![]() | Annu. Rev. Astron. Astrophys. 1998. 36:
267-316 Copyright © 1998 by Annual Reviews. All rights reserved |
3.3. Absorption Line Widths
By measuring the line widths we may hope to gain insights into the
temperature and kinematics of
Ly clouds. High resolution
spectra showed that many low column density (NHI <
1015cm-2)
Ly
lines do indeed show
widths (b
(=
2
) ~ 10 - 45
kms-1) that are consistent with photoionization temperatures
(Chaffee et al. 1983;
Carswell et al. 1984;
review by Carswell 1988),
though some lines appear to be as wide as 100 kms-1.
Median Doppler parameters are around
bmed ~ 30-35 kms-1,
with a largely intrinsic scatter about the mean with standard deviation
~ 15 kms-1
(Atwood et al 1985;
Carswell et al. 1991;
Rauch et al. 1992).
The Doppler parameters may decrease with increasing redshift.
Williger et al (1994)
have found an excess of lines with lower Doppler parameters b ~
20kms-1 at z
4.
Occasionally, a correlation between Doppler parameter
and column density has been noted
(Carswell et al. 1984,
Hunstead et al. 1988).
However, the reality of this effect has been subject to a
debate which culminated in the so-called "b-N controversy"
(Hunstead & Pettini
1991;
Webb & Carswell 1991;
Peacock 1991), when
Pettini et al. (1990)
suggested that (when looked at with high enough resolution)
Ly lines had much lower Doppler
parameters (mostly b
22 kms-1)
than previously thought.
There also appeared to be a strong positive correlation between Doppler
parameter b and column density N. These results were not
confirmed by an analysis of another QSO spectrum with an identical
observational setup
(Carswell et al. 1991).
The controversy was resolved when it was realized that the
presence of noise in a spectrum can distort weak line profiles and lead
to underestimates of the average b values of low column density
lines. The problem is exacerbated by a detection bias
against weak broad lines, which are more difficult to find against a
noisy continuum and tend to end up below the detection threshold. The
combination of these effects accounts for both the presence of
spuriously low Doppler parameters and the apparent b - N
correlation seen in these datasets
(Rauch et al 1992,
1993).
RECENT KECK RESULTS Data taken at similar
resolution but with much higher signal to noise ratio with the Keck
telescope's HIRES instrument have basically confirmed the earlier 4m
results.
Hu et al. (1995)
found the Doppler parameter distribution at
z ~ 3 to be well represented by a Gaussian with a mean of 28
kms-1 and width = 10
kms-1, truncated below a cutoff bc = 20
kms-1. With increasing redshift, there seems to be a genuine
trend to lower Doppler parameters. The finding by
Williger et al (1994)
of evolution in b appears confirmed: Median Doppler parameters for
relatively strong lines (13.8 < log N(HI) < 16.0) change from 41
kms-1 (< z > ~ 2.3;
Kim et al. 1997)
to 31 kms-1 (< z > ~ 3.7;
Lu et al 1996),
with lower cutoffs dropping from 24 to 15
kms-1 over the same redshift range. The locus of the
Pettini et al (1990)
narrow lines in the b - N diagram is virtually empty
(Hu et al 1995),
as expected in data with such a high S/N ratio.
Kirkman & Tytler
(1997)
obtain similar results for the Doppler parameters in
their Keck data at even better S/N ratios, but they question the
significance
of the change with redshift, and find a lower, mean b of 23
kms-1 (< z > ~ 2.7) with a lower cutoff
bc=14 kms-1 at
logN(HI) = 12.5. However, at logN(HI) = 13.8 their minimum b at 19
kms-1 is very close to the result of
Kim et al. 1997,
so the analyses
may well be consistent. It is conceivable that the discrepancies at
lower column densities arise once more from the noise bias discussed
above which may affect any dataset as long as there continues to be a
supply of weaker and weaker lines crossing the detection threshold with
increasing S/N ratio. The differences might lie in a different
understanding of what constitutes "statistically acceptable fits" or
"detectable lines". A dataset spanning a large redshift range, with
- most importantly - a homogeneous S/N ratio would be desirable.
THE TEMPERATURE OF THE IGM FROM LINE PROFILES ?
Though narrow lines (b < 15 kms-1)
are apparently very rare
or even absent, this should not be interpreted as indicating a minimum
temperature of the Ly
absorbing gas. The issue is more complex;
in analogy with other astrophysical situations there are reasons for
which a correlation might be expected between the
temperature (or velocity dispersion) and the density (or column
density) of the gas. Typical photoionization equilibrium temperatures
should be in excess of 30000 K (e.g.,
Donahue & Shull 1991),
but temperatures as low as 20000 K can be attained through inverse
Compton cooling and a decrease of the ionizing spectrum at the HeII edge
(Giallongo & Petitjean
1994).
If photo-thermal
equilibrium is abandoned, adiabatic expansion cooling can lower the
temperatures further while maintaining high ionization, as suggested by
Duncan et al (1991).
Currently favored theories of
Ly
clouds that are the result of cold dark matter-based gravitational
collapse do predict a
b - N correlation with temperatures for low column density
clouds even
below 104 K, as a consequence of adiabatic expansion
and inefficient
photoheating at low densities, while the larger column densities are
heated as a result of compression during collapse. However, inspite of
the low temperatures the Doppler parameters of the weak lines are
predicted to be large because of bulk motion: Nature, in a random act
of unkindness, has endowed these cool clouds with a large size so that
the Hubble expansion
dominates the line broadening. Yet, it may be worth trying to track down
the residual influence of the gas temperature on the line profiles.
The lower column density systems are at gas densities where the cooling
time (for processes other than expansion cooling) exceeds a Hubble
time. Therefore, the gas retains a memory of the temperature after
reheating is complete
(Miralda-Escudé &
Rees 1994;
Meiksin 1994;
Hui & Gnedin 1997),
and the process of reheating may have left a record in the
Doppler parameter distribution
(Haehnelt & Steinmetz
1998).