The LAMOST 1d Spectroscopic Pipeline

A-Li LUO

LAMOST team, NAOC

2008/12/3

The KIAA-Cambridge Joint Workshop on Near-Field Cosmology and Galactic Archeology

Lessons from SDSS

• Three 1d pipelines of SDSS (template based )

Princeton 1d; Fermi 1d; SEGUE: SSPP

• Have been improving from DR1->DR7

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

Software Structure

Measurement

Modular

Classification

Modular

Preprocessing

Modular

File Management

System

ODBC/JDBC

Interface

DBMS CCD Raw Data

Database Management Interface

QL

Storage &distribution

Image processing &

Spectra extraction

Production

Galaxies

Stars

QSOsInput Catalog

Galaxies (z)

Stars (rv)

QSOs (z)

Unknown

Basic Production

AGN

Starburst

Supernovae

SearchEmission Line stars

H II Identificat

ion O B Stars

M or later Stars

A F G K Stars

Reflection Nebulae

Reference classification

Stellar-Atmospheric- Parameters

Normal galaxies

Multi-Wavelength IdentificationCandidat

e Catalogue

1. Catalogs

2. Calibrated spectra with analysis results

Results:

Comparison between object type and spectral class in SDSS DR5

Object type

Totalnumber

Correct(after spectralIdentify)

False(after spectralIdentify)

UNKNOWN STAR GALALY QSO HIZ_QSO STAR-LATE

QSO 112147 5856252.219%

5358547.781%

30772.744%

2297520.487%

1671617.905%

5385548.022%

47074.197%

108179.645%

GALAXY 565267 54878997.085%

164782.915%

34030.602%

73331.297%

54878997.085%

11790.209%

30.00053%

45600.807%

STAR 29595 2899197.959%

6042.04%

1750.591%

1342645.366%

520.176%

2170.733%

1600.54%

1556552.593%

-- object type

-- spectral class

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

Identification automaticallyExtracted Spectra

Late type stars (M type) with bands (TiO etc)

Normal galaxies

Absorptionband detection

Linesdetection

Emission LineSpectra ?

Absorption lines at

6563±20A, 4860±20A, 4340±20A ?

He II lines

Continuum fitting

Emission line at 6563±20A, 4860±20A,

4340±20A ?

ContinuumHigh or low ?

Absorption lines of

NaI, Mgb and CaII etc

O_III 5007, H_alpha H_beta

NII 6583 measurement

Star forming galaxies

Star burst

galaxies

QSO & Seyfert I

Seyfert II LINEREarly type emission line star + CSM

O or early B type star

A,F,G, early K star or Reflection Nebular

Late type emission line star + CSM

Redshift measurement

Starburst AGN or QSO etc.

NoYes

H II Region

No

Low

High

Yes

Yes

No

No Yes Yes

No line spectraNo

Yes

S/N low?

No

BL LAC or high Z galaxies

No

No

Yes

STELLAR ANALYSIS PIPELINE

GOODBAD

A, F,G, K typestellar spectra

Continuum Rectification

Cross-correlation

Vrad geo Correction

Vrad geo

Line Index Measure

Line index definitionH_delta, H_zeta, ,

CaII triplet, H&K, G band

trash bin

Health Check?

Line index & Color index calibration

(ANN, Polynomial)

High Resolution Spectra for example.HERES: 372 stars (VLT/UVES) R=20000 S/N=50

±10-20 km/s

Color index from Input Catalog

Rough model spectra gridTeff~500K, logg~1.0dex,

[Fe/H]~1.0 dex

Best fit rough spectra

[Fe/H][C/Fe]Teff logg

distance

Optimization of different

methods

Cross-correlation

Best fit spectra

Visual Magnitude

Absolute Magnitude

Sub-grid model spectra Teff~100K, logg~0.25dex

[Fe/H]~0.25dex

Line Indices

• To determine the local continuum level

• Width selection

Some lines used in the pipeline

• CaII K line (3933A)

• Balmer lines

• CaII triplet

• Mg I b

• G band and [C/Fe]

• Colors

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).

Balmer lines ~ Teff

[Fe/H]=-3.0

[Fe/H]=-2.0

[Fe/H]=-1.0

[Fe/H]=0

[Fe/H]=-2.0[Fe/H]=-3.0

[Fe/H]=-1.0[Fe/H]=0

Hγ (434.0 nm) Hδ (410.2 nm) Hζ (388.9 nm)[Fe/H]=-3.0

[Fe/H]=-2.0

[Fe/H]=0[Fe/H]=-1.0

Three Balmer lines in Kurucz model spectra

• 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 Hζ for 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

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.

MgI b ~ gravity

(left) SDSS data, (right) ELODIE data.

G band ~ [C/Fe]

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

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)

Structure of the stellar analysis pipeline

Independent compiled module +script

Already completed module list:

Kurucz model calculation

Continuum fitting(whole range)

ANN Module

Regressionmodule

Spectra synthesize

Continuum fitting(local range)

Interpolationmodule

Cross correlation

Line indexcalculation

EW calculationmodule

Kurucz model calculation•Atlas9 Kurucz/Castelli •LTE •NewODF•Intermod: an interpolation program to quickly generate intermediate models from an initial grid

Spectra Synthesize

• Synthe

• Spectrum Gray

Test with Elodie library

Accuracy of the parameters

• Checked with SEGUE dr6 data

Accuracy of parameters with different SNR

Thanks !