Mon. Not. R. Astron. Soc. 000, 1–?? (1994) Printed 2 February 2008 (MN LATEX style file v1.4) arXiv:astro-ph/0302317v1 17 Feb 2003 First Results from the HI Jodrell All Sky Survey: Inclination-Dependent Selection Effects in a 21-cm Blind Survey Robert H. Lang1, Peter J. Boyce,2, Virginia A. Kilborn3, Robert F. Minchin1, Michael J. Disney1 , Christine A. Jordan3, Marco Grossi1, Diego A. Garcia1, Ken C. Freeman4, Steven Phillipps2 and Alan E. Wright5 1 Department of Physics and Astronomy, Cardiff University, P.O. Box 913, Cardiff, CF24 3YB Group, Department of Physics, University of Bristol, Tyndall Avenue, Bristol, BS8 1TL 3 Jodrell Bank Observatory, University of Manchester, Macclesfield, Cheshire, SK11 9DL 4 Research School of Astronomy and Astrophysics, Mount Stromlo Observatory, Cotter Road, Weston, ACT 1611, Australia 5 Australia Telescope National Facility, CSIRO, P.O. Box 76, Epping, NSW 1710, Australia 2 Astrophysics Accepted ???. Received ???? ; ABSTRACT Details are presented of the HI Jodrell All Sky Survey (HIJASS). HIJASS is a blind neutral hydrogen (HI) survey of the northern sky (δ>22◦ ), being conducted using the multibeam receiver on the Lovell Telescope (FWHM beamwidth 12 arcmin) at Jodrell Bank. HIJASS covers the velocity range –3500 km s−1 to 10000 km s−1 , with a velocity resolution of 18.1 km s−1 and spatial positional accuracy of ∼2.5 arcmin. Thus far about 1115 deg2 of sky have been surveyed. The average rms noise during the early part of the survey was around 16 mJy beam−1 . Following the first phase of the Lovell telescope upgrade (in 2001), the rms noise is now around 13 mJy beam−1 . We describe the methods of detecting galaxies within the HIJASS data and of measuring their HI parameters. The properties of the resulting HI-selected sample of galaxies are described. Of the 222 sources so far confirmed, 170 (77 per cent) are clearly associated with a previously catalogued galaxy. A further 23 sources (10 per cent) lie close (within 6 arcmin) to a previously catalogued galaxy for which no previous redshift exists. A further 29 sources (13 per cent) do not appear to be associated with any previously catalogued galaxy. The distributions of peak flux, integrated flux, HI mass and cz are discussed. We show, using the HIJASS data, that HI self-absorption is a significant, but often overlooked, effect in galaxies with large inclination angles to the line of sight. Properly accounting for it could increase the derived HI mass density of the local Universe by at least 25 per cent. The effect this will have on the shape of the HI Mass Function (HIMF) will depend on how self-absorption affects galaxies of different morphological types and HI masses. We also show that galaxies with small inclinations to the line of sight may also be excluded from HI-selected samples, since many such galaxies will have observed velocity-widths which are too narrow for them to be distinguished from narrow-band radio frequency interference. This effect will become progressively more serious for galaxies with smaller intrinsic velocity-widths. If, as we might expect, galaxies with smaller intrinsic velocity-widths have smaller HI masses, then compensating for this effect could significantly steepen the faint-end slope of the derived HIMF. Key words: surveys – galaxies: evolution – galaxies: luminosity function, mass function – galaxies: distances and redshifts – large-scale structure of Universe. 1 INTRODUCTION A complete and bias-free census of the population of extragalactic objects is essential to any study of the formac 1994 RAS tion and evolution of galaxies or the large-scale structure of the universe. However, our current understanding of galaxy populations has been primarily derived from optical and IR 2 R.H. Lang et al. surveys. There is an inevitable bias in such surveys against low luminosity objects (dwarfs), but also against low surface brightness (LSB) objects (see, e.g. Disney 1976; Disney & Phillipps 1987; Impey & Bothun 1997; Disney 1999). However, it has become clear that low luminosity and low surface brightness galaxies play a key role in many cosmological and cosmographical problems. For example, dwarf/LSB galaxies can clearly play a major role in helping us to understand large-scale structure and its influence on galaxy formation and evolution. Their numbers and distribution place constraints on the increasingly sophisticated numerical and semi-analytic models of galaxy formation (e.g., Baugh, Cole & Frenk 1996; Kauffmann et al. 1997), while their morphologies and stellar contents may reflect the local physics which define the star formation process in galaxies (e.g., Bell & Bower 2000; Bell & de Jong 2000). Recent observational studies have fully supported the view (expounded by, e.g., Phillipps et al. 1987 and Impey, Bothun & Malin 1988) that low luminosity and low surface brightness galaxies numerically dominate the galaxy population in the local Universe (see e.g. McGaugh 1996; Cross et al. 2001). However, optical surveys of the local Universe for faint/LSB objects are problematic due to the very long exposure times required, the large areas which need to be surveyed and the need to measure a redshift for each faint/LSB object found. Consequently, our knowledge of the local population of galaxies at low luminosity and low surface brightness is still relatively limited. This inhibits our knowledge of many broader cosmological/cosmographical issues. Given the limitations of optical surveys for detecting low luminosity / LSB objects, an alternative method to sample the extragalactic population is to use the 21-cm neutral hydrogen (HI) line. This provides a way of potentially circumventing optical selection effects operating against low luminosity and/or LSB objects, since a galaxy’s HI content may be relatively uncorrelated with its optical emission. For example, it is well known that elliptical galaxies contain little HI whereas we might expect to find large amounts of HI in galaxies where star formation has been inefficient, e.g. in low luminosity and LSB galaxies. However, until comparatively recently, most HI surveys were limited to HI measurements of galaxies previously detected in optical or IR surveys. The advent of the 21-cm multibeam receiving systems at Parkes and Jodrell Bank has made possible, for the first time, blind HI surveys of large areas of sky to reasonable sensitivity over comparatively large volumes. The HI Parkes All Sky Survey (HIPASS, StaveleySmith et al. 1996) was commenced in 1997 and concluded in 2002. HIPASS has surveyed the southern hemisphere (up to δ=+25◦ ) to cz=12700 km s−1 and an HI mass limit around 106 d2Mpc M⊙ . Results from HIPASS have indeed added significantly to the census of the local extragalactic population. Recent scientific highlights include the discovery of 10 new members to the Cen A group (Banks et al. 1999), the detection of an apparently extragalactic HI cloud with no optical counterpart to faint limits (Kilborn et al. 2000) and the discovery of a massive HI cloud associated with NGC 2442 (Ryder et al. 2001). Kilborn et al. (2002) have recently published a catalogue of 536 galaxies from a 2400 sq deg region of HIPASS covering the South Celestial Cap. Koribalski et al. (in preparation) will present the HIPASS Brightest Galaxies Catalogue (BGC), a catalogue of the brightest 1000 galaxies (in terms of HI peak flux) from the whole of HIPASS. Meanwhile, Ryan-Weber et al. (2002) have discussed the properties of those previously uncatalogued galaxies found in the BGC. The HI Jodrell All Sky Survey (HIJASS) is the northern counterpart to HIPASS. HIJASS will survey the northern sky above δ=22◦ to similar sensitivity to HIPASS, using the Multibeam 4-beam cryogenic receiver mounted on the 76-m Lovell Telescope. HIJASS was begun in 2000. So far ≃1115 deg2 have been surveyed. We recently presented results from the HIJASS data covering the M81 group (Boyce et al. 2001). The survey reveals several new aspects to the complex morphology of the HI distribution in the group and illustrates that a blind HI survey of even such a nearby, well studied group of galaxies can add much new information. This paper presents a detailed description of the HI Jodrell All Sky Survey and of the properties of the HI-selected sample of galaxies which has been compiled so far from the HIJASS data. We use the sample of confirmed HIJASS sources to study the effect that a galaxy’s inclination to the line of sight has on its inclusion within an HI-selected sample. We show that both highly inclined galaxies and galaxies close to face-on are subject to selection effects which could have led to their being under-represented in previous determinations of the HI Mass Function (HIMF) and HI mass density, ΩHI , from HI-selected samples of galaxies. Section 2 describes the hardware, the observing strategy and survey parameters and also describes the data reduction methods. Section 3 describes the methods by which galaxies have been detected within HIJASS data and their parameters measured. Section 4 is a discussion of the properties of the sample of galaxies found in HIJASS data thus far. In Section 5 we use the sample of confirmed HIJASS sources to study the inclination-dependent selection effects on the inclusion of a galaxy in an HI-selected sample and discuss the implications of this. Section 6 presents some concluding remarks. 2 2.1 THE SURVEY Hardware HIJASS uses a cryogenic Multibeam receiver (Bird 1997) of similar design to the Multibeam receiver used at Parkes for HIPASS (Staveley-Smith et al. 1996). The Multibeam system installed at Jodrell Bank has four dual linearly polarised receivers covering a frequency range of 1200 MHz to 1550 MHz. The feed horn array consists of 4 stepped circular horns (which were designed at the CSIRO) arranged in a rhombic pattern, the apertures of which are located at the telescope prime focus. Stepped circular horns were chosen because of their good pattern symmetry, low spillover and good cross polarization properties (Bird 1994). The horns couple directly into a low temperature, high vacuum, cryogenic dewar. The output from the feed horn arrays are then fed to a set of 3-stage high electron mobility transistor (HEMT) pre-amplifiers which are cooled to a temperature of around ∼25 K. Following amplification, each receiver RF band is then down converted to an IF bandpass which can be set anywhere between 30 MHz and 245 MHz. Each of the 8 resultant IF bands are then passed from c 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey 3 Figure 1. A section of a HIJASS cube at roughly constant R.A.. Visible are the residue of Galactic HI at 0 kmṡ−1 , the galaxy UGC06534 at V⊙ ≃1300 km s−1 ; and the radio frequency interference between 4500→7500 km s−1 . the focus cabin to the observing room via about 300 m of low loss coaxial cable which is terminated into N-socket connections in the Lovell Observing Room. These outputs are next patched into a set of digitally programmable attenuators and are then fed into a set of equaliser and splitter units. Each IF is equalised for frequency dependent cable losses and then split into two outputs. The first output connects to a filter bank which sets the bandpass which is presented to the correlator. A second set of outputs are used for pulsar survey measurements. The correlator was constructed at the Australia Telescope National Facility (ATNF). It is built around special purpose VLSI chips developed by the NASA Space Engineering Research Centre for VLSI System Design (Canaris 1993). These chips accept 2-bit sampled data streams at rates of up to 140 Msamples/sec and form either the cross correlation function of the two streams or the autocorrelation function of one stream at 1025 contiguous sample delays. The chip has 1024 32-bit accumulators and a 32-bit output bus and can integrate for up to 16 seconds. In the c 1994 RAS, MNRAS 000, 1–?? multibeam correlator, one of these chips, operating in autocorrelation mode, is used on each of the 8 sampled data streams, thereby providing, after Fourier transformation, a measurement of the input spectrum at 1024 contiguous frequencies spaced at 62.5 kHz (equivalent to 13.2 km s−1 at the rest frequency of HI). 