The Arecibo Legacy Fast ALFA Drift Survey (ALFALFA/VAVA) and E-ALFA Data Processing Overview...

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The Arecibo Legacy Fast ALFAThe Arecibo Legacy Fast ALFADrift Survey (ALFALFA/VAVA)Drift Survey (ALFALFA/VAVA)and E-ALFA Data Processing and E-ALFA Data Processing OverviewOverview

Riccardo GiovanelliRiccardo Giovanelli

GALFA/Aug 2004

E-ALFA Surveys (as of May 2004):

• AGES2 (P.I. Jon Davies, U. of Cardiff, G.B.)• DRIFT1 (P.I. R. Giovanelli, Cornell U., Ithaca)• AULDS2 (P.I. Wolfram Freudling, ESO, Munich)• NGC 29032 (P.I. Judith Irwin, Queens U., Ontario)• ZOA3 (P.I. Trish Henning, UNM, Albuquerque)

E-ALFA Coordinating Committee:

Jon Davies Wolfram Freudling Riccardo Giovanelli Trish Henning Judith Irwin

Two components of the “Drift group”:- ALFALFA - VAVA

1 Precursor proposal submitted Feb04; currently on ‘scope2 Precursor proposal submitted Jun04; awaiting review3 To run piggy-back on G-ALFA/P-ALFA surveys

Science to be addressed byALFALFA/VAVA Drift:

1 The investigation of the HI Mass Function

2 High Mass HI sources

3 Environmental variations of the HI properties of galaxies

4 HI Diameter Function

5 The low HI Column density environment of galaxies

6 Environmental differences in the HI Mass function

7 HI absorbers and the link to Lyman absorbers

8 OH Megamasers at intermediate redshift

Group website: http://www.astro.cornell.edu/~haynes/pre204/drift.htm

Credit: Virgo collaboration (MPIfAp)

HI Mass FunctionHI Mass Functionin the local Universein the local Universe

Parkes HIPASS survey: Zwaan et al. 2003

Survey Beam Area rms min MHI Ndet ts Nlos arcmin sq. deg. (mJy @ 13 km/s) @ 1 Mpc sec

AHISS 3.3 13 0.8 1.0x105 66 var 17,000ADBS 3.3 430 3.5 4.2x105 265 12 500,000HIPASS 15. 30,000 14 1.9x106 ~5000 460 1.9x106

HIJASS 12. (13,000) 14 1.9x106 (?) 3500 (1.2x106)J-Virgo 12 32 14 1.9x106 31 3500 3200HIDEEP 15 32 3.2 4.4x105 173 9000 2000

ALFALFA 3.5 6,000 2.2 2.8x105 10,000? 2x12 7x106

VAVA 3.5 900 1.3 1.3x105 3,000? 12x5 1,000,000

E-ALFA Data Processing Planned Environments

- AULDS and AGES : adapt HIPASS software

- NGC2903 : IDL?

- ALFALFA/VAVA : IDL

- ZOA : see T. Henning’s talk

ALFALFA/VAVA Data Taking Mode (minimal intrusion):ALFALFA/VAVA Data Taking Mode (minimal intrusion):

• For Dec<16 and Dec>20: park telescope at meridian; rotate array to 19deg (equal Dec spacing of beams); sky drifts, sampled one record per sec at 100 MHz BW.

• For 16<Dec<20: park telescope at AZ near EW, rotate array for equal Dec spacing of beams (note: Dec spacing smaller than at meridian!); sky drifts.

• Data collected in scans of 900 1-sec records. Minimize overhead between scans. Each scan ~250 Mb.

- Sky is subdivided into “tilestiles” of [RA,Dec]=[20min, 4deg]- Each tile is sampled every 1’ in Dec, 1 sec in RA (double pass strategy: ALFALFA) or every 30” in Dec (quadruple pass strategy: VAVA – selected regions: Virgo, Leo)

-“Processing Unit” is scan of

2 pol x 900 sec x 7 beams x 4096 ch

scan is converted from FITS to IDL during observing session, into “d” structure (identical in format to “m” structure in AO/PP software package)

-Within days, d-structure is noise-calibrated, bandpass-calibrated and baselined stored as “d_red” structure, with identical format to “d”. Ancillary continuum, calibration and mask structures are also saved. These are “level I data product”

DRIFT DATA PROCESSINGDRIFT DATA PROCESSING

-When all data for a tile have been collected, various dred structures contributing to it are assembled into a tile structure (same format again). Continuum source calibration and regridding are done and “level II data products” are placed in the public domain

-Automatic signal extraction algorithms are applied to the the tile structure, candidate source catalogs, observing lists for confirmation runs continuum source/variability lists cross-references with optical/other catalogs produced “ level III data products “

- Survey products placed in NVO domain, HI node (3 of our students are attending NVO School in Boulder, Sep04)

Our group has been on the telescope for the last 10 days(A1946), testing ALFA performance, pointing, rotation,Tsys, beam orientation, data taking software, calibrationoptions, changing data processing pipeline on the fly.

- Level I product software is fully operational

- Level II product software will be tested upon completion of precursor run, in late September

- Level III product software under development. Incorporation to NVO HI node planned out.

Calibration:Calibration: 1)1)Noise Diode:Noise Diode:

cal cal cal cal

A: Fire Cal between scans

B: Fire Cal during scans

Note: CIMA cal is “asynchronous”, i.e. not synchronized with record tick

Issues: - In mode A, a 1 sec cal scan take 4.5 sec sky loss - In mode , duration of 1 sec cal pulse not equal to 1 sec, thus, must fire cal 2-3 sec to assure that 1 record is fully “cal-ed” 4-5 cal-corrupted records per cal event

2) Continuum Sources2) Continuum Sources

System Temperature Summary(on cold, high latitude sky, @ 1400 MHz)

BeamBeam TTsyssys[K], [K], AA

TTsyssys[K], [K], BB

Cal, ACal, A Cal, BCal, B

00 n.a.n.a. 29.929.9 11.311.3 10.710.7

11 29.329.3 28.128.1 10.610.6 10.210.2

22 29.829.8 28.928.9 11.811.8 11.211.2

33 28.928.9 29.429.4 11.311.3 10.910.9

44 30.930.9 29.529.5 11.311.3 10.910.9

55 29.729.7 32.632.6 11.211.2 10.810.8

66 31.631.6 30.630.6 12.012.0 11.611.6

A1946 team, 28Aug04

Raw DataRaw Data

ChannelTime

Temp

Channel

Time

After the bandpass correction…After the bandpass correction…

ChannelTime

Temp

Channel

Time

Signal Extractor -- Introduction

● The signals are extracted by cross-correlations of a template with the spectra.

– More sensitive than peak-finding algorithms.

● sensitive to total flux, not only peak flux

● especially important for low mass systems

– Using FFT's, cross-correlations are fast

– It’s a matched-filter algorithm

Slide: Amelie Saintonge

Signal Extractor -- Application(2)

● The process is :

– Repeat for a range of widths of the template● e.g. 10 km/s – 600km/s

– Choose the width for which the convolution is maximised --> position of the signal

– Calculate the amplitude of the signal from the width

Slide: Amelie Saintonge

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