English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Optimal estimation of signal amplitude, background level, and photocentrelocation is crucial to the combined extraction of astrometric and photometricinformation from focal plane images, and in particular from the one-dimensionalmeasurements performed by Gaia on intermediate to faint magnitude stars. Ourgoal is to define a convenient maximum likelihood framework, suited toefficient iterative implementation and to assessment of noise level, bias, andcorrelation among variables. The analytical model is investigated numericallyand verified by simulation over a range of magnitude and background values. Theestimates are unbiased, with a well-understood correlation between amplitudeand background, and with a much lower correlation of either of them withlocation, further alleviated in case of signal symmetry. Two versions of thealgorithm are implemented and tested against each other, respectively, forindependent and combined parameter estimation. Both are effective and provideconsistent results, but the latter is more efficient because it takes intoaccount the flux-background estimate correlation.

Performance of an Algorithm for Estimation of Flux, Background and Location on One-Dimensional Signals