A. Spagna - D. Carollo - M. G. Lattanzi - B. Bucciarelli
INAF - Osservatorio Astronomico di Torino, 10025 Pino Torinese, Italy
Received 13 April 2004 / Accepted 21 July 2004
Abstract
We present an alternative method for the kinematic analysis of
high proper motion surveys and discuss its application to the
survey of Oppenheimer et al. (2001) for the selection of reliable
halo white dwarfs (WDs).
The local WD space density we estimate is
pc-3, which is about an
order of magnitude smaller than the value derived in Oppenheimer
et al. (2001), and is consistent with the values obtained from
recent reanalyses of the same data.
Our result, which corresponds to a fraction of 0.1%
0.2%
of the local dark matter, does not support the scenario suggested
by microlensing experiments that ancient cool WDs could contribute
significantly to the dark halo of the Milky Way.
Key words: stars: kinematics - white dwarfs - dark matter - Galaxy: stellar content - surveys - methods: statistical
These studies reveal a significant contamination of thick disk objects affecting the halo WD sample, and point out the basic problem of defining an accurate procedure to deconvolve the halo and thick disk populations on the basis of their kinematic and photometric properties.
In this paper we describe a general statistical method designed to reject objects with disk kinematics and isolate probable halo members from the screening of kinematically selected samples. We discuss the results obtained with this method when applied to the OHDHS survey, and compare them to the preliminary results derived from the GSC II-based new high proper motion survey in the Northern hemisphere by Carollo et al. (2004).
The OHDHS survey was based on digitized, photographic Schmidt
plates (R59F and BJ passbands) from the SuperCOSMOS Sky Survey
(SSS, Hambly et al. 2001). They analyzed 196 three
epoch plates (IIIaJ, IIIaF and IV-N) covering an area of 4165
square degrees near the South Galactic Pole (SGP). The magnitude
limit of the survey is of R59F = 19.8, while the proper motion
limits are 0.33
yr
yr-1.
They found 98 WDs, whose tangential velocities were derived from
the measured proper motions and photometric distances estimated
via a linear color magnitude (CM) relation, MBJ vs. BJ-R59F, calibrated by means of the WD sample with available
trigonometric parallaxes published by Bergeron et al.
(1997).
The kinematic analysis of this sample was made in the two dimensional
(U, V) plane, after assuming that the third galactic velocity component was zero (W=0).
Thick disk contaminants were rejected with a 2
threshold,
km s-1, which would correspond to a
86% confidence level in the case of a non-kinematically selected
sample. In this way, 38 WDs were considered as halo members, from
which a space density of
pc-3 was computed, assuming
for the
average WD mass.
As mentioned in the previous section, these results were
critically revised by several authors. In particular, an
independent kinematic analysis of the OHDHS sample was performed
by Reid et al. (2001), who noted that the resulting
distribution of the WDs in the (U, V) diagram seems more compatible
with the high velocity tails of the thick disk. They computed
(U, V) components assuming that the unknown radial velocity is
null (Vr = 0) and selected halo WDs with the crude but robust
criterion of accepting objects with retrograde motion only (4
objects). This leads to a more conservative value of the density,
pc-3.
Recently, Salim et al. (2004) reanalyzed the WD
sample of OHDHS on the basis of new spectroscopic and photometric
measurements. Radial velocities of 13 WDs with H
lines,
and standard Johnson-Cousins photometry for half of the sample
were obtained. In addition, distances were redetermined by CCD
photometry and adopting the theoretical color magnitude relation
for hydrogen and helium atmospheres published by Bergeron, Leggett
& Ruiz (2001). Salim et al. (2004)
confirmed the results of OHDHS with the same 95 km s-1(2
)
threshold, but showed that a minimum density,
pc-3 is attained with a higher, more
conservative, threshold of 190 km s-1.
![]() |
Figure 1:
Tangential velocity distributions,
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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As the velocity distribution of the disk(s) and halo population do partially overlap (Fig. 1), it is not possible to infer unequivocally, on the basis of kinematic data alone, the parent population of each object. Nevertheless, it is always possible to test if an object is, or is not, consistent with the velocity distribution of a certain population once a value for the confidence level is chosen.