2.2 Observing strategy and data reduction The survey is conducted by actively scanning the sky in 8◦ strips in Declination, at a rate of 1◦ per minute. Each declination scan is separated by 10 arcmin but each area of sky is scanned 8 times, resulting in a final scan separation of 1.25 arcmin. The data from the 8 correlators are stored every 5 s. A 64 MHz bandpass with 1024 channels is used, although local interference at the band edges restricts the useful velocity range to about –1000 km s−1 to +10000 km s−1 (note, however, that a broad band of radio frequency interference also affects all velocities between 4500 km s−1 and 7500 km s−1 - see Section 2.3). The sys- 4 R.H. Lang et al. Table 1. Areas surveyed by HIJASS Decl. Range 70◦ –78◦ 62◦ –70◦ 54◦ –62◦ 30◦ –38◦ 22◦ –30◦ R.A. Range Area (deg2 ) Run complete 09h 02m –11h 55m 02h 30m –04h 02m 03h 26m –04h 08m 01h 13m –01h 59m 12h 08m –12h 34m 795 128 64 32 64 32 2000,2001 2001,2002 2002 2001 2002 2002 tem temperature is ∼30 K. Bandpass correction and calibration are applied using the software package LIVEDATA (see Barnes et al. 2001). The spectra are gridded into threedimensional 8◦ ×8◦ datacubes (α,δ,V⊙ ) using the software package GRIDZILLA (Barnes et al. 2001). The observed spectra are smoothed online by applying a 25 per cent Tukey filter to reduce ‘ringing’ caused by strong Galactic signals entering through the side-lobes. This reduces the actual velocity resolution in the gridded datacubes to 18.1 km s−1 . The spatial pixel size of the datacubes is 4 arcmin×4 arcmin. The effects of continuum emission on the baselines of the spectra in each cube are then removed by the program POLYCON written by Daniel Zambonini and Robert Minchin. This program fits and then subtracts a 5th order polynomial baseline to each individual spectrum in a datacube: fitting is only performed on parts of the spectrum free of interference or line emission. 2.3 Areas Surveyed and Data Quality HIJASS has been conducted during three observing runs: in April-June 2000; in Jan-Feb 2001; and in Jan 2002. Table 1 notes those areas of the northern sky so far surveyed by HIJASS and during which run the data were taken. The whole of a strip in R.A. between Decl.=70◦ →78◦ has been surveyed (795 deg2 ). Two areas of the R.A. strip between Decl.=62◦ →70◦ have also been surveyed (192 deg2 ), along with smaller areas at Decls.=58◦ , 34◦ , and 26◦ . In total 1115 deg2 has been surveyed thus far. Fig. 1 shows an example of the data. This is a plot of Decl. against Velocity at roughly constant R.A.. The HIJASS source HIJASS J1133+63 can be seen at Decl.≃63◦ , V⊙ =1300 km s−1 . This has been identified as UGC 06534. Prominent in the data is a broad band of radio frequency interference (RFI) which affects all velocities from ≃4500 km s−1 to 7500 km s−1 . This is mainly due to off-site radio and data communication emissions generated in the locality. Between the observing runs in 2001 and 2002, the Lovell dish underwent the first stage of a major upgrade. A new telescope drive system was installed and around half of the dish surface was replaced. Prior to this upgrade, the rms noise in the datacubes (away from the broad-band RFI) was typically 1618 mJy beam−1 . However, those cubes made from data taken following the first stage of the refurbishment (i.e. in 2002), show an improvement in sensitivity by around 25 per cent, the rms noise in these cubes being about 1214 mJy beam−1 . The improvement is believed to be due to a combination of several factors: the improved sensitivity of the partially resurfaced dish, an improvement in the telescope pointing model, an improvement in the smoothness of the scanning and a concerted effort to reduce local (Jodrell-based) interference during the observing run. 3 3.1 DETECTING AND PARAMETRIZING GALAXIES IN HIJASS DATA Galaxy detection techniques The general method of detecting galaxies in the HIJASS data is as follows. An initial candidate galaxy list is formed by visually searching the datacubes. The visual display program KVIEW (Gooch 1995) is used to search through the data in three dimensions by displaying 2 axes and stepping through the third. Narrow velocity-width, bright galaxies are most easily seen when the data are displayed in R.A. versus Decl. and stepped through Velocity. Broad velocity-width, faint galaxies are more easily discovered when the datacube is displayed R.A. or Decl. versus Velocity. The selection criteria for this visual sample is that a detection must : (1) be easily visible above the noise (∼3σ in peak flux), (2) should have a spatial extent of greater than 1 pixel, and (3) be visible over two or more velocity planes. Two lists are compiled using these criteria: one of ‘definite’ detections and one of ‘possible’ detections. The list of possible detections includes sources close to the selection limit or just below it but still considered possible sources. A second candidate galaxy list is formed by running the automated finding algorithm POLYFIND, written by Robert Minchin and Jonathon Davies. POLYFIND determines the noise in non-masked regions of a hanning smoothed datacube and then looks for peaks at some userdefined level above the noise (typically set at 3σ). It then runs a series of matched filters over these identified peaks and a peak is noted as a potential source if a sufficiently good fit is obtained. The results from POLYFIND are then re-checked by eye using the same criteria as used for the eyeball method and lists of definite and possible detections made. The two lists of definite detections are then amalgamated and these objects included in our final sample of confirmed HIJASS galaxies. The two lists of possible detections are also amalgamated. These objects are then re-observed with the Lovell telescope in single-beam mode using a bandwidth of 16 MHz. Those possible sources confirmed by this narrow-band follow-up are then added to the sample of confirmed HIJASS sources. The possible sources found during the 2002 run have not yet been subjected to narrow-band follow-up. Hence, for the 2002 data, only the definite detections found by the above selection methods have presently been included in the sample (69 sources). 3.2 Parametrization of the galaxies The parameters of those galaxies included in the sample of confirmed HIJASS sources are determined from the data using tasks from the MIRIAD software package (Sault et al. 1995). Firstly, a two-dimensional Gaussian fit (IMFIT) is made to a zeroth order (intensity) moment-map of each detection to determine the central position of the galaxy as well as the spatial extent of the HI. The central position c 1994 RAS, MNRAS 000, 1–?? c 1994 RAS, MNRAS 000, 1–?? Table 2. The sample of on rmed HIJASS sour es. Sour e Name rms Vo
V20
V50 Class Opti al Counterpart Position Velo ity mJy kms 1 kms 1 kms 1 O set (0 ) O set (kms 1 ) 11.8 2419 502 479 ID UGC 12921 2.4 +30 12.7 4040 363 332 ID UGC 01033 1.2 -3 18.1 {175 146 103 ID M33 6.8 -4 14.8 150 153 121 ID UGC 01281 0.4 +3 15.6 3740 158 119 ASS ZOAG G135.80+04.32 1.0 11.6 3456 390 374 ID* MCG+11-04-003 2.1 -12 13.5 2533 320 301 ID UGC 02411 0.8 +14 12.2 3532 217 192 ID IRAS 03028+6516 2.1 +67 12.6 3213 197 150 ID [H92℄ 09 3.4 +7 10.2 1462 90 76 PUG 18.4 529 105 70 PUG 14.5 2462 260 213 ID* IRAS 03044+6528 1.8 -2 11.5 2009 199 47 ID kkh 019 3.7 +28 11.0 3163 273 237 ID* IRAS 03076+6712 2.6 -76 15.7 2389 172 85 ID* IRAS 03108+6441 0.7 -31 12.0 2493 166 142 ASS ZOAG G136.34+08.19 0.5 13.8 3167 378 322 ID* IRAS 03123+6450 1.6 -22 11.3 3005 200 185 ASS* 13.1 3267 157 148 ASS ZOAG G138.56+05.39 0.9 30.5 1555 73 65 PUG 12.6 2591 241 218 ASS 2MASXi J0322123+723607 1.9 18.1 2314 370 297 ID* IRAS 03189+5828 2.9 +6 13.4 2171 119 72 PUG 9.3 1391 136 125 ASS ZOAG G136.67+09.22 2.1 11.0 2008 180 158 ASS ZOAG G138.98+05.94 1.8 11.5 1934 256 233 ID UGC 02729 0.2 +6 11.5 2125 84 58 ID HFLLZOA G131.80+16.14 3.2 +6 12.1 2080 247 234 ID UGCA 069 2.3 -7 13.4 1958 134 114 PUG 22.8 1427 192 177 PUG 10.0 2456 453 411 ASS* 17.5 1340 138 120 PUG 10.8 1603 262 241 ID* IRAS 03266+6619 0.5 -23 13.6 1730 327 105 ID UGC 02765 4.4 -51 10.5 1639 96 74 PUG 10.9 1347 175 109 ID IRAS 03277+6755 1.3 -14 12.9 2558 114 78 PUG 11.8 2501 113 99 ASS HFLLZOA G133.03+15.74 2.4 13.0 2214 146 128 ID NGC 1343 0.3 +1 13.3 1439 122 92 ID IRAS 03337+6725 0.3 -5 13.0 1181 223 201 ID UGC 02800 1.6 -5 11.7 1502 273 256 ID UGCA 081 0.4 -6 15.0 1293 136 125 PUG 18.2 2547 147 135 PUG 17.7 97 51 32 PUG 5 De l. SInt SPk (J2000) Jy kms 1 mJy 77:17:43 9.530.99 61 31:33:07 17.250.91 105 30:43:09 780.660.86 7654 32:34:57 32.940.72 281 64:06:01 17.620.77 169 66:22:10 12.310.86 78 75:45:29 27.040.92 143 65:29:20 9.300.69 75 62:10:16 9.000.68 89 74:57:20 2.640.40 49 65:00:38 6.580.77 109 65:39:12 17.130.89 120 74:13:27 4.170.63 58 67:25:10 10.650.69 67 64:52:44 22.620.80 244 67:12:43 11.500.60 119 65:00:48 15.361.01 72 66:49:26 16.030.62 114 63:39:56 7.610.64 72 54:56:13 8.591.10 152 72:37:56 20.390.74 147 58:36:21 33.241.31 169 66:40:25 6.960.59 102 67:53:43 3.550.43 46 63:53:09 7.090.57 85 68:35:02 24.140.70 178 76:17:35 9.280.44 153 72:49:56 14.610.73 85 67:07:40 41.430.62 518 57:54:58 38.031.22 290 64:58:38 13.170.80 75 55:57:22 30.590.84 326 66:30:09 31.540.67 179 68:17:49 16.630.93 133 66:08:36 7.680.42 114 68:06:37 39.310.56 371 75:09:23 4.210.56 59 75:12:50 12.680.51 151 72:33:57 18.710.62 173 67:35:33 55.400.59 688 71:23:45 22.660.62 169 66:42:24 61.800.74 415 70:10:07 26.150.70 182 71:46:59 2.130.87 43 68:16:20 408.990.57 11129 First Results from the HI Jodrell All Sky Survey HIJASS J0002+77 HIJASS J0127+31 HIJASS J0133+30 HIJASS J0149+32 HIJASS J0253+64 HIJASS J0254+66 HIJASS J0258+75 HIJASS J0307+65 HIJASS J0308+62 HIJASS J0308+74 HIJASS J0308+65 HIJASS J0309+65 HIJASS J0310+74 HIJASS J0312+67 HIJASS J0315+64 HIJASS J0316+67 HIJASS J0316+65 HIJASS J0319+66 HIJASS J0320+63 HIJASS J0321+54 HIJASS J0322+72 HIJASS J0322+58 HIJASS J0323+66 HIJASS J0325+67 HIJASS J0326+63 HIJASS J0326+68 HIJASS J0326+76 HIJASS J0327+72 HIJASS J0327+67 HIJASS J0328+57 HIJASS J0329+64 HIJASS J0330+55 HIJASS J0331+66 HIJASS J0332+68 HIJASS J0332+66 HIJASS J0332+68 HIJASS J0335+75 HIJASS J0337+75 HIJASS J0337+72 HIJASS J0338+67 HIJASS J0339+71 HIJASS J0340+66 HIJASS J0347+70 HIJASS J0348+71 HIJASS J0348+68 R.A. (J2000) 00:02:31.1 01:27:29.7 01:33:23.9 01:49:30.5 02:53:45.3 02:54:57.0 02:58:48.2 03:07:22.9 03:08:00.5 03:08:27.1 03:08:44.3 03:09:01.1 03:10:26.8 03:12:35.0 03:15:16.6 03:16:42.2 03:16:56.4 03:19:59.7 03:20:16.7 03:21:17.7 03:22:06.3 03:22:52.1 03:23:36.1 03:25:49.4 03:26:17.9 03:26:55.0 03:26:49.8 03:27:24.6 03:27:58.2 03:28:31.3 03:29:17.5 03:30:51.0 03:31:07.7 03:32:14.9 03:32:22.9 03:32:43.8 03:35:01.4 03:37:40.8 03:37:51.1 03:38:31.1 03:39:45.3 03:40:04.3 03:47:19.6 03:48:08.1 03:48:22.5 6 Continued. Sour e Name Table 2. De l. SInt SPk rms Vo
