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

1. The Arecibo Legacy Fast ALFA Drift Survey (ALFALFA/VAVA) and E-ALFA Data Processing Overview Riccardo Giovanelli GALFA/Aug 2004

2. 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 1Precursor proposal submitted Feb04; currently on ‘scope 2 Precursor proposal submitted Jun04; awaiting review 3To run piggy-back on G-ALFA/P-ALFA surveys

3. 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 a absorbers 8 OH Megamasers at intermediate redshift Group website: http://www.astro.cornell.edu/~haynes/pre204/drift.htm

4. Credit: Virgo collaboration (MPIfAp)

5. HI Mass Function in the local Universe Parkes HIPASS survey: Zwaan et al. 2003

6. 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 17,000 ADBS 3.3 430 3.5 4.2x105 265 12500,000 HIPASS 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 3200 HIDEEP 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

7. E-ALFA Data Processing Planned Environments • AULDS and AGES : adapt HIPASS software • NGC2903 : IDL? • ALFALFA/VAVA : IDL • ZOA : see T. Henning’s talk

8. 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.

9. DRIFT DATA PROCESSING • Sky is subdivided into “tiles” 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”

10. 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)

11. Our group has been on the telescope for the last 10 days • (A1946), testing ALFA performance, pointing, rotation, • Tsys, beam orientation, data taking software, calibration • options, 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.

12. Calibration: • Noise Diode: A: Fire Cal between scans cal cal cal cal 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 Sources

13. System Temperature Summary (on cold, high latitude sky, @ 1400 MHz) A1946 team, 28Aug04

14. Raw Data Temp Time Channel Time Channel

15. After the bandpass correction… Temp Time Channel Time Channel

16. 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

17. 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