E. Janknecht - R. Baade - D. Reimers
Hamburger Sternwarte, Universität Hamburg, Gojenbergsweg 112, 21029 Hamburg, Germany
Received 15 April 2002 / Accepted 6 July 2002
Abstract
Spectroscopy with HST/STIS Echelle and VLT/UVES
of the bright QSO HE 0515-4414 (
)
offers for the first time the opportunity to study the Lyman
forest
in the redshift range
0.9 < z < 1.7 at a resolution
10 kms-1.
The number density evolution of the Lyman
lines is well described
by the power law approach d
.
We derive
for the strong lines
(
),
in agreement with the Lyman
forest evolution for z > 1.7.
The expected slow-down in their evolution does not appear
earlier than
.
For the weak lines
(
)
we find
that the HE 0515-4414 data for z > 1 follow the trend with
known from z > 1.7 observations, i.e. we confirm the difference in evolution
between weak and strong lines.
We use the two-point velocity correlation function (TPCF)
to search for clustering of the Lyman
lines,
yet we detect no excess in the TPCF on scales up to 10000 kms-1.
Key words: cosmology: observations - intergalactic medium - quasars: Ly
forest - quasars: individual: HE0515-4414
The evolution of the Lyman
absorption lines per unit redshift
d
has been a subject of observational studies since many years. At high redshift
(z>1.6) the evolution is steep with dn/d
and
-3 for strong Lyman
lines (i.e.
log
;
Rauch 1998).
Observations of the Lyman
forest at low redshift with HST/FOS,
at first in 3C273 (Bahcall et al. 1991), showed that the number of
Lyman
lines was far in excess of the expected number according
to an extrapolation from high z. As a final result from the HST QSO
absorption line key project Weymann et al. (1998) found
-0.3
for z < 1.5.
They also claimed a break in the evolutionary behaviour from
a steep evolutionary law for z > 1.6 to a flat one for z < 1.5.
The apparently rather abrupt break in the evolutionary law
just at the transition from high-resolution optical data to low-resolution
UV data immediately raised the suspicion that this behaviour might
not be real. Owing to the insufficient FOS resolution
(230-
)
the number counts might be underestimated
due to line blending (Weymann et al. 1998). It is obvious, that this open
question can be addressed only by UV observations of very bright QSOs at
Echelle resolution. A further unsettled question which requires
high-resolution UV spectra is the different evolutionary behaviour of strong
compared to weak Lyman
lines. It has been found from
high-resolution optical spectra for z > 1.6 that apparently weak lines evolve
much slower than strong lines (Kim et al. 1997). Is that also true
for z < 1.5?
In this paper we use the first UV spectra of the bright intermediate redshift QSO HE 0515-4414 (z = 1.73, B = 15.0, Reimers et al. 1998) at STIS/Echelle resolution (10 kms-1) for addressing the above discussed open questions.
HE0515-4414 was observed with STIS between January 31
and February 2, 2000 with the medium-resolution NUV echelle mode (E230M)
and a
aperture. The overall exposure time was 31500 s
resulting in a typical signal-to-noise ratio of 10 depending on the order
and on the position within the orders. The resolution of the spectra is
FWHM
10 kms-1.
The data reduction was performed by the HST pipeline completed by
an additional inter-order background correction and by coadding the separate
subexposures.
The optical spectra were obtained between October 7, 2000 and January 3, 2001
using the UV-Visual Echelle Spectrograph (UVES) at the VLT/Kueyen
telescope. The overall exposure time was 31500 s. The slit width was 0.8
arcsec resulting in a spectral resolution of
FWHM 6 kms-1. After reduction by the UVES pipeline
and conversion to vacuum baryocentric wavelengths, the individual spectra
were coadded and exhibit a S/N
-50 in the investigated
spectral region.
The combined HST and VLT data provide the spectral range
of the Lyman
forest of HE0515-4414 from z=0.87 up to z=1.73,
the quasar's Lyman
emission redshift.