V20
V50 Class Opti al Counterpart Position Velo ity (J2000) Jy kms 1 mJy mJy kms 1 kms 1 kms 1 O set (0 ) O set (km s 1 ) 70:07:56 90.781.13 328 14.2 1178 451 371 ID UGC 02855 0.1 +24 70:06:11 51.531.53 198 18.7 1283 482 231 ID* UGC 02866 0.6 -51 65:11:02 8.870.73 94 15.2 1266 148 137 PUG 74:09:33 8.570.60 101 12.9 2555 137 85 ASS* 67:55:28 4.820.48 87 12.2 1279 90 49 PUG 70:16 57 6.060.84 75 17.9 1376 142 99 ASS HFLLZOA G137.35+12.75 1.9 72:48:01 3.860.83 61 17.2 1150 149 85 PUG 66:07:07 7.790.72 72 12.2 3448 240 193 PUG 69:16:41 5.910.59 82 13.2 1302 127 105 ID BK19 0.6 0 67:09:07 332.800.41 4654 21.9 65 156 66 ID UGCA 086 2.3 +1 56:25:30 1.740.73 55 21.1 3564 66 56 PUG 71:41:10 10.520.52 86 20.2 4573 230 199 ID UGC 02916 1.2 -56 71:42:30 17.890.94 169 20.2 4451 220 198 ID CGCG 327-013 0.8 -58 74:11:22 9.280.51 265 16.4 2574 47 31 ASS HFLLZOA G135.05+16.10 4.0 71:31:57 3.930.62 65 13.8 1725 128 113 ID BK21 4.7 +9 69:45:45 101.782.40 360 13.8 886 479 460 ID IC 0356 3.1 +9 70:25:36 8.231.15 78 20.7 736 206 188 ASS* 75:17:31 33.031.05 238 15.3 2475 329 300 ID NGC 1530 1.0 -14 71:42:56 1.890.58 61 16.8 3124 64 29 PUG 75:36:22 16.970.81 102 12.7 2476 281 263 ID NGC 1530A 3.4 0 72:46:53 10.961.61 97 23.2 4798 339 308 ID UGC 03131 3.0 -44 76:24:36 41.040.90 241 15.1 989 242 230 ID UGC 03137 1.2 +3 74:56:55 18.020.77 160 15.8 1639 154 132 ID UGC 03144 2.3 -3 73:21:03 4.600.44 121 13.4 1266 56 39 PUG 76:21:17 15.520.88 88 12.8 2483 332 245 ID UGC 03276 2.7 +20 72:23:49 7.670.51 151 14.3 1106 70 52 ID [HS98℄ OD 3.7 -17 73:42:18 13.320.56 139 12.3 1238 129 109 ID UGC 03317 1.5 +2 73:36:41 4.700.53 68 11.8 1053 127 83 ID* KUG 0539+735 1.1 +46 72:22:07 10.180.45 78 8.2 1080 199 163 ID UGC 03343 0.7 +10 75:18:40 23.700.88 228 18.4 811 146 129 ID UGC 03371 0.7 +5 73:04:46 18.310.56 224 12.8 1095 119 77 ID UGC 03384 4.1 -6 71:23:17 16.020.70 87 11.3 1270 268 231 ID UGC 03403 1.1 -6 71:06:29 8.870.28 56 14.9 3981 325 220 ID UGC 03422 2.2 -60 75:01:14 1.750.42 41 10.9 1324 85 75 ASS 2MASXi J0620153+745817 4.8 69:39:03 6.720.95 120 16.4 1196 290 56 ID UGC 03580 5.5 +5 71:49:40 21.510.83 99 12.2 3144 321 298 ID UGC 03697 0.9 -7 73:29:30 10.470.64 105 12.2 2702 183 122 ID UGC 03730 (Pair) 3.8 +5 75:43:42 9.720.45 138 11.1 1118 96 79 ID UGC 03739 1.5 +2 74:18:45 1.450.53 61 14.3 966 77 44 PUG 77:49:01 7.110.57 67 11.1 2643 172 156 ID UGC 03794 2.1 +13 72:29:29 12.280.88 108 15.3 2620 223 175 ID* UGC 03864 (Group) 2.3 -51 74:25:10 6.610.55 70 9.6 3776 221 119 ID* UGC 03906 (Pair) 2.6 -72 73:41:59 13.520.59 111 11.1 943 188 170 ID UGC 03909 1.5 +2 72:47:54 10.140.58 201 15.3 2476 83 59 ID UGC 03975 0.8 +4 74:19:57 14.560.94 84 14.3 3943 298 180 ID UGC 04028 2.8 +9 R.H. Lang et al. c 1994 RAS, MNRAS 000, 1–?? HIJASS J0348+70 HIJASS J0350+70 HIJASS J0352+65 HIJASS J0352+74 HIJASS J0355+67 HIJASS J0355+70 HIJASS J0357+72 HIJASS J0357+66 HIJASS J0358+69 HIJASS J0400+67 HIJASS J0401+56 HIJASS J0402+71 HIJASS J0402+71 HIJASS J0403+74 HIJASS J0404+71 HIJASS J0407+69 HIJASS J0409+70 HIJASS J0423+75 HIJASS J0430+71 HIJASS J0443+75 HIJASS J0445+72 HIJASS J0445+76 HIJASS J0447+74 HIJASS J0509+73 HIJASS J0520+76 HIJASS J0529+72 HIJASS J0533+73 HIJASS J0545+73 HIJASS J0545+72 HIJASS J0556+75 HIJASS J0602+73 HIJASS J0610+71 HIJASS J0615+71 HIJASS J0619+75 HIJASS J0655+69 HIJASS J0711+71 HIJASS J0713+73 HIJASS J0716+75 HIJASS J0721+74 HIJASS J0722+77 HIJASS J0730+72 HIJASS J0736+74 HIJASS J0736+73 HIJASS J0744+72 HIJASS J0750+74 R.A. (J2000) 03:48:23.7 03:50:11.6 03:52:06.5 03:52:54.4 03:55:08.1 03:55:57.8 03:57:37.4 03:57:38.2 03:58:19.7 04:00:13.1 04:01:06.2 04:02:32.0 04:02:57.2 04:03:08.2 04:04:07.4 04:07:36.7 04:09:04.6 04:23:11.7 04:30:17.5 04:43:43.6 04:45:47.3 04:45:58.7 04:47:24.1 05:09:47.1 05:20:31.5 05:29:32.1 05:33:25.9 05:45:19.9 05:45:26.1 05:56:28.7 06:02:25.1 06:10:23.0 06:15:24.5 06:19:15.8 06:55:49.8 07:11:32.4 07:13:28.8 07:16:10.9 07:21:20.9 07:22:12.5 07:30:35.1 07:36:12.5 07:36:39.4 07:44:58.4 07:50:14.4 c 1994 RAS, MNRAS 000, 1–?? Continued. Sour e Name Table 2. SInt Jy kms 1 10.621.11 6.710.59 5.400.19 9.100.56 22.390.57 195.860.60 3.620.54 8.790.82 19.350.86 9.620.77 8.710.85 15.000.43 16.900.75 23.470.82 39.530.81 30.880.83 21.900.66 20.740.71 90.070.68 2.870.39 8.190.59 10.840.88 19.790.53 34.210.61 58.200.69 10.960.91 79.251.05 10.800.46 326.190.99 149.381.78 71.870.81 14.790.85 24.007.20 35.049.51 35.607.12 5.820.76 173.650.72 3.140.66 16.231.00 22.970.95 11.540.79 8.640.41 19.940.92 2.030.58 13.820.77 SPk mJy 119 56 59 123 149 3588 83 135 131 99 280 95 116 128 186 146 172 109 1129 85 91 82 134 1086 439 91 433 229 2816 1116 460 96 600 730 1780 66 3353 74 116 98 74 303 100 53 124 rms Vo
V20
V50 Class Opti al Counterpart Position Velo ity mJy kms 1 kms 1 kms 1 O set (0 ) O set (kms 1 ) 22.7 3470 156 104 ID NGC 2441 1.5 0 10.9 2346 196 156 ASS KUG 0746+747 3.1 10.0 2483 111 81 ID* UGC 04050 0.7 +16 13.1 2294 114 90 ID NGC 2336A 2.1 +2 10.8 1538 187 170 ID UGC 04238 2.0 +6 16.5 156 74 54 ID Holmberg II 2.3 +1 15.9 117 62 42 ID M81DWARFA 1.3 -4 14.7 3532 93 67 ID UGC 04363 2.4 -3 15.9 2169 195 166 ID UGC 04390 3.0 0 14.1 3677 200 100 ID NGC 2550A 4.5 -36 27.7 157 44 30 ID UGC 04483 2.9 +21 12.8 1335 299 263 ID NGC 2591 2.9 -13 13.4 2374 210 157 ID IC 2389 1.3 +7 10.8 2111 402 232 ID NGC 2633 4.1 +49 12.3 1317 302 281 ID NGC 2715 1.3 +22 12.1 1494 324 278 ID* NGC 2748 2.0 -18 12.3 1126 193 161 ID Holmberg III 1.2 +1 10.6 2263 313 296 ID IC 0529 1.5 -1 15.9 1740 114 90 ID NGC 2805 0.4 -10 11.4 660 60 27 ID UGC04945 1.8 -1 13.3 3438 124 107 ID UGC 05042 1.6 -3 15.2 2175 238 144 ID* UGC 05050 3.1 +2 9.3 2286 217 203 ID NGC 2938 1.6 -1 19.5 140 48 30 ID Holmberg I 1.1 +3 13.4 {40 172 100 ID NGC 2976 3.1 +37 15.4 3920 239 176 ID* KUG 0946+674 4.0 -7 15.5 1315 322 302 ID NGC 2985 1.1 +7 13.0 3362 69 37 ID UGC 05277 1.6 +3 17.6 -40 459 388 ID M81 3.6 +6 32.2 184 204 132 ID M82 2.2 +19 14.2 1052 223 208 ID NGC 3027 1.9 +6 13.6 2461 272 189 ID NGC 3061 2.7 -4 32.2 59 75 40 ID* Holmberg IX 3.1 +6 32.2 99 57 48 ASS A0952+69 2.8 17.6 {151 80 50 ID KDG061 5.9 +16 14.7 2109 177 81 ID NGC 3066 1.9 -60 17.9 9 93 35 ID NGC 3077 3.1 +5 17.4 335 84 58 ID UGC 05423 1.6 +15 15.4 3321 293 237 ID UGC 05520 1.0 -6 12.6 2794 403 366 ID NGC 3147 2.5 +26 12.1 2940 296 255 ID NGC 3155 1.4 +4 12.9 43 57 37 PUG 12.8 3098 364 304 ID NGC 3183 0.9 -10 12.3 1671 143 90 PUG 15.1 1013 171 147 ID UGC 05612 1.2 -2 7 De l. (J2000) 72:59:37 74:35:11 72:03:04 78:00:50 76:23:25 70:42:01 71:00:36 74:24:06 73:28:31 73:41:01 69:43:54 77:59:01 73:31:15 74:02:01 78:04:01 76:27:09 74:13:51 73:44:08 64:05:57 75:44:32 66:28:16 76:26:58 76:18:05 71:12:00 67:55:50 67:06:31 72:16:00 65:28:32 69:07:16 69:40:18 72:11:09 75:50:05 69:05:40 69:19:41 68:39:02 72:05:39 68:42:19 70:20:24 65:08:43 73:23:55 74:20:40 68:42:00 74:10:07 77:54:43 70:52:52 First Results from the HI Jodrell All Sky Survey HIJASS J0751+72 HIJASS J0752+74 HIJASS J0752+72 HIJASS J0755+78 HIJASS J0811+76 HIJASS J0818+70 HIJASS J0824+71 HIJASS J0824+74 HIJASS J0827+73 HIJASS J0828+73 HIJASS J0836+69 HIJASS J0837+77 HIJASS J0848+73 HIJASS J0848+74 HIJASS J0908+78 HIJASS J0913+76 HIJASS J0915+74 HIJASS J0918+73 HIJASS J0920+64 HIJASS J0922+75 HIJASS J0928+66 HIJASS J0932+76 HIJASS J0938+76 HIJASS J0940+71 HIJASS J0947+67 HIJASS J0950+67 HIJASS J0950+72 HIJASS J0951+65 HIJASS J0955+69 HIJASS J0955+69 HIJASS J0956+72 HIJASS J0956+75 HIJASS J0957+69 HIJASS J0957+69 HIJASS J0957+68 HIJASS J1002+72 HIJASS J1003+68 HIJASS J1005+70 HIJASS J1015+65 HIJASS J1017+73 HIJASS J1018+74 HIJASS J1021+68 HIJASS J1022+74 HIJASS J1022+77 HIJASS J1023+70 R.A. (J2000) 07:51:46.1 07:52:11.6 07:52:54.5 07:55:34.9 08:11:26.6 08:18:39.7 08:24:01.9 08:24:41.2 08:27:29.4 08:28:07.5 08:36:47.6 08:37:51.4 08:48:07.9 08:48:23.9 09:08:18.9 09:13:18.6 09:15:05.4 09:18:28.1 09:20:23.4 09:22:07.9 09:28:51.9 09:32:00.0 09:38:44.2 09:40:34.3 09:47:46.8 09:50:19.9 09:50:33.1 09:51:52.1 09:55:18.6 09:55:27.2 09:56:01.6 09:56:43.7 09:57:19.0 09:57:22.4 09:57:55.5 10:02:16.6 10:03:49.1 10:05:22.4 10:15:09.3 10:17:28.4 10:18:00.0 10:20:31.0 10:22:01.0 10:22:12.8 10:23:52.4 8 Continued. Sour e Name Table 2. De l. SInt SPk rms Vo
V20
V50 Class Opti al Counterpart Position Velo ity (J2000) Jy kms 1 mJy mJy kms 1 kms 1 kms 1 O set (0 ) O set (kms 1 ) 66:43:37 4.510.55 58 11.0 1130 166 127 ID UGC 05671 5.9 +6 68:26:23 187.070.63 2600 14.0 64 126 104 ID IC 2574 4.7 -7 70:02:49 11.090.45 202 12.6 1917 72 54 ID UGC 05688 1.6 +3 77:51:19 1.960.44 56 12.3 1633 72 30 ID UGC 05701 3.3 -9 65:01:44 35.741.03 198 16.8 1670 256 235 ID NGC 3259 0.8 +16 73:44:08 9.180.98 72 15.2 1140 290 99 ID NGC 3252 2.3 +16 63:13:21 146.190.66 775 10.7 1019 261 238 ID NGC 3359 0.1 -5 72:24:38 9.080.66 94 12.0 2731 201 159 ID NGC 3364 0.9 0 65:31:34 12.740.44 201 11.8 341 83 66 ID UGC 05918 2.4 -1 67:58:50 7.240.48 96 11.5 1111 108 89 ID UGC 05979 0.6 +5 73:41:28 40.620.93 275 14.1 1268 301 281 ID NGC 3403 0.5 -6 65:14:34 2.810.50 54 11.1 1051 128 92 ID UGC 06237 1.1 +17 67:14:55 10.510.52 93 10.5 1316 159 143 ID NGC 3622 0.4 -10 69:37:18 12.300.54 106 10.2 1317 184 145 ID UGC 06378 1.0 -11 64:03:45 10.030.73 89 14.3 1011 172 160 ID UGC 06390 1.0 +4 63:43:12 12.590.58 198 15.5 3729 80 59 ID UGC 06429 0.8 -3 64:05:14 3.510.54 60 13.9 981 89 79 ID UGC 06448 3.4 +6 61:49:36 3.840.47 102 13.5 3273 64 28 ID UGC 06528 4.1 -23 63:17:25 19.360.91 167 16.3 1272 212 135 ID UGC 06534 1.4 +1 71:30:54 9.780.72 62 11.5 2821 273 194 ID* UGC 06552 1.7 -14 77:21:34 5.800.52 53 9.7 1683 195 177 ID NGC 3901 0.9 +3 69:45:55 7.070.58 72 10.8 2709 194 136 ID UGC 06711 2.2 -7 69:22:07 15.000.66 108 11.5 1441 221 199 ID NGC 3879 0.9 -10 69:09:58 7.860.58 63 10.2 1465 214 156 ID UGC 06764 3.7 -4 77:29:25 11.220.60 77 8.7 2023 336 274 ID UGC 07086 2.2 -15 76:48:52 20.910.64 162 10.2 1828 272 242 ID NGC 4127 0.7 -11 29:12:44 21.231.62 130 21.1 3884 419 318 ASS* 25:00:02 10.770.76 94 13.1 2570 227 208 ID UGC 07143 1.7 +3 29:56:49 35.581.40 449 33.2 610 108 88 ID NGC 4136 2.5 -1 76:06:19 9.020.69 121 12.1 1752 219 165 ID* NGC 4159 2.0 -16 24:06:21 13.910.79 81 11.4 2563 333 320 ID NGC 4162 1.4 +6 29:07:34 5.590.44 87 11.0 3998 93 65 ID* NGC 4174 3.2 -18 29:12:00 35.920.70 310 13.4 1113 179 161 ASS* 24:15:03 4.090.37 81 10.3 950 72 61 ID UGC 07236 1.6 -5 75:04:31 5.490.61 62 9.6 2272 280 129 ID UGC 07226 3.3 0 28:33:07 12.670.84 82 11.6 3896 374 337 ID NGC 4185 2.5 +8 30:20:30 4.460.41 67 10.4 3830 91 74 ASS MAP-NGP 0-321-0285578 0.8 28:43:55 11.620.40 192 10.3 1215 89 70 ID UGC 07300 0.2 -5 22:31:42 31.430.68 229 11.6 420 235 214 ID UGC 07321 2.2 -12 70:48:33 8.810.54 126 11.6 2048 143 122 ID NGC 4250 2.0 -19 28:21:29 7.840.61 57 10.1 2527 251 222 ASS* 26:04:04 3.220.36 38 7.9 1019 134 112 ID IC 3215 1.0 0 76:08:14 11.000.72 104 11.7 1581 257 157 ID NGC 4331 2.4 -12 74:59:16 7.380.55 59 10.2 1411 197 178 ID* NGC 4363 3.3 +16 26:43:11 13.060.54 100 10.4 321 180 134 ID IC 3308 0.3 -5 R.H. Lang et al. c 1994 RAS, MNRAS 000, 1–?? HIJASS J1028+66 HIJASS J1029+68 HIJASS J1030+70 HIJASS J1032+77 HIJASS J1032+65 HIJASS J1034+73 HIJASS J1046+63 HIJASS J1048+72 HIJASS J1049+65 HIJASS J1052+67 HIJASS J1053+73 HIJASS J1112+65 HIJASS J1120+67 HIJASS J1121+69 HIJASS J1122+64 HIJASS J1125+63 HIJASS J1126+64 HIJASS J1133+61 HIJASS J1133+63 HIJASS J1134+71 HIJASS J1142+77 HIJASS J1144+69 HIJASS J1146+69 HIJASS J1147+69 HIJASS J1205+77 HIJASS J1208+76 HIJASS J1208+29 HIJASS J1209+25 HIJASS J1209+29 HIJASS J1211+76 HIJASS J1211+24 HIJASS J1212+29 HIJASS J1212+29 HIJASS J1213+24 HIJASS J1213+75 HIJASS J1213+28 HIJASS J1216+30 HIJASS J1216+28 HIJASS J1217+22 HIJASS J1217+70 HIJASS J1219+28 HIJASS J1222+26 HIJASS J1222+76 HIJASS J1224+74 HIJASS J1225+26 R.A. (J2000) 10:28:16.7 10:29:08.5 10:30:06.8 10:32:33.5 10:32:37.1 10:34:01.2 10:46:36.6 10:48:28.8 10:49:13.8 10:52:44.7 10:53:47.9 11:12:13.8 11:20:11.9 11:21:59.9 11:22:32.9 11:25:24.3 11:26:36.6 11:33:18.6 11:33:31.6 11:34:23.3 11:42:52.2 11:44:36.4 11:46:52.1 11:47:38.1 12:05:18.3 12:08:30.9 12:08:37.7 12:09:43.2 12:09:07.5 12:11:19.5 12:11:56.6 12:12:13.7 12:12:21.0 12:13:54.9 12:13:52.2 12:13:21.6 12:16:36.2 12:16:44.1 12:17:24.6 12:17:49.8 12:19:22.6 12:22:12.1 12:22:55.6 12:24:07.9 12:25:18.4 c 1994 RAS, MNRAS 000, 1–?? Continued. Sour e Name Table 2. De l. (J2000) 27:34:01 28:23:41 28:29:58 28:40:16 22:49:06 29:42:02 24:00:37 75:15:31 71:10:37 72:51:52 74:24:54 73:40:47 73:06:52 75:20:13 70:30:46 78:12:45 70:46:01 70:21:03 72:21:55 72:05:53 75:11:51 71:32:11 71:06:18 74:17:26 75:42:45 77:21:44 72:05:45 74:35:59 70:30:04 74:15:59 75:07:32 72:27:43 71:12:11 73:14:55 71:55:16 75:22:10 76:30:57 75:09:56 73:08:25 75:15:12 71:33:05 72:44:02 SInt SPk rms Vo