Here, we retain as halo WDs those objects whose kinematics are
not consistent with the velocity distribution of the thick
disk population given a certain confidence level; this allows
the identification of halo WDs while limiting the contamination by
high velocity thick disk objects.
Unless corrected for the incompleteness due to the fraction of rejected halo WDs
whose kinematics are compatible with that of the thick disk
population, it is clear that this procedure can only provide a
lower limit to the actual density.
An alternative, and potentially more rigorous procedure, is a Maximum-likelihood analysis that fits simultaneously the superposition of two or more populations (see e.g. Nelson et al. 2002; Koopmans & Blandford 2001). In this case however, because of the small size of the samples, further assumptions on the kinematics and the formation process (IMF, age, etc.) of all the populations involved are usually necessary.
In practice, the galactic components need to be derived from the
observed tangential and radial velocity components
:
![]() |
= | ![]() |
|
![]() |
= | ![]() |
If the full 3D space velocity cannot be recovered, as in the case
of proper motion surveys, we can adopt a similar procedure in the
2D tangential velocity plane, (
,
). The
bivariate marginal distribution,
,
can be obtained by properly integrating the distribution in Eq. (1) along the Vr component:
Our analysis will be based on Eq. (3), that represents the appropriate density distribution when radial velocities are missing. Notice that this approach, even in the case of surveys involving widely different line-of-sights, allows the derivation of the exact tangential velocity distribution for each star, without any assumption on the unknown third velocity component Vr.
The probability of selecting a star with absolute magnitude M in
the range
,
(
),
(
)
is then
,
where the
joint probability density is:
![]() |
Figure 2:
Left panel: iso-probability contours (1![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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Figure 3:
Left panel: iso-probability contours (1![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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If we integrate over r the joint probability density function
given in Eq. (4), we obtain the marginal density
distribution
At the same time, we can introduce the (conditional) probability
that an object with tangential velocities
is found at the measured distance,
r:
Both the marginal distribution
and the
conditional probability
can be used
to test the consistency of each object with a parent population.
In principle, the conditional probability
seems more appropriate than
since it fully utilizes the individual
stellar distances. However, the differences become insignificant
when the confidence level is set to sufficiently high values (see
next section).
Note that, formally, Eq. (6) is equivalent to the
original distribution,
,
except that
the probability is null for
,
and it has been re-normalized.
This effect needs to be taken into account when we define a
confidence interval over the
plane in
order to test the consistency with the parent population and to
estimate the contamination due to objects in the tails beyond the
critical limit. In fact, the adoption of the original
to reject the disk stars with
respect to a certain confidence level, e.g.
,
would exclude 99% of all the existing thick disk stars
which, however, corresponds to a smaller fraction of the thick
disk objects that are really present in the kinematically selected
sub-sample. In this case, only the confidence interval defined for
,
or
,
assures that the fraction of false negatives contaminating the
sample of bona fide halo stars does not exceed - on average
- 1% of the observed thick disk objects.
Table 1: Estimation of the halo WD density based on the objects selected from the OHDHS sample.
In the left panels of Figs. 2-3 the concentric ellipses show the iso-probability contours (1Table 2: Estimation of the halo WD density based on the sample revised by Salim et al. (2004).
LHS 1447 is also located outside the 3
contour so that,
according to the complete distribution, it should be rejected as a
thick disk star with a confidence level higher than
.
Actually, that conclusion would be incorrect if
we tested the hypothesis that LHS 1447 is a member of the
kinematically selected sample as shown in the right panels of
Figs. 2-3, where the marginal and
conditional distributions,
and
,
are drawn. In these cases the star
is located within the iso-probability contour delimiting the
99% confidence level so that it must be accepted as a thick disk
star.
The kinematic tests were carried out in the tangential plane of
each individual star so that no assumption on radial velocity is
necessary.
The values of 95% and 99% for the confidence level ()
were
chosen in order to minimize the presence of false negatives.
