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The LAMOST 1d Spectroscopic Pipeline

This workshop delves into near-field cosmology and galactic archeology, focusing on improving 1D spectroscopic pipelines for classification, measurement, and special candidate identification in the realm of astronomy. Key topics include automated classification, line measurements, and stellar analysis pipelines. Emphasis is placed on spectral analysis, line indices, and relationship mappings for various astronomical objects.

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The LAMOST 1d Spectroscopic Pipeline

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  1. The KIAA-Cambridge Joint Workshop on Near-Field Cosmology and Galactic Archeology The LAMOST 1d Spectroscopic Pipeline A-Li LUO LAMOST team, NAOC 2008/12/3

  2. Lessons from SDSS • Three 1d pipelines of SDSS (template based ) Princeton 1d; Fermi 1d; SEGUE: SSPP • Have been improving from DR1->DR7

  3. Task of 1D pipeline • Classification and Identification • Measurement (z of galaxies and QSOs, rv of stars) • Stellar parameter estimation • Special Candidate searching (Supernovae, Metal-poor stars, HII …) – according to requirements of astronomers

  4. Measurement Modular Classification Modular Preprocessing Modular File Management System CCD Raw Data Image processing & Spectra extraction ODBC/JDBC Interface QL DBMS Database Management Interface Storage &distribution Software Structure

  5. Production 1. Catalogs 2. Calibrated spectra with analysis results AGN Galaxies Stars QSOs Starburst Supernovae Search Galaxies (z) Normal galaxies Emission Line stars Stars (rv) H II Identification O B Stars QSOs (z) A F G K Stars Stellar-Atmospheric- Parameters Input Catalog M or later Stars Unknown Reflection Nebulae Multi-Wavelength Identification Results: Candidate Catalogue Basic Production Reference classification

  6. Comparison between object type and spectral class in SDSS DR5 -- object type -- spectral class

  7. Classification algorithm • Automated Classification by objective methods (training by templates, predicting by distance or density ), collaborators: IA(CAS), BNU,SDU, etc. • Identified by line measurement

  8. Extracted Spectra Yes Absorption lines of NaI, Mgb and CaII etc Absorption lines at 6563±20A, 4860±20A, 4340±20A ? Emission line at 6563±20A, 4860±20A, 4340±20A ? Absorption band detection Lines detection Late type stars (M type) with bands (TiO etc) No No Continuum fitting Starburst AGN or QSO etc. No Yes No line spectra Yes Low S/N low? Redshift measurement Continuum High or low ? Emission Line Spectra ? Yes No High H II Region No BL LAC or high Z galaxies O_III 5007, H_alpha H_beta NII 6583 measurement No Star forming galaxies Star burst galaxies QSO & Seyfert I He II lines Yes No No Yes Yes Normal galaxies O or early B type star A,F,G, early K star or Reflection Nebular Early type emission line star + CSM Late type emission line star + CSM Seyfert II LINER Identification automatically

  9. STELLAR ANALYSIS PIPELINE A, F,G, K type stellar spectra Continuum Rectification Sub-grid model spectra Teff~100K, logg~0.25dex [Fe/H]~0.25dex Best fit rough spectra Rough model spectra grid Teff~500K, logg~1.0dex, [Fe/H]~1.0 dex Cross-correlation Vrad geo Cross-correlation Vrad geo Correction Best fit spectra Line index definition H_delta, H_zeta, , CaII triplet, H&K, G band ±10-20 km/s Optimization of different methods [Fe/H] [C/Fe] Teff logg Line Index Measure Line index & Color index calibration (ANN, Polynomial) Color index from Input Catalog BAD GOOD Health Check? Absolute Magnitude trash bin Visual Magnitude High Resolution Spectra for example. HERES: 372 stars (VLT/UVES) R=20000 S/N=50 distance

  10. Line Indices • To determine the local continuum level • Width selection

  11. Some lines used in the pipeline • CaII K line (3933A) • Balmer lines • CaII triplet • Mg I b • G band and [C/Fe] • Colors

  12. CaII K ~ [Fe/H] Relationship between [Fe/H] and CaII K in 4500K,5000K,5500K,6000K,6500K,7000K and 7500K respectively (Marcs model synthetic spectra). Lines (left) and 2 order polynomial (right) are used to fit the relationships from low to high temperature. Relationships between [Fe/H] and the strength of CaII K in SDSS/SEGUE (Dr6).

  13. [Fe/H]=-2.0 [Fe/H]=-3.0 [Fe/H]=0 [Fe/H]=-1.0 Balmer lines ~ Teff Three Balmer lines in Kurucz model spectra Hγ (434.0 nm) Hδ (410.2 nm) Hζ (388.9 nm) [Fe/H]=-3.0 [Fe/H]=-2.0 [Fe/H]=-3.0 [Fe/H]=-2.0 [Fe/H]=0 [Fe/H]=0 [Fe/H]=-1.0 [Fe/H]=-1.0 • Hδ and Hζ in CFLIB spectra are obvious correlated with Teff. • Since the resolution of 1 Å FWHM of CFLIB and low S/N in the range around Hζfor half of the CFLIB dataset, Hζ line in 3889 Å is difficult to measure. • Fitting Teff ~ Hδ: • Teff = 4572.813 + 546.716×Hδ − 53.773×Hδ2 • error:100-200K

  14. CaII triplet Fitting of relationship between CaII triplet and Teff, [Fe/H], and logg respectively, CFLIB spectra were used as experimental dataset Relationship between CaII triplet and [Fe/H], EW of all Ca II triplet of SDSS/SEGUE spectra are plotted in left panel, and [Fe/H] varies with CaII triplet when T = 5000K, logg = 2.0 in right panel.

  15. MgI b ~ gravity (left) SDSS data, (right) ELODIE data.

  16. G band ~ [C/Fe] Relationship between G band and [C/Fe] with HES follow up spectra

  17. Color ~ Teff Temperature varies with B-V Color in CFLIB dataset For SDSS, in the range -0.3 < g-r <1.0, the following expression provides the effective temperature with an rms only 2% (100-200K) (Ivezić et al 2006)

  18. Structure of the stellar analysis pipeline Independent compiled module +script Already completed module list: Kurucz model calculation Continuum fitting (whole range) ANN Module Regression module Spectra synthesize Continuum fitting (local range) Interpolation module Cross correlation Line index calculation EW calculation module

  19. Kurucz model calculation • Atlas9 Kurucz/Castelli • LTE • NewODF • Intermod: an interpolation program to quickly generate intermediate models from an initial grid • Synthe • Spectrum Gray Spectra Synthesize

  20. Test with Elodie library

  21. Accuracy of the parameters • Checked with SEGUE dr6 data

  22. Accuracy of parameters with different SNR

  23. Thanks !

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