V20
V50 Class Opti al Counterpart Position Velo ity Jy kms 1 mJy mJy kms 1 kms 1 kms 1 O set (0 ) O set (km s 1 ) 35.690.50 359 10.7 743 138 118 ID NGC 4393 0.3 +12 5.990.60 86 13.3 4510 128 115 ID IC 3309 1.8 +5 6.440.50 124 13.3 481 79 44 ID LEDA 166137 1.3 +5 7.510.78 65 12.9 4458 247 197 ID UGC 07597 0.5 0 29.630.56 249 11.6 642 152 134 ID NGC 4455 0.7 -5 8.160.46 134 12.1 642 84 68 ID UGC 07673 0.6 0 3.600.52 65 15.0 1329 65 24 ASS* 4.380.51 59 10.9 1896 137 72 ID UGC 07872 3.1 -18 15.270.85 88 13.0 1665 299 256 ID NGC 4693 1.0 +5 10.410.86 69 12.7 1628 321 265 ID NGC 4750 1.1 -5 2.610.54 35 10.5 3164 176 166 PUG 6.870.67 51 10.9 1650 260 197 ID UGC 08120 1.5 +15 1.940.49 47 13.0 2837 83 76 PUG 2.020.94 84 29.3 2533 52 44 PUG 9.530.75 72 14.6 3097 176 146 ID NGC 5144 (Pair) 1.7 +38 50.070.84 339 15.0 1354 211 183 ID NGC 6217 1.2 +8 11.800.86 102 16.0 1284 191 169 ID NGC 6236 4.5 -4 30.760.84 257 16.5 1132 171 150 ID NGC 6248 0.5 -3 18.440.91 125 14.4 1192 276 176 ID IC 1251 2.8 -24 3.250.58 51 11.4 1307 168 84 ASS 87GB 171345.8+720715 5.3 7.080.38 149 10.5 1234 71 54 ID UGC 10792 0.8 -1 2.380.37 65 10.2 2495 70 33 PUG 10.550.65 89 11.2 1156 230 195 ID NGC 6395 1.2 +8 5.980.42 63 9.0 1904 214 166 ID UGC 10892 2.5 +23 19.590.55 171 12.1 1318 141 117 ID NGC 6412 0.8 +6 3.740.56 59 10.1 1828 209 154 ID* UGC 10907 2.1 -6 12.150.78 61 11.3 2491 340 305 ID NGC 6434 0.5 -8 27.531.04 154 14.7 1491 353 335 ID NGC 6643 1.9 -7 29.220.75 214 13.2 495 217 190 ID NGC 6689 1.5 +5 2.340.46 54 12.6 2330 74 45 PUG 6.670.21 64 11.2 1844 186 132 PUG 25.920.74 168 11.4 2404 289 254 ID UGC 11818 1.3 -2 10.670.69 94 13.8 2537 160 130 PUG 40.530.80 215 12.9 1485 266 245 ID UGC 11861 4.0 -4 13.870.77 79 12.0 2540 285 269 ID* IRAS 22002+7142 1.5 -42 25.701.00 143 15.4 2461 295 275 ID* IRAS 22282+7506 0.5 -16 10.280.74 99 14.6 2366 167 156 ID UGC 12069 1.0 +1 26.801.08 172 17.7 1549 254 237 ID UGC 12160 1.6 +6 7.820.98 90 17.9 1538 201 115 ID* UGC 12182 1.4 -4 8.660.51 94 10.7 1662 147 130 ASS UGC 12247 1.0 3.660.45 74 12.2 1540 75 39 ID UGC 12261 4.5 +3 25.300.83 200 13.8 2668 246 223 ID UGC 12263 1.5 +8 First Results from the HI Jodrell All Sky Survey HIJASS J1225+27 HIJASS J1225+28 HIJASS J1225+28 HIJASS J1228+28 HIJASS J1228+22 HIJASS J1231+29 HIJASS J1233+24 HIJASS J1242+75 HIJASS J1246+71 HIJASS J1250+72 HIJASS J1255+74 HIJASS J1300+73 HIJASS J1315+73 HIJASS J1321+75 HIJASS J1323+70 HIJASS J1632+78 HIJASS J1643+70 HIJASS J1646+70 HIJASS J1710+72 HIJASS J1711+72 HIJASS J1714+75 HIJASS J1720+71 HIJASS J1726+71 HIJASS J1729+74 HIJASS J1729+75 HIJASS J1729+77 HIJASS J1736+72 HIJASS J1819+74 HIJASS J1834+70 HIJASS J2012+74 HIJASS J2016+75 HIJASS J2147+72 HIJASS J2151+71 HIJASS J2155+73 HIJASS J2201+71 HIJASS J2229+75 HIJASS J2230+76 HIJASS J2241+75 HIJASS J2245+73 HIJASS J2253+75 HIJASS J2256+71 HIJASS J2257+72 R.A. (J2000) 12:25:51.5 12:25:13.0 12:25:32.7 12:28:24.3 12:28:41.1 12:31:59.4 12:33:46.5 12:42:08.8 12:46:56.4 12:50:18.9 12:55:38.2 13:00:14.0 13:15:12.7 13:21:17.8 13:23:14.4 16:32:55.3 16:43:41.2 16:46:18.2 17:10:25.6 17:11:51.8 17:14:12.5 17:20:40.7 17:26:44.5 17:29:26.0 17:29:46.8 17:29:52.2 17:36:45.7 18:19:57.5 18:34:41.8 20:12:06.5 20:16:45.4 21:47:00.0 21:51:08.1 21:55:29.9 22:01:07.5 22:29:22.6 22:30:30.2 22:41:18.5 22:45:43.1 22:53:46.0 22:56:19.3 22:57:03.5 9 10 R.H. Lang et al. is then used to generate a spatially integrated spectrum of the detection, using a box size based on the extent of the HI. The spectrum is generated using MBSPECT which also gives a measurement of the peak and integrated flux of each detection, as well as the 50 per cent and 20 per cent velocitywidth, the rms noise and barycentric velocity. Table 2 presents the derived parameters for the sample of confirmed HIJASS sources. Column 1 gives the HIJASS Name. Columns 2 and 3 give the Right Ascension (J2000) and Declination (J2000) from the IMFIT task. Columns 4-6 R list the zeroth order moment (Integrated flux SInt = SV dV ), the peak flux (Speak ), and the noise (rms dispersion around the baseline, σ); all as measured by MBSPECT. Columns 79 give the first order moment (barycentric velocity V⊙ ), the velocity width at 20 per cent of the peak flux (∆V20 ), and the velocity width at 50 per cent of the peak flux (∆V50 ), all measured by MBSPECT in the radio frame and converted to cz. The error in integrated flux is calculated from the rms noise on the spectrum and the velocity extent of the source. Columns 10-13 contain the details of any counterpart to the HIJASS source, as listed in the NASA/IPAC Extragalactic Database (NED). Column 10 contains one of five possible classifications. If there is no object within NED which could be spatially coincident with the HIJASS source (defined as being within 6 arcmin), then Column 10 contains the classification ‘PUG’ (i.e. Previously Uncatalogued Galaxy). If there is an object in NED which matches the HIJASS source in both position and space (defined as being within 6 arcmin and 100 km s−1 ) then this is listed as ‘ID’ (Identification). Those IDs which have been detected in HI for the first time by HIJASS are denoted by an asterix, i.e. ‘ID*’. If there is an object within NED which is spatially coincident with the HIJASS source (i.e. within 6 arcmin) but for which no redshift is listed in NED, then Column 10 contains the classification ‘ASS’ (i.e. Association). In several cases, there is more than one galaxy within 6 arcmin: in these cases the classification ‘ASS*’ is used. For the ID, ID* and ASS classifications, Column 11 lists the object within NED which appears to correspond to the HI detection. Column 12 lists the position offset (in arcmin) of the coordinates of the optical counterpart from the HI position. Column 12 lists (for the IDs and ID*s) the velocity offset of the barycentric velocity contained within NED from the barycentric velocity as measured by HIJASS. 4 4.1 PROPERTIES OF THE HIJASS GALAXIES Composition of the sample There are currently 222 sources included in the sample of confirmed HIJASS sources. Of these, 170 (77 per cent) are clearly associated with a previously catalogued galaxy (classification ID or ID*). However, 25 of these 170 objects have been detected in HI for the first time by HIJASS (classification ID*). For 4 of these 170 sources, HIJASS appears to be measuring HI from a pair or a small group of galaxies which lie at the redshift of the HI. There are a further 23 HIJASS sources (10 per cent of the whole sample) which lie within 6 arcmin of a catalogued galaxy for which no redshift is reported in NED (classification ASS or ASS*). These HIJASS sources may or may not be associated with the catalogued galaxy. 15 of these sources have only one possible optical counterpart within 6 arcmin of the HI position (classification ASS). We may be relatively confident about the optical identification of these sources. However, even for these sources there remains the possibility that the HI has been detected from an associated HI cloud (cf. Ryder et al. 2001) or a LSB companion. The other 8 of the 23 sources have more than one galaxy within 6 arcmin of the HIJASS position (classification ASS*). We intend to obtain accurate positions for all 23 of these sources using HI aperture synthesis observations, so as to unambiguously determine the optical counterpart of each source. There are then a further 29 sources (13 per cent of the whole sample) which do not lie within 6 arcmin of any previously catalogued galaxy (classification PUG). A study of the Digital Sky Survey (DSS) at the positions of these sources reveals an obvious and unambiguous optical counterpart in only 5 cases (J0327+67, J0721+74, J1720+71, J2016+75 and J2151+71). Fig. 2 presents the DSS images of these five PUGs. Three of these objects (J0327+67, J2016+75, J2151+71) have a compact but relatively high surface brightness core but a low surface brightness disk. They may have been excluded from optical catalogues because they were mistaken for stars. One object (J0721+74) is a highly inclined but relatively high surface brightness object, although very small (≃1 arcmin diameter). The fifth object (J1720+71) has a complex morphology and appears to be involved in some kind of interaction or merger. A study of the DSS for the other 24 PUGs, reveals no unambiguous optical counterpart. In many cases there are several possible optical candidates within the positional uncertain of HIJASS. In several cases, however, no possible candidate can be seen. The optical counterparts of these sources must be of very low surface brightness. All of the PUGs will have accurate positions determined from aperture synthesis observations and will be the subject of deep optical follow-up work. It is interesting to compare the number of PUGs found in the sample of confirmed HIJASS sources with those found in the Bright Galaxy Catalogue (BGC: Koribalski et al., in preparation). The BGC contains the 1000 brightest (in HI peak flux) sources in the whole of the HIPASS sample. 