With a total sample of 98 WDs, presumably a mixture of (thin and thick)
disk and halo WDs, we expect that <1 (99%) and <5 (95%) of
the high velocity thick disk stars would contaminate the selected
Pop. II WD sample.
Finally, the halo WD density was estimated by means of the
classical 1/V
method (Schmidt 1975), and
assuming a value of
for the typical WD mass. The
results, with their (Poissonian only) errors, are reported in
Table 1, where the different values refer to the
two confidence levels and the three probability distributions used
for the calculations.
Although affected by large uncertainties, the values in Table 1 suggest a density of
pc-3, i.e. 0.1-0.2% of the local dark
matter, which is an order of magnitude smaller than that reported
in OHDHS.
Our results are consistent with the local mass density of halo WDs
estimated by Gould et al. (1998), and with various
reanalyses of the OHDHS sample (e.g. Reid et al. 2001; Reylé et al. 2001; Torres et al. 2002; Salim et al. 2004). Furthermore,
Carollo et al. (2004), applying the statistical
methodology described in this paper to a new high proper motion
survey based on GSC-II material, derived a similar value of
pc-3.
Lacking individual trigonometric parallaxes, a critical point of this (and any) analysis is the choice of the method for the estimation of the distances, which directly affects the evaluation of the WD tangential velocities and, of course, of their stellar density. As remarked by several authors (see e.g. Torres et al. 2002; Bergeron 2003), empirical and theoretical CM relations can both give rise to systematic errors.
If for the distances of the OHDHS sample we adopt the values
recently redetermined by Salim et al. (2004), the number of selected halo WDs increases but
the resulting densities, shown in Table 2, are
not significantly different from those reported in Table 1.
Table 3: Same as Table 1 after adopting a thick disk velocity distribution convolved with the observation errors.
Table 4: Same as Table 2 after adopting a thick disk velocity distribution convolved with the observation errors.
In practice, the main effect of the tangential velocity errors,
,
is to
increase the dispersion and the overlap of the "observed''
kinematic distributions belonging to the various stellar
populations. Clearly this also increases the contamination of the
disk WDs and makes the identification of the halo WDs more
difficult.
Although a more rigorous statistical analysis would be necessary
to properly consider the presence of these errors, a conservative
estimation can be given by selecting only those objects that are
not consistent with the "observed'' kinematic distribution that
results from convolving the
projected kinematic distribution of the thick disk
(Eq. (3)) with a bivariate Gaussian error
distribution with null mean and dispersions, (
,
corresponding to the velocity errors
of the i-th object. The velocity errors have been derived by
assuming the proper motion errors,
,
listed in Table 1
of OHDHS, and a more realistic photometric parallax error,
,
of 25% (instead of 20%).
The different halo WD densities estimated from the objects which
are not consistent (at the 95% and 99% confidence level) with
the new distributions are reported in Tables 3 and 4. Because of
the larger velocity thresholds, the number of selected halo WDs is
smaller than those reported in Tables 1 and 2. The estimated WD
densities, uncorrected for the loss of halo WDs with disk
kinematics, decrease proportionally, but are still consistent with
pc-3. Note that the
minimum values, which are reported in Table 4, have been derived
from the data of Salim et al. (2004) who provided
distances (and thus volumes) systematically larger than
Oppenheimer et al. (2001).
![]() |
Figure 4:
Velocity distribution (U,V,W) of the subsample of 15 stars with available radial
velocity (dots with 1![]() ![]() ![]() ![]() |
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Although controversial, some authors claim the presence
of a vertical velocity gradient that supports a thick disk which
rotates faster close to the galactic plane (i.e. where the WD
sample is localized), than at higher distances, where the studies
of the thick disk kinematics have been usually carried out.
In particular, Chiba & Beers (2000), who analyzed
1203 metal poor stars non-kinematically selected, found a rapidly
rotating thick disk close to the galactic plane with a small
asymmetric drift
km s-1 and
with velocity dispersions (
km s-1. Moreover, they
determined a velocity gradient
km s-1 kpc-1, that, however, other studies
(e.g. Soubiran et al. 2003) do not detect.
Nevertheless, a fