Consistency check of automatic pipeline measurements of quasar redshifts with Bayesian convolutional networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00362346" target="_blank" >RIV/68407700:21240/23:00362346 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Consistency check of automatic pipeline measurements of quasar redshifts with Bayesian convolutional networks

Original language description

Spectroscopic redshifts of quasars are important inputs for constructing many cosmological models. Redshift measurement is generally considered to be a straightforward task performed by automatic pipelines based on template matching. Due to the millions of spectra delivered by surveys of SDSS or LAMOST telescopes, it is impossible to verify all redshift measurements of automatic pipelines by a human visual inspection. However, the pipeline results are still taken as the "ground truth" for further statistical inferences. Nevertheless, because of the similarity of patterns of quasar emission lines in different spectral ranges, an optimal match may be found for a completely different template position, causing severe errors in the measured redshift. For example, it may easily happen that a faint emission star with a noisy spectrum is identified as a high redshift quasar and vice versa. We show such examples discovered by the consistency check of redshift measurements of the SDSS pipeline and redshift predictions of a regression Bayesian convolutional network. The network is trained on a large amount of human-inspected redshifts and predicts redshifts together with their predictive uncertainties. Therefore, it can also identify cases where predictions are uncertain and thus require human visual inspection.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Astronomical Data Analysis Software and Systems XXXII

ISBN

978-1-58381-964-7

ISSN

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e-ISSN

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Number of pages

4

Pages from-to

134-137

Publisher name

Astronomical Society of the Pacific

Place of publication

San Francisco

Event location

Victoria

Event date

Oct 31, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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