87 of these objects had not been previously catalogued, although 57 of these lie close (within 10 ◦ ) to the Galactic plane. Of the other 30 previously uncatalogued galaxies within the BGC, Ryan-Weber et al. (2002) found a single optical counterpart for 25 on the DSS. Whilst the relative number of previously uncatalogued galaxies within the BGC is much smaller than within the HIJASS sample (3 per cent compared to 13 per cent), most of the BGC objects can be unambiguously assigned to an optical counterpart on the DSS, whilst most of the HIJASS PUGs cannot be. These differences are probably primarily due to the different flux limits of the two samples. The faintest source in the BGC has a peak flux of 116 mJy. Only 6 of the 29 HIJASS PUGs have a peak flux larger than this. The much lower peak flux limit of HIJASS has produced a much larger fraction of PUGs compared to the BGC. Since these have generally lower HI flux, they are correspondingly harder to detect in optical data. As it currently stands, the sample of confirmed HIJASS sources presents the first HI measurement of 77 galaxies (i.e. classes ID*, ASS, ASS*, PUG), 35 per cent of the whole samc 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey (a) HIJASS J0327+67 (b) HIJASS J0721+74 (d) HIJASS J2016+75 (e) HIJASS J2151+71 11 ( ) HIJASS J1720+71 Figure 2. Digitial Sky Survey images of the 5 PUGs for which an obvious and umabiguious optical counterpart can be seen. Each image is 5 arcmin×5 arcmin. ple. It presents the first redshift measurement of 52 galaxies (i.e. classes ASS, ASS*, PUG), 23 per cent of the whole sample. Between 29 and 52 (13 and 23 per cent) of the objects within it have not been previously catalogued. It must also be noted that the ‘possible’ detections from the 2002 observing run have not yet been followed up. Based on the results of previous narrow-band follow-up, this will probably lead to an additional 5-10 sources being added to the sample, many of them previously uncatalogued sources. 4.2 Peak and integrated flux distributions The main factor which determines the inclusion of a galaxy within the HIJASS sample ought to be its peak flux (rather than integrated flux). Eyeball searches are inevitably drawn to sources with larger peak fluxes. The POLYFIND automated finding algorithm also initially looks for peaks in individual pixels. Fig. 3 is a histogram of the peak flux of every source in the sample of confirmed HIJASS sources. For a peak flux limited survey of a homogeneous distribution of −5/2 galaxies we expect Nobj ∝SPk . The curve on Fig. 3 shows the best fit of this function to the observed distribution. This implies that our sample is complete to SPk ≃80 mJy. We noted above that the rms noise in HIJASS data shows considerable variation between cubes. In particular, the cubes from the 2002 run have considerably lower noise. The completeness limit of 80 mJy corresponds to a 5σ detection in the pre-upgrade data. The 3σ detection limit for the postupgrade data is at ≃39 mJy. Only 2 sources have a peak flux less than this. c 1994 RAS, MNRAS 000, 1–?? Figure 3. Peak flux distribution of HIJASS sources. The curve −5/2 shows the best-fit to the data of the function Nobj ∝SPk , i.e. that expected for a peak flux limited sample of a homogeneous distribution of galaxies. Fig. 4 is a plot of SPk against 20% velocity-width (∆V20 ). Marked on this is the peak flux detection limit at SPk =39 mJy (3σ for the post-upgrade data). This figure also shows another important selection effect in our sam- 12 R.H. Lang et al. Figure 4. Plot of SPk against ∆V20 for the sample of confirmed HIJASS sources. The short-dashed line shows the 3σ peak flux detection limit for the post-upgrade data at 39 mJy. The longdashed line shows the velocity-width limit equivalent to 4 chan−1 . nels, ∆Vlim 20 =52.8 km s Figure 5. Plot of log (SInt ) against ∆V20 for all the galaxies in the HIJASS sample. The long-dashed line is the locus of equation (3) for Slim pk =48 mJy (i.e. a 3σ detection from the pre-upgrade observing runs). The short-dashed line is the locus of equation (3) for Slim =39 mJy (i.e. a 3σ detection from the post-upgrade Pk observing run). ple: we detect few galaxies at ∆V20 <50 km s−1 . This is because there is a minimum believable velocity-width which a galaxy must have in order to be selected as a real source from our data. Sources with a narrower velocity-width will be mistaken for narrow band radio frequency interference. From the data it appears that this minimum believable velocity-width is around 4 channels wide for ∆V20 , i.e. −1 ∆Vlim . This makes intuitive sense as it allows 20 =52.8 km s 2 ‘high’ channels where the source is seen and believed and 2 ‘low’ channels where the flux is dropping off down to the 20 per cent level. The locus of this limit is drawn on Fig. 4 and constrains the data well. In Section 5 we consider the implications of this velocity-width limit for the completeness of HI-selected samples of galaxies. Because the HIJASS sample is approximately peak flux limited, the detection of a galaxy of a given integrated flux, SInt , will (even in similar noise) be a function of its velocitywidth: broader velocity-width galaxies of a given integrated flux have a lower peak flux and therefore are less likely to be detected than a narrower galaxy of the same integrated flux. This is clearly seen in Fig. 5, a plot of log(SInt ) against ∆V20 . From this can be seen a clear trend for the minimum detected integrated flux to increase with increasing velocitywidth. For a given profile shape we expect the integrated flux, SInt , 20% velocity-width, ∆V20 , and the peak flux, SPk , to be related via least-squares best-fit to this data produces a mean value of k≃0.6. Adopting this value we can say SInt = k ∆V20 SPk (1) where k is a constant which depends on the profile shape. For a top-hat function k≃1, for a Gaussian k≃0.7. Fig. 6 is a plot of SInt against ∆V20 .SPk for all galaxies in the HIJASS sample. The linearity of this relationship is clear although there is some expected scatter in the value of k. A SInt ≃ 0.6 ∆V20 SPk (2) for the HIJASS sample. Hence, for a given peak flux limit, lim Slim Pk , the integrated flux limit, SInt is a function of ∆V20 via: lim lim SInt ≃ 0.6 ∆V20 SPk (3) Slim Pk =48 The loci of this relationship for mJy (i.e. a 3σ detection from the pre-upgrade observing runs) and for Slim Pk =39 mJy (i.e. a 3σ detection from the post-upgrade observing run) are plotted on Fig. 5. These describe well the form of the observed cut-off in SInt as a function of ∆V20 . It is worth noting that the fact that our sample is essentially peak flux limited has a dramatic effect on the proportion of broad velocity-width to narrow velocity-width galaxies included in the sample, compared to the proportion we would expect to find in an integrated flux limited sample. For the sake of illustration, we consider the fraction of galaxies with SInt >3 Jy km s−1 which will be included in the HIJASS sample as a function of velocity-width. The value of 3 Jy km s−1 corresponds to a galaxy of velocitywidth 100 km s−1 with a peak flux of about 48 mJy (the 3σ limit for the pre-upgrade data). At ∆V20 =100 km s−1 , all galaxies with SInt >3 Jy km s−1 will be included in the HIJASS sample. However, at broader velocity-widths, the integrated flux limit will increase [equation (3)] and the sample will contain a progressively smaller fraction of galaxies with SInt >3 Jy km s−1 . In Table 3 we list (Column 2) the Slim Int values equivalent to a range of ∆V20 values (Column 1) using equation (3) and assuming SPk =48 mJy. For each pair of ∆V20 , Slim Int values we list (Column 3) the fraction of galaxies with SInt >3 Jy km s−1 which will be missing from the HIJASS c 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey Figure 6. Plot of SInt against ∆V20 .SPk for the galaxies in the sample of confirmed HIJASS sources. Table 3. The fraction of galaxies with SInt >3 Jy km s−1 which will be missed from the HIJASS sample as a function of ∆V20 . This assumes Slim Pk =48 mJy and that the distribution of galaxies in space at each ∆V20 is homogeneous. ∆V20 km s−1 150 200 250 300 350 400 Slim Int Jy km s−1 frac of gals missed 4.32 5.76 7.20 8.64 10.08 11.52 0.42 0.62 0.73 0.80 0.84 0.87 sample. This has been calculated assuming a homogeneous −5/2 distribution of sources with Nobj ∝SInt at each ∆V20 . −1 At ∆V20 =150 km s only 68 per cent of galaxies with SInt >3 Jy km s−1 will be included in the HIJASS sample. At ∆V20 >300 km s−1 less than 20 per cent of galaxies with SInt >3 Jy km s−1 will be included. This is a particularly important selection effect since we might reasonable expect that broader velocity-width galaxies will tend to have higher HI masses (see e.g. Rao & Briggs 1993). Hence, compared to an integrated flux limited sample, our selection techniques may be significantly biased against the inclusion of higher HI mass galaxies. This effect will not bias an HIMF derived from the data provided that the selection effect is properly accounted for. It does, however, mean that the morphological mix of galaxies revealed by a blind HI survey is going to be biased towards narrow velocity-width dwarf galaxies and away from broad velocity-width giant galaxies. This bias needs to be born in mind when considering the relative proportions of the different morphologies of galaxies in an HIselected sample. c 1994 RAS, MNRAS 000, 1–?? 13 Figure 7. Histogram showing the distribution of the offset between HIJASS source position and the position of the identified optical counterpart. 4.3 Positional accuracy of HIJASS The positional accuracy of HIJASS sources can be judged by considering the offset between the HIJASS positions and the positions listed in NED for those galaxies identified as being associated with each HIJASS source (i.e. the IDs and ID*s). Fig. 7 shows a histogram of these offsets. The majority of HIJASS sources (71 per cent) lie within 2.5 arcmin of the NED position, with only a very small fraction (7 per cent) lying beyond 4 arcmin. 4.4 Mass distribution Fig. 8(a) shows a histogram of the distribution of HI masses for the whole of the sample of confirmed HIJASS sources. Galaxies within the M81 group have been assumed to lie at 3.63 Mpc (Freedman et al. 1994). The distances of the other galaxies have been determined from their redshifts (assuming Ho =75 km s−1 Mpc−1 ). There is a peak in this distribu⋆ tion at ∼109.6 M⊙ . This is close to the value found for MHI 9.75 of 10 M⊙ by Zwaan et al. (1997). Although the HIJASS bandpass stretches to 10000 km s−1 , the RFI problem beyond cz=4500 km s−1 effectively places a bandpass limit at this point. A galaxy with an HI mass of 109.75 M⊙ would have an integrated flux of about 6.6 Jy km s−1 at this cz=4500 km s−1 . This is similar to the limiting integrated flux one would expect for a −1 broad velocity-width (> ∼200 km s ) galaxy. Hence, HIJASS ⋆ is effectively bandpass-limited for galaxies with MHI > ∼MHI ⋆ (assuming Zwaan et al.’s value for MHI ). For galaxies with ⋆ MHI < ∼MHI , HIJASS is flux limited. Fig. 8(b) shows the HI mass distribution only for those 77 galaxies which had not previously been detected in HI (i.e. classes ID*, ASS, ASS* and PUG) . This distribution is very similar to that of the whole sample. In fact, most of those 25 previously catalogued galaxies which had not previously been detected in HI, have HI masses be- 14 R.H. Lang et al. Figure 8. (a) MHI distribution of the whole of the HIJASS sample; (b) MHI distribution of the 77 galaxies which had not previously been detected in HI (classes ID*, ASS, ASS*, PUG); (c) MHI distribution of the 52 galaxies with no previous redshift measurement (classes ASS, ASS*, PUG); (d) MHI distribution for the 29 PUGs. Figure 9. (a) The cz distribution of the whole of the HIJASS sample; (b) the cz distribution of the 77 galaxies which had not previously been detected in HI (classes ID*, ASS, ASS*, PUG); (c) the cz distribution of the 52 galaxies with no previous redshift measurement (classes ASS, ASS*, PUG); (d) the cz distribution for the 29 PUGs. tween 109.3 –109.8 M⊙ . All but 2 have integrated fluxes above 10 Jy km s−1 . These would appear to mostly be ‘normal’ galaxies which had simply not been observed in HI prior to HIJASS. Fig. 8(c) shows the HI mass distribution for the 52 HIJASS objects which had no previous redshift measurement (classes ASS, ASS*, PUG). The peak at 109.5 M⊙ is much less pronounced in this plot. A weaker peak in this distribution can be seen at 108.9 M⊙ . A peak at this mass is clearly seen in Fig. 8(d) which plots the HI mass distribution for the 29 PUGs. The peak in this distribution is at about 108.9 M⊙ , an order of magnitude below the peak in the distribution for the whole sample. In fact 69 per cent of the PUGs lie at MHI <109 M⊙ . In comparison only 39 c 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey per cent of the full sample lie in this mass range. A similar result was found by Ryan-Weber et al. (2002) for the 30 previously uncatalogued galaxies in the BGC at |b|>10◦ . They found the mass distribution of these 30 galaxies to peak at 108.7 M⊙ , compared to a peak at 109.5 M⊙ for the whole of the BGC. This tendency for the newly discovered galaxies to have lower HI masses suggests a correlation between HI mass and optical detectability. 