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. This
research has made use of the NASA/IPAC Extragalactic
Database (NED) which is operated by the Jet Propulsion
Laboratory, Caltech, under agreement with the National
Aeronautics and Space Administration. This research has
also made use of the Digitised Sky Survey, produced at
the Space Telescope Science Institute under US Government
Grant NAG W-2166.
REFERENCES
Banks G.D., et al., 1999, ApJ, 524, 612
Barnes D.G. et al., 2001, MNRAS, 322, 486
Baugh C., Cole S., Frenk C.S., 1996, MNRAS, 283, 1361
Bertin E., Arnouts S., 1996, A&AS, 117, 393
Bell E.F., Bower R.G., 2000, MNRAS, 319, 235
Bell E.F., de Jong R.S., 2000, MNRAS, 312, 497
Bird T.S., 1994, in IEEE Antennas & Propagation Symposium.
Seattle, p.966
Bird T.S., 1997, in IEEE Antenna & Propagation Society Symposium, Montreal, p. 1618
Bottinelli L., Gouquenheim L., Fouque P., Paturel G., 1990,
A&AS, 82, 391
Boyce P.J. et al., 2001, ApJ, 560, L127
Broeils, A.H., 1992, PhD Thesis, Univ Groningen
Canaris J., 1993, in Workshop on New Generation Digital Correlators. Publisher, Tuscon, p.117
Cross N.J.G., et al., 2001, MNRAS, 324, 825
Disney M.J., 1976, Nature, 263, 573
Disney M.J., 1999, in Davies J.I., Impey C., Phillipps S., eds, Low
Surface Brightness Universe, ASP, San Francisco
Disney M.J., Phillipps S., 1987, Nature, 329, 203
Disney M.J., Davies J.I., Phillipps S., 1989, MNRAS, 239, 939
Epstein E.E., 1964a, AJ, 69, 490
Epstein E.E., 1964a, AJ, 69, 512
Freedman W.L. et al., 1994, ApJ, 427, 628
Gooch, R, 1995, in ASP Conf. Ser. 77: ADASS IV, Volume 4
Haynes M.P., Giovanelli R., 1984, 89, 758
Holmberg E., 1958, Medd.Lunds.Astr.Obs., Ser.II, No.136
Impey C.D., Bothun G.D., 1997, ARA&A, 35, 267
Impey C.D., Bothun G.D, Malin D.F., 1988, ApJ, 330, 634
Kauffmann G., Nusser A., Steinmetz M., 1997, MNRAS, 286, 795
Kilborn V.A., 2000, PhD thesis, Univ Melbourne
Kilborn V.A. et al., 2000, AJ, 120, 1342
Kilborn V.A. et al., 2002, AJ, 124, 690
Lo K.Y., Sargent W.L.W., Young K., 1993, AJ, 106, 507
McGaugh S.S., 1996, MNRAS, 280, 337
Minchin R.F., 2001, PhD thesis, Univ. Wales, Cardiff
Phillipps S., Disney M.J., Kibblewhite, E., Cawson M.G.M., 1987,
MNRAS, 229, 505
Rao S., Briggs F.H., 1993, ApJ, 36, 267
Rhee, M.-H., 1996, A&AS, 115, 407
Rohlfs K., 1996, Tools of Radio Astronomy, Springer-Verlag
Rosenberg J.L., Schneider S.E., 2002, ApJ, 567, 247
Rosenberg J.L., Schneider S.E., 2000, ApJS, 130, 177
Ryan-Weber E. et al., 2002, AJ, 124, 1954
Ryder S.D. et al., 2001, ApJ, 555, 232
Sault R.J., Teuben P.J., Wright M.C.H., 1995, ADASS, p.433,
ASP San Francisco
Schneider S.E., Spitzak J.G., Rosenberg J.L., 1998, ApJ, 507, L9
Solanes J.M., Giovanelli R., Haynes M.P., 1996, ApJ, 461, 609
Sorar E., 1994, PhD Thesis, Univ Pittsburgh
Spitzak J.G., Schneider S.E., 1998, ApJS, 119, 159
Staveley-Smith L., Davies R.D., Kinmann T.D., 1992, 258, 334
22
R.H. Lang et al.
Staveley-Smith L. et al., 1996, Proc. Astron. Soc. Australia, 13,
243
Tully R.B., Fouque., 1985, ApJS, 58, 67
de Vaucouleurs G., de Vaucouleurs A., Corwin H.G., Buta R.J.,
Paturel G., Fouque P., 1991, Third Reference Catalogue of
Bright Galaxies, Springer-Verlag, New York
Verheijen M.A.W., Sancisi R., 2001, A&A, 370, 765
Witt A., Thronson H.A., Capuano J.M., 1992, ApJ, 393, 611
Zwaan M.A., Briggs F.H., Sprayberry D., Soror, E., 1997, ApJ,
490, 173
c 1994 RAS, MNRAS 000, 1–??