To avoid the proximity effect we exclude a region of about 5000 km s-1from the quasar leading to an investigated spectral range
Å or z = 0.87-1.68.
We normalize the spectrum fitting polynomials to line-free regions and
dividing the flux by this background continuum.
The spectrum of HE0515-4414 is strewn with metal lines and lines of molecular
hydrogen (H2) from its damped Lyman
system which has been
studied in detail by de la Varga et al. (2000). The main difficulty
in the line identification was the extraction of the
Lyman
lines from this real H2
forest dominating the short-wavelength region of the HST spectrum
and thus suggesting to ignore this region in our analysis of the weak Lyman
lines (see below). The molecular hydrogen of the DLA
will be the topic of a forthcoming paper.
In a first approximation, we detected about 400 lines as Lyman
candidates in the whole spectrum. These lines were fitted with the FITLYMAN
code in the MIDAS package (Fontana & Ballester 1995) using Voigt profiles
convolved with the instrumental profile. FITLYMAN adjusts three independent
parameters per line by
minimization.
These parameters are the redshift of an absorption line z,
its H I column density
,
and its Doppler
parameter b,
comprising the thermal and the turbulent broadening of the lines.
The general fitting strategy, especially for blends, was to start with a
single line and to add a further component to the ensemble if the
decreased with this second line.
For each of the Lyman
candidates we calculated the significance level
,
where W denotes the observed equivalent width
of the line and
the
error of W implying both
the fit error and the continuum error.
With the selection criteria
and
kms-1,
we reduced the original sample to 235
Lyman
lines. The full fit parameter list for all recognized hydrogen
absorption lines is available in electronic form at the CDS
via anonymous ftp to cdsarc.u-strasbg.fr (130.79.12.85) via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?/A+A/391/L11.
An important fitting constraint is given for the stronger Lyman
lines for which we tried to detect the higher order lines of the Lyman series
followed by a simultaneous fit, if possible. We compared the H I
parameters inferred from Ly
profile fitting with the parameters
determined with a simultaneous fit with the accompanying Ly
counterparts. Figure 1 shows a rather small systematic effect
in the column densities. We derive
for the mean proportion of the Ly
/Ly
fit column densities
and the column densities based solely on Ly
fitting.
The same holds for b
(
).
This is in contrast to the recently suggested strong dependence of the fit
parameters on the fit strategy (single-component fit versus simultaneous
Ly
-Ly
fit; e.g., Hurwitz et al. 1998; Shull et al. 2000).
Our 15 per cent deviation of the inferred column densities is at variance
with the above cited studies. Obviously, the improved data quality
leads to more consistent fit results. The remaining discrepancy may be
attributed to the unphysical assumption of Voigt profile
fitting. Indeed, the interpretation of the line-broadening velocity
as unresolved stochastic motions is probably an oversimplification
(e.g., Levshakov & Kegel 1997).
![]() |
Figure 1:
Column densities of individually treated Lyman
![]() ![]() ![]() |
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The differential column density distribution function
is defined as the number of Lyman
absorption lines per unit
column density and per unit absorption distance path (Tytler 1987):
![]() |
(1) |
![]() |
Figure 2:
The column density distribution function for the Lyman ![]() ![]() |
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Usually,
is fitted by a power law of the form
.
The distribution function for all 232 lines with
log
is plotted in Fig. 2. The squares show the observed log f values,
while the solid line represents the best fit for all lines with
log
.
We have chosen this lower boundary
because the distribution follows the power law down
to this value. Assuming the general validity of the power law the sample
is obviously not complete below log
.
The best fit yields log
and
.
Considering exclusively the STIS lines in the same column density
range, the result is very similar: log
and
.
In contrast, the slope
of the distribution function for the UVES lines is much flatter
(log
,
).
The distribution of the UVES lines can be approximated very well
with a single power law for an even wider column density range
(
)
due to the better resolution of UVES.
The flatter slope of the higher redshifted UVES lines indicates
that stronger absorbers have evolved away faster than weaker ones.
This will be discussed in more detail in Sect. 4.3.