4.5 Velocity distribution Fig. 9(a) shows the distribution of all the HIJASS galaxies as a function of cz. The peak close to 0 km s−1 is due to galaxies in the Local Group and the M81 Group. Beyond that there are prominent peaks at cz∼1200 km s−1 and 2500 km s−1 . These are due to large-scale structure. Note that only a handful of galaxies have been identified beyond 4500 km s−1 . This is mainly due to the increasing problems of RFI beyond this point and the difficulty of distinguishing any galaxies from interference. Fig. 9(b) shows the cz distribution for all of those 77 galaxies which had not previously been detected in HI (Classes ID*, ASS, ASS*, PUG). This distribution is very similar to that of the whole sample. Fig. 9(c) shows the cz distribution for the 52 objects which had no previous redshift measurement (classes ASS, ASS*, PUG). Fig. 9(d) plots the HI mass distribution just for the 29 PUGs. All of these distributions show the same peaks at cz=1200 km s−1 and 2500 km s−1 as that seen in Fig 8(a). Clearly, the distribution of new HI detections, new redshift measurements and newly catalogued galaxies follows that of the large-scale structure as revealed by the whole sample. This is particularly interesting in regard to the previously uncatalogued galaxies. These have a HI mass distribution with a peak an order of magnitude lower than that of the whole sample (see Fig. 8(d)) but the cz distribution is not skewed to nearer distances. The relationship of HIJASS galaxies to large-scale structure is further explored in Fig. 10. This is a diagram showing the relationship of HIJASS galaxies (filled triangles) and all objects with redshifts in NED (open circles) in the complete R.A. strip between Decl.=70◦ →78◦ . The general association of HIJASS sources with the large-scale structure as delineated by the NED objects is clear. Most of those previously uncatalogued objects found by HIJASS lie in regions already populated with galaxies. Some of the structures which can be seen in the data include the group of galaxies at R.A.∼17h , V⊙ ∼1200 km s−1 (which includes NGC 6217, NGC 6236, NGC 6248 and NGC 6395); the NGC 4291 group at R.A.∼13h , V⊙ ∼1600 km s−1 ; a group including UGC 03317, UGC 03343 and UGC 03403 at R.A.∼6h , V⊙ ∼1200 km s−1 ; and two prominent ‘walls’, at R.A.∼3h →5h , V⊙ ∼2600 km s−1 and at R.A.∼7h →10h , V⊙ ∼2300 km s−1 . We have thus far failed to positively detect any galaxy beyond cz=4800 km s−1 . The presence of RFI between cz=4500–7500 km s−1 makes the detection of galaxies in the region practically impossible. None the less, the band between 7500-9000 km s−1 is generally free from RFI and we ought to be able to detect any galaxies in this region. However, to be detectable beyond cz=7500 km s−1 , a galaxy 10.9 M⊙ . Such objects must would need an HI mass of > ∼10 c 1994 RAS, MNRAS 000, 1–?? 15 be very rare. For example, Kilborn et al.’s (2002) survey of 2400 deg2 of HIPASS data did not detect any galaxy this massive. Minchin (2001) presented results from surveying a 32 deg2 with the Parkes multibeam system to 12× the standard HIPASS exposure time. No galaxy with MHI >1010.6 M⊙ was detected. 4.6 Comparison to HIPASS Following the first stage of the Lovell telescope upgrade, the rms noise in HIJASS data is around 12-14 mJy beam−1 . The typical noise in HIPASS data is ∼14 mJy beam−1 , although there is considerable variation between HIPASS cubes with rms spanning the range 9-17 mJy beam−1 . The data at R.A.≃12h 08m →12h 34m , Decl.=22◦ →30◦ , observed during the 2002 run, was taken specifically because it provides a small overlap with the HIPASS survey between Decl.=22◦ →25◦ . Fig. 11 shows the integrated fluxes from HIPASS and HIJASS cubes for those galaxies which lie in the overlap region. The calibration between the surveys appears robust. As noted in Section 4.4, terrestrial-based RFI effectively limits the HIJASS bandpass to cz<4500 km s−1 whereas HIPASS can survey out to 12700 km s−1 . However, only ⋆ −1 galaxies with MHI > ∼MHI can be seen beyond 4500 km s in HIPASS data. In fact less than 24 per cent of the HIPASS sample presented by Kilborn et al. (2002) lies beyond 4500 km s−1 . HIPASS therefore, has an advantage over HIJASS in that very massive sources can be detected over ⋆ larger volumes. However, for galaxies with MHI < ∼MHI , both HIJASS and HIPASS are flux limited and HIJASS is potentially more sensitive. 5 INCLINATION-DEPENDENT SELECTION EFFECTS IN AN HI-SELECTED SAMPLE The distribution function of neutral hydrogen masses among galaxies and intergalactic clouds (the HI mass function, HIMF) and, more generally, the neutral hydrogen density in the local Universe, ΩHI , are important inputs into models of cosmology and galaxy evolution. Prior to the advent of blind HI surveys, astronomers were restricted to constructing an HIMF by making HI measurements of optically selected samples of galaxies (see, e.g. Rao & Briggs 1993; Solanes, Giovanelli & Haynes 1996). In recent years several authors have attempted to determine the HIMF of the local Universe using an HI-selected sample of galaxies, with conflicting results. For example, using the data from the the Arecibo HI Strip Survey (Sorar 1994), Zwaan et al. (1997) derived an HIMF with a shallow faint end slope (α=1.2) consistent with earlier HIMFs derived from optically selected samples. In contrast the HIMF derived from the Arecibo Slice survey (Schneider, Spitzak & Rosenberg 1998; Spitzak & Schnedier 1998) has an upturn in its lowest mass bin, although this is due to only 2 galaxies in this bin. Recently, Rosenberg & Schneider (2002) have also reported a steep faint end slope (α≃1.5) to the HIMF they have derived from the Arecibo Dual-Beam Survey (Rosenberg & Schneider 2000). HIPASS and HIJASS will provide much larger samples of galaxies and greatly improve the statistics of such determinations of the HIMF. 16 R.H. Lang et al. 6 4000 3000 2000 1000 12 0 18 Figure 10. Distribution of R.A. vs cz of HIJASS galaxies in the range Decl.=70◦ →78◦ (filled triangles). Also shown (open circles) is the R.A. vs cz distribution of all galaxies within NED within this declination range and with measured redshifts. However, previous studies based upon HI-selected samples of galaxies have tended to overlook the important effect that the inclination of a galaxy to the line of sight could have on its inclusion in such a sample. There are two factors to be considered. Firstly, highly inclined galaxies may suffer from significant self-absorption. Studies of the HI emission from galaxies have generally assumed that the HI line is optically thin in all circumstances. Relatively few authors (e.g. Epstein 1964a,b; Haynes & Giovanelli 1984) have addressed the issue of whether the HI emission from galaxies is actually optically thin in all galaxies. If this assumption is not valid for highly inclined galaxies, then the HI masses of such galaxies will have been underestimated. Some highly inclined galaxies will be missed altogether from an HI-selected sample of galaxies, despite less inclined galaxies of the same HI mass being included. Both of these effects will lead to errors in the derived HIMF. Secondly, as noted in Section 4.2, there is a minimum believable velocity-width, ∆Vlim 20 , which an object in a blind HI survey must have in order to be distinguishable from narrow-band radio frequency interference. For any given type of galaxy, the measured velocity-width will be narrower the more face-on the galaxy is. Hence, some galaxies with inclinations close to the line of sight could be missed. In this section, we use the sample of confirmed HIJASS sources to study the relative seriousness of these two selec- tion effects on the composition of an HI-selected sample of galaxies and the implications this has for derivations of the HIMF and ΩHI . 5.1 The expected distribution of galaxies in an HI-selected sample as a function of inclination angle If the assumption that the 21-cm line of HI is always optically thin is correct, then the relationship between integrated HI flux from a galaxy, SInt (in Jy km s−1 ), and total HI mass, MHI (in M⊙ ), is given by MHI = 2.356 × 105 SInt D2 (4) where D is the distance in Mpc (see e.g. Rohlfs 1986). Now, if we assume that HI emission from any given type of galaxy is not necessarily optically thin, i.e. that there is an inclination-dependent opacity effect, then we can re-write equation (4) as MHI = 2.356 × 105 SInt D2 f (i) (5) where f(i) is the correction factor needed to correct the HI mass derived from the optically thin assumption to the actual HI mass. Assuming this function is significant at all, then f(i) may vary for different morphological types and will increase as inclination angle increases. c 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey 17 To find the expected observed distribution of galaxies as a function of inclination angle, φ(i), we have to multiply the intrinsic distribution of galaxies as a function of i, N(i), by the volume within which a galaxy at a given i can be observed, V(i), i.e. φ(i) ∝  MHI 1 . f (i) ∆V20  23 . sin i (12) The expected observed distribution of the HIJASS sample as a function of inclination angle therefore depends on several other relationships: the distribution of galaxies as a function of MHI ; the relationship (if any) between MHI and ∆Vo ; the relationship between ∆Vo and ∆V20 and inclination angle, i. In Section 5.3 we show that at large i (i.e. >50◦ ) this relationship can be simplified and used to study the effect of HI self-absorption within the HIJASS sample. Firstly, in Section 5.2, we consider the effect of the velocity-width limit on the HIJASS sample at small inclination angles. 5.2 Figure 11. Comparison of integrated fluxes from HIJASS and HIPASS for galaxies in the region 12h 08m →12h 34m , Decl.