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Global Sky Model for LOFAR and MSSS catalog A. Mints Hamburger Sternwarte September 21, 2012 A. Mints, Global Sky Model for LOFAR and MSSS catalog 1 / 13
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Page 1: LOFAR Global Sky Model database

Global Sky Model for LOFAR andMSSS catalog

A. Mints

Hamburger Sternwarte

September 21, 2012

A. Mints, Global Sky Model for LOFAR and MSSS catalog 1 / 13

Page 2: LOFAR Global Sky Model database

Global Sky Model Data Flow

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Page 3: LOFAR Global Sky Model database

GSM components

DatabaseI Storage only (all logic in the pipeline);

I MonetDB or PostgreSQL support;

PipelinePython code with unified database binding.

Front-ends (planned)I Web-interface;

I Python API;

I Direct DB access;

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Data

Observations (pyBDSM output)Time, frequency, Stokes parameter, position(+size/orientation), peak/total flux, errors.

Catalogrunningcatalog Position, spectral parameters,classification, errors, (+Frequency, Stokesparameter, size/orientation).runningcatalog fluxes Frequency, Stokesparameter, peak/total flux, errors

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Point and extended sources

Point sources1 record in positions table and N records in fluxestable.

Extended sourcesN+1 record in positions table and N records influxes table.

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Matching

Matching criteria for point sources is based on deRuiter distance:

R2deRuiter =

(α1 cos δ1 − α2 cos δ2)2

(∆α1)2 + (∆α2)2+

(δ1 − δ2)2

(∆δ1)2 + (∆δ2)2

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Extended source matching

1. Search for a match in the same band;

2. If 1. failed – search for a cross-band match.

R∗2deRuiter =

(α1 cos δ1 − α2 cos δ2)2 + (δ1 − δ2)2

g 2major ,1 + g 2

major ,2

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Page 8: LOFAR Global Sky Model database

First snapshot

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-1 0 1 2 3 4 5 6

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Second snapshot

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-1 0 1 2 3 4 5 6

1

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34

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Resolved source

For point sources a “flux splitting” technique isapplied.

For extended sources flux splitting is applied onlyat per-band level.

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Page 11: LOFAR Global Sky Model database

Merged source

In this case the nearest source is chosen.Exception: extended sources are merged if possible:

A1, 2, 3 + B5, 6, 7 + X4 = A1, 2, 3, 4, 5, 6, 7 (1)

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Groups

Assigned a unique group ID(all detections in the group).

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Code features

I Coding style: Python PEP8 style rules;

I In-code documentation (docstrings);

I Unit testing (34 tests unified forMonetDB/PostgreSQL);

I SQL mini-preprocessor:1. Queries stored in SQL-file, called by unique Id;2. Parameters can be passed;3. Global parameters can be set;4. Arbitrary Python-code can be called and result

substituted:

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