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The impact of the point spread function fitting radius on photometric uncertainty based on the Fisher information matrix

Mario L. Vicuña, Marcos E. Orchard, Sebastián Espinosa, Jorge F. Silva et al.
1 citations
Astronomy and Astrophysics
Infrared Target Detection Methodologies
4.99
article

The impact of the point spread function fitting radius on photometric uncertainty based on the Fisher information matrix

Mario L. Vicuña, Marcos E. Orchard, Sebastián Espinosa, Jorge F. Silva, R. A. Méndez
article en
1 citations

Abstract

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.

Astronomy and AstrophysicsVol. 702
Agencia Nacional de Investigación y Desarrollo
Openalex Percentile: Top 5%
Infrared Target Detection Methodologies
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.