=22◦ →25◦ . From eqn (5), it follows that the integrated flux, SInt , which a galaxy of HI mass, MHI , and inclination angle, i, will have at a distance of D can be written as: 1 MHI 1 SInt = . . (6) 2.356 × 105 D2 f (i) Hence, if a survey has an integrated flux limit, Slim Int , then the maximum distance, Dmax in Mpc, at which one could detect a galaxy of HI mass, MHI , and inclination angle, i, would be given by Dmax =  1 MHI 1 . . lim 2.356 × 105 f (i) SInt  21 (7) However, as discussed in Section 4.2, the HIJASS sample does not have a single Slim Int value. The sample is approximately peak flux limited and the integrated flux limit varies with velocity-width such that: lim lim SInt ≃ 0.6∆V20 Spk (8) So, for a given peak flux limit, the maximum distance at which a galaxy could lie and still be included in the HIJASS sample is related to its MHI , ∆V20 and i, by: Dmax ∝  MHI 1 . f (i) ∆V20  12 (9) and the volume, V(i) (in Mpc3 ), within which such a galaxy could lie and still be included within HIJASS is related to MHI , ∆V20 and i by: V (i) ∝  MHI 1 . f (i) ∆V20  23 (10) Now, we expect galaxies to be randomly oriented in space. If so then the intrinsic distribution of galaxies as a function of inclination angle, N(i), is described by N (i) ∝ sin i c 1994 RAS, MNRAS 000, 1–?? (11) Effect of the velocity-width limit on the HIJASS sample For a given galaxy, ∆V20 is an observed property which depends on a combination of its rotational velocity, Vrot , its inclination to the line of sight, i, its internal velocity dispersion, ∆Vt (i.e. that due to turbulence and non-planar motions within the galaxy) and the contribution of instrumental broadening to the velocity width, ∆Vinst . For low MHI galaxies, Tully & Fouque (1985) showed that these properties can be related via the equation: ∆V20 = ∆Vo2 (sin i)2 + ∆Vt2  1/2 + ∆Vinst (13) where ∆Vo =2Vrot is the linewidth the galaxy would have if edge-on (i.e. ignoring the internal velocity-dispersion). For higher MHI galaxies, the ∆Vt term adds linearly to the measured velocity-width (see also Verheijen & Sancisi 2001) since these galaxies generally show ‘boxy’ HI profiles rather than the typical Gaussian profiles of dwarf galaxies. However, since the velocity-width limit is more important for dwarf than giant galaxies, we conservatively adopt the quadratic summation of eqn(13). If we assume that a galaxy cannot be seen by the survey if ∆V20 <∆Vlim 20 then we can express the minimum inclination angle that a galaxy must have in order to be included in the sample as imin = arcsin  lim (∆V20 − ∆Vinst )2 − ∆Vt2 ∆Vo2 1/2 (14) To illustrate the effect of the velocity-width limit, we adopt the value ∆Vt =20±2 km −1 found by Rhee (1996) from a study of 28 galaxies with well defined HI velocity fields. This value is in close agreement with those found by similar studies by Broeils (1992) and Verheijen & Sancisi (2001). We use the Bottinelli et al. (1990) estimate of ∆Vinst = 0.55 × R, where R is the velocity resolution of the survey. This gives ∆Vinst =10 km s−1 for HIJASS. We assume −1 ∆Vlim (see Section 4.2). 20 =52.8 km s Table 4 illustrates the effect of the velocity-width cutoff on the number of galaxies included in the HIJASS sample for a range of ∆Vo values (Column 1). Column 2 lists the imin for each ∆Vo , found using eqn(14) and our assumed 18 R.H. Lang et al. Table 4. Illustration of the effect of the velocity-limit selection effect on the inclusion of galaxies within the HIJASS sample. Column 1 is a set of ∆Vo values. Column 2 lists the minimum inclination angle, imin , which a galaxy of each ∆Vo must have in order to be included in the sample (using eqn 14). Column 3 lists ζ, the fraction of galaxies which will be missed from the sample at each ∆Vo . ∆Vo km s−1 40 50 75 100 150 200 250 300 350 400 imin deg ζ per cent 63.5◦ 49.2◦ 30.3◦ 22.2◦ 14.6◦ 10.9◦ 8.7◦ 7.3◦ 6.2◦ 5.4◦ 55.4 34.6 13.7 7.4 3.2 1.8 1.2 0.8 0.6 0.5 values above. As expected this effect gets progressively more serious for inherent narrow velocity-width objects: galaxies with ∆Vo <100 km s−1 cannot be seen with i<22◦ ; galaxies with ∆Vo <50 km s−1 are missed if i<49◦ . The actual fraction of galaxies missed at each ∆Vo can be found by integrating from i=0 to i=imin over a randomly oriented sample (see Zwaan et al., in preparation): ζ= Z imin sin i di = 1 − cos imin (15) o The derived values of ζ are listed in Column 3 of Table 4. Clearly, within HIJASS data, this selection effect becomes progressively more important at smaller ∆Vo . Whilst only 7% of galaxies have been missed at ∆Vo =100 km s−1 , this number has risen to 35% at ∆Vo =50 km s−1 . As noted above, we cannot properly consider the effect that the velocity-width cut-off may have on a derived HIMF without knowing whether there is a relationship between ∆Vo and MHI and, if so, what form that relationship takes. Whilst one could argue about the precise relationship between MHI and ∆Vo , previous studies suggest that the two are related such that more massive galaxies appear to have broader velocity-widths. For example, from HI measurements of an optically-selected sample of galax1/3 ies, Rao & Briggs (1993) derived ∆V20 =0.15MHI . From their HIDEEP sample, Minchin et al.(in preparation) have 0.28 found that ∆V20 =0.42MHI . However, such relations may be partly due to selection effects (see e.g. Minchin 2001). Fig. 12 is a plot of ∆Vo against MHI for 186 HIJASS galaxies for which we have derived inclination angles. This sample includes all of the previously catalogued galaxies (expect those listed as ‘pair’ or ‘group’), the 15 ASSs for which the optical identification was relatively unambiguous (i.e. not the ASS*s) and the 5 PUGs for which an obvious optical counterpart could be seen on the DSS. The inclination for each galaxy was determined from the ratio of the semimajor to the semi-minor axis using the equation: cos2 i = (b/a)2 − ro2 1 − ro2 (16) Figure 12. Plot of log(∆Vo ) against log(MHI ) for those 186 HIJASS galaxies for which we have inclination angles. The solid line is the locus of the relationship ∆Vo =0.42M0.3 HI (equation 20). (Holmberg 1958), where ro is the intrinsic axis ratio of an edge-on disk. Estimates for ro vary between 0.11 and 0.2 for this property. We have assumed a value of 0.16 for every galaxy. Note that this may be significantly inaccurate for low-mass dwarf galaxies, for which Staveley-Smith, Davies & Kinmann (1992) found that values up to about 0.5 may be appropriate. However, relatively few of the galaxies in the HIJASS sample are dwarfs (see Fig. 8a). The values of b/a were taken from the Third Reference Catalogue of Bright Galaxies (de Vaucouleurs et al. 1991) where available. Otherwise they were determined from DSS images of each galaxy using the SExtractor package (Bertin & Arnouts 1996). Included on Fig. 12 is the locus of a line showing the relationship 0.3 ∆Vo = 0.42 MHI (17) which gives the best fit to our data. Note, however, that there is a wide scatter about this locus. There are very few data points at MHI <108 M⊙ and many of these lie a long way from the locus of eqn 17. Hence, the conclusions we draw using this relationship, especially at low MHI , should be treated as only illustrative of the possible effect of ignoring the velocity-width limit selection effect. Table 5 lists the ∆Vo (Column 2) equivalent to a range of MHI values (Column 1), assuming the ∆Vo -MHI relationship of eqn(17). Also listed (Column 3) is the minimum inclination angle imin which a galaxy of each ∆Vo could have and still be included in the HIJASS sample (assuming −1 ∆Vlim ) (from eqn.14). Column 4 lists the frac20 =52.8 km s tional error, ζ, which would be introduced into the HIMF at each mass as a result of the exclusion from the HI-selected sample of galaxies at i<imin (from eqn.15). . As is clear from Column 4 of Table 5, under these assumptions, for the HIJASS sample, we would be significantly underestimating the HIMF at MHI <108 M⊙ if we did not compensate for the velocity-width limit selection c 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey 19 Table 5. Illustration of the effect of the velocity-limit selection effect on the HIMF derived from HIJASS data −1 ). Column 2 shows the ∆V value for a range (∆Vlim o 20 =52.8 km s of MHI values (Column 1), derived assuming eqn (17) (note the caveats about this in the main body of the text). Column 3 shows the minimum inclination angle, imin , at which a galaxy of this ∆Vo would be included in the sample (from eqn 14). Column 4 shows the percentage error in the HIMF at each mass resulting from excluding galaxies with i<imin (from eqn 15) from the sample. MHI M⊙ ∆Vo km s−1 imin deg ζ per cent 65 86 105 171 210 341 420 35.6 26.1 21.1 12.8 10.4 6.4 5.2 18.7 10.2 6.7 2.5 1.6 0.6 0.4 2×107 5×107 1×108 5×108 1×109 5×109 1×1010 effect. What is most striking is that the extent of our underestimate of the HIMF would increase at the low MHI /small ∆Vo end. This implies that HIMFs derived from HI-selected samples without correcting for this effect may have significantly underestimated the steepness of the faint-end slope. There are, however, other complicating factors which may affect the low mass end, e.g. the relationship of Vrot to velocity dispersion in dwarfs (e.g. Lo, Sargent & Young 1993, Staveley-Smith et al. 1992). At best, Table 5 is a warning that a consideration of the effect of the velocity-width cutoff on sample completeness should be an essential part of any derivation of the HIMF. 5.3 Effect of HI self-absoprtion To study the possible impact of HI self-absorption on the HIJASS sample, we ideally wish to study the actual observed distribution of inclination angles of the sample against that predicted for a sample with no HI self-absorption. Eqn (12) describes the expected observed distribution of galaxies as a function of inclination angle, φ(i). As noted above, this is a complex function which depends on the relationship betwwen ∆Vo and MHI and that between ∆Vo and ∆V20 . However, if we restrict our analysis to large inclination angles then we can reasonably make two simplifying assumptions. The first is that we are not missing a significant number of galaxies due to the velocity-width limit selection effect. As noted in Table 4, only a galaxy with ∆Vo <50 km s−1 will be missed due to this effect at i<50◦ . The second is that at i>50◦ the thermal velocity dispersion, Vt , no longer makes a significant contribution to V20 and, hence, we can assume that ∆V20 ≃ ∆Vo sin i (18) In this case, the expected observed distribution of galaxies as a function of i can be written as φ(i) ∝ h MHI ∆Vo i 23  . 1 f (i)  32 h . 