Our result is in accordance with other analyses in comparable redshift ranges.
For example, Dobrzycki et al. (2002) found
-1.7, deriving the exponent from a curve of growth
analysis. Hu et al. (1995) obtained
for
,
while
Kim et al. (2001) determined
for various column density ranges
to 1.70-1.74.
The evolution of the number density per unit redshift of
Lyman
clouds can be well approximated by the power law
![]() |
(2) |
![]() |
Figure 3:
The number density evolution of the Lyman ![]() ![]() ![]() ![]() |
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![]() |
Figure 4:
Same as in Fig. 3, for
![]() |
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In Figs. 3 and 4 we present the line numbers per unit redshift plotted
over the redshift for the weak and for the strong lines, respectively.
While for the strong lines we could exploit the whole wavelength region,
we omit the spectral range
Å
for the weak lines to avoid misidentification due to the H2 lines,
retaining an effective redshift range
.
The diagrams show the data points and the best fit for which we obtain
for
,
suggesting that there is little
evolution in the weak lines in the redshift interval
1.0 < z < 1.7. Considering a broader redshift range (Fig. 5, upper
part) demonstrates that our STIS data follow the earlier
optical observations (z > 1.6), i.e. the number density evolution is
consistent with
over the whole redshift range
.
It should be noted that
lies
within the 2
confidence band of our data points (see Fig. 3).
The transition to a flat (
)
evolution curve probably
occurs around z = 1.
In contrast, the strong Lyman
lines show a steeper gradient
in the evolution diagram (Fig. 4).
We detect an obvious correlation between the evolution and the line strength,
i.e., the high column density absorbers evolve with
.
This disagrees with the results of Penton et al. (2000)
and Dobrzycki et al. (2002) who found no or only marginal evidence
for a different evolution, respectively.
We cannot recognize a slow-down in the evolution of the stronger absorbers.
Therefore, we conclude that this break does not occur earlier than at
rather than at
-1.7 as previously claimed
(Impey et al. 1996; Weymann et al. 1998; Dobrzycki et al. 2002).
The large spread of our data points result from the poor statistics of
a single line of sight.
For example, omitting the two outliers in the plot for the strong lines
lying beyond the 95% confidence limit our result
(
)
becomes more robust.
The lower panel of Fig. 5 demonstrates the difference
between the Weymann et al. (1998) data points and our values.
Indeed, the former ones do not indicate any change
in the evolution until
,
while the results of HE 0515-4414
suggest a change of the slope at much lower z.
![]() |
Figure 5:
The number density evolution of the Lyman ![]() ![]() ![]() ![]() |
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To study the clustering properties of the Lyman
forest,
we introduce the two-point velocity correlation function
where the number of observed line pairs in a given velocity
separation bin
,
,
is compared with the number of
expected pairs
determined in the same velocity difference bin
in a randomly produced spectrum:
![]() |
(3) |
![]() |
(4) |
![]() |
Figure 6:
Two-point correlation function
![]() ![]() ![]() ![]() |
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We have analyzed the evolution of the Lyman
forest in the
redshift range
0.9 < z < 1.7 using combined high-resolution HST/STIS
and VLT/UVES data. The main results are summarized as follows:
The evolution of strong and weak lines is distinctly different.
The high column density
(
)
absorbers evolve according to
with
for
0.9 < z < 1.7, and the
expected slow-down in the evolution does not appear down to
.
The evolution of the weaker lines over the same redshift range is consistent
with
,
thus we have a continuation of the trend
seen at higher redshifts.
Again, the transition to non-evolution probably occurs around z=1.
More lines of sight are necessary to confirm our results.
We detect no significant clustering of neither the weak nor
the strong Lyman
lines on scales up to 10000 kms-1,
so we are unable to confirm most of the previous studies reporting
a weak clustering signal for
kms-1.
Acknowledgements
This research has been supported by the Verbundforschung of the BMBF/DLR under Grant No. 50 OR 9911 1. We thank the anonymous referee for his very helpful report.