1 sin i i 12 (19) Since MHI and ∆Vo are constant for a given galaxy, the expected observed distribution of all galaxies in the HIJASS c 1994 RAS, MNRAS 000, 1–?? Figure 13. Histogram showing observed distribution of HIJASS galaxies as a function of inclination angle, i, for galaxies with i>50◦ . Each bin has width 8◦ . The short-dashed line shows a φ(i) function, fitted to the observed distribution in the range i=50◦ →74◦ (assumes no self-absorption). The long-dashed line shows the best fitting φ(i) function to galaxies in the range i>50◦ (assumes self-absorption with a best fit value of β=0.2). sample as a function of inclination angle can then be described by φ(i) ∝ f (i)−1.5 (sin i)−0.5 (20) The implication of this equation is that, in the absence of significant self-absorption, we expect to see a relatively flat distribution at i>50o . Fig. 13 presents a histogram of the derived inclination angles for those of the 186 HIJASS galaxies for which we have derived inclination angles where i>50◦ (105 galaxies). In the optically thin scenario, we expect a very shallow falloff in the observed distribution at high inclination angles. We actually observe a sharp fall in the observed number of galaxies at i>74◦ . This could be because self-absorption becomes significant in at least some galaxies at these high inclinations. We can quantify the effect of self-absorption if we assume that the sample of galaxies in the range i=50◦ →74◦ is free from the effects of both the velocity-width cut-off and HI self-absorption. Note that the velocity-width limit will tend to flatten the observed distribution as a function of i, so this assumption may lead to us underestimating the effects of self-absorption rather than over-estimating it. We have fitted a φ(i) function to the observed distribution in the range i=50◦ →74◦ . The best fit was determined by normalising φ(i) such that the theoretical number of galaxies in the range i=50◦ →74◦ is equal to the observed number of galaxies in this range. The best fitting φ(i) function is plotted on Fig. 13 (short-dashed line). This best fitting φ(i) distribution predicts that there should be 51±7 galaxies at i>74◦ . This compares to the observed number of 25 galaxies, i.e. a 3.5σ shortfall of galaxies. An alternative fit can be made by normalising the theoret- 20 R.H. Lang et al. ical φ(i) function in the range i=50◦ →74◦ to 1σ below the total observed counts in this range. Such a best fit predicts that there should be a total of 44±7 galaxies at i>74◦ , still 2.5σ above the number observed. The largest previous study of this issue was that of Haynes & Giovanelli (1984) who obtained HI measurements of 288 isolated galaxies using the Arecibo 305-m telescope. They compared the HI surface density (defined as the ratio of integrated HI flux to optical surface area of the galaxy) with the axial ratio for the galaxies as a function of morphological type. They found that for Sa, Sab, Sb, Sbc and Sc galaxies there was a clear trend for the measured surface density to fall as inclination to the line of sight increases. The implication of this is that the measured column depth of a highly inclined galaxy is less than it would be for more face-on objects because a fraction of the HI is being selfabsorbed. Haynes & Giovanelli found a general tend for f(i) [the inclination-dependent HI mass correction factor - see eqn (5)] to vary as f (i) = (cosi)−β (21) where β is a constant dependent on morphological type. They found values of β of 0.04 for Sa and Sab, 0.16 for Sb, and 0.14 for Sbc and Sc galaxies. They found no corrections to be necessary for galaxies earlier than Sa or later than Sc, indicating self-absorption to be negligible in these types. We adopt a similar form for f(i) and used a χ2 minimisation technique to derive the value of β which gives a best fit to our observed distribution at i>50◦ . This best fitting value is β=0.2. This ignores the possible dependence of β on morphological type. The φ(i) function derived using β=0.2 is shown on Fig. 13 (long-dashed line). This value is significantly larger than the largest value derived by Haynes & Giovanelli (1984). Note, however, that our model does not provide a particularly good fit to the data above i=74◦ , especially in the bin centered at i=78◦ . This may be a consequence of the relatively small total number of galaxies in our sample or of the assumed functional form of f(i) not being appropriate. Using the argument of Zwaan et al. (1997), the average effect of self-absorption on measured MHI can be obtained by averaging f(i) over a random distribution of inclinations. < f (i) >= R π/2 o (cos i)−β sin i di R π/2 o sin i di = 1 1−β (22) giving a mean correction over all inclinations of <f(i)>=1.25 for β=0.2. We have no knowledge of how f(i) varies with MHI or morphological type. If it is uncorrelated with MHI then the effect of this on the HIMF would be to shift galaxies of each mass to higher masses by an average factor of 1.25. This would lead to a corresponding increase in M⋆HI . The shape of the HIMF would be unaltered. This correction factor of 1.25 to M⋆HI is a lower limit for two reasons. Firstly, we found a best fitting β-corrected φ(i) function by assuming that the velocity-width limit effect was not significant at i>50◦ . As is clear from Table 4, some intrinsically narrow velocity-width galaxies will be lost even at i>50◦ . Hence, our value of β is a lower limit. Secondly, in deriving <f(i)> we have averaged over all i. We should actually integrate over i=imin →90◦ for any given ∆Vo (since galaxies at i<imin will not have been included in the sample). This would have the effect of increasing <f(i)> for those galaxies actually included in the sample. We also have to account for the fact that self-absorption is not only causing us to underestimate the mass of some galaxies, but is also causing some galaxies to be excluded from the sample altogether. In a randomly oriented sample of galaxies, 28 per cent of the contribution to the HIMF should come from galaxies with i>74◦ . However, at i>74◦ we are missing at least 40 per cent of those galaxies which we would expect to see in the absence of self-absorption. If we assume that self-absorption is not correlated with ∆Vo or MHI then this effect will cause us to underestimate the HIMF by a factor of 1.14 at each MHI , i.e. to derive the correct HIMF we would need to correct the normalisation θ* by a factor of at least 1.14. The combined effect of the correction factors of 1.25 in M⋆HI and 1.14 in θ* would be to increase the derived value of ΩHI by at least 25 per cent. Experience in the optical suggests that correcting for the number of self-absorbed discs in a survey, using only those you can see, is extremely model-dependent (Disney, Davies & Phillipps 1989; Witt, Thronson & Capuano 1992). For instance, in the present case the optical depth could vary by an order of magnitude as between flat and solid rotation curves. All we can truly say for now is that an HIselect survey like ours would, of all surveys, be most likely to run into HI self-absorption, and that the affect is plainly significant. How significant remains a question for the future. 6 CONCLUDING REMARKS This paper has described the properties of the present sample of confirmed sources derived from the HIJASS data. This sample will be added to as further sources are confirmed. This will obviously follow further observing runs on the Lovell telescope. However, there is scope within existing HIJASS data for adding to the present sample. As noted in Section 3.1, the ‘possible’ detections from the 2002 run have not yet been followed up by single-beam narrow-band observations. Those confirmed in this way will then be added to the sample. We noted in Section 4.2 the important selection effect that, because our sample is effectively peak flux limited, the integrated flux limit is a function of ∆V20 . This leads to a major bias against galaxies with broad velocitywidths (and presumably higher HI masses). We are developing alternative detection techniques with the aim of detecting broader velocity-width sources to similar integrated flux levels as we can presently detect narrow-line sources. There is a further possibility that nearby spatially extended objects may be removed from the data by the conventional bandpass correction algorithm used by LIVEDATA. Alternative algorithms are being tested to determine if any sources have been lost in this way. We are also considering ways of detecting massive galaxies in the data between cz=7500–9000 km s−1 . It is possible that any galaxies massive enough to be detectable at this distance will have very broad velocity-widths and hence, be hard to actually detect despite their mass. We have embarked upon a detailed follow-up program in order to fully study the astrophysical nature of the objects within the HIJASS sample: in particular the previously uncatalogued objects. As discussed in Section 1, the addition of these previously uncatalogued objects to the extrac 1994 RAS, MNRAS 000, 1–?? First Results from the HI Jodrell All Sky Survey galactic census of the local Universe could have a significant impact not only on determinations of the luminosity density and mass density of the local universe but also on our understanding of the processes of galaxy formation and evolution. They could be systems which have undergone a very different formation process and/or evolutionary path than optically selected galaxies. Are they old galaxies which have evolved slowly and have yet to transmute most of their gas into stars ? Or are they young objects which are still at an early stage of their star formation histories ? Are they objects which have recently accreted large amounts of HI ? To determine this we require information on their morphological and structural properties; on their stellar populations; and on their star formation rates, star formation histories and metalicities. All of the potential new detections will be observed using the Westerbork Synthesis Radio Telescope (WSRT) in order to get accurate positions for these objects and to map the distribution of HI within them. This will also enable us to decide which of the 23 objects lying close to a catalogued galaxy with no measured redshift (ASSs) are actually associated with that previously catalogued galaxy and which are new objects. Broad band imaging is being undertaken with the Isaac Newton Telescope of the most interesting objects. We are attempting to detect Hα emission from the nearer of the objects using the Jakobus Kapteyn Telescope. We have also been awarded time on the William Herschel Telescope to obtain IR imaging of several of the objects. Future publications will present the results of this follow-up program. We have shown, using the HIJASS sample, that selfabsorption is a significant, but often overlooked, effect in galaxies at high inclinations. Properly accounting for it could increase the derived HI mass density by at least 25 per cent and possibly a lot more. The effect this will have on the shape of the HIMF will depend on how self-absorption affects galaxies of different ∆Vo . We have also shown that the velocity-width limit will always act so as to exclude low inclination angle galaxies from HI-selected samples. This affect will become progressively more serious at lower ∆Vo values. If, as we might expect, galaxies with smaller intrinsic velocity-widths have smaller HI masses, then compensating for this effect could significantly steepen the faint end of the HIMF. ACKNOWLEDGMENTS The construction of the multibeam receiving system at Jodrell Bank was made possible by the UK PPARC (Grant No. GR/K28237 to Jodrell Bank). The HI Jodrell All Sky Survey is funded by the UK PPARC (Grant No. PPA/G/S/1998/00620 to Cardiff). Both grants are gratefully acknowledged. PJB and RFM also acknowledge the financial support of the UK PPARC. We thank the Director of the Jodrell Bank Observatory, Prof. Andrew Lyne, for granting the observing time for HIJASS and for making available the facilities of the observatory. We thank CSIRO Radiophysics in Australia for producing much of the design and engineering of the system. We also thank the following for their help with HIJASS: Gareth Banks, Dave Brown, Mark Calabretta, Jim Cohen, Jon Davies, Rod Davies, Judy Haynes, Anthony Holloway, Ian Morison, Rhys Morris, Rodc 1994 RAS, MNRAS 000, 1–?? 21 ney Smith, Lister Staveley-Smith, Daniel Zambonini and the staff and students of the Jodrell Bank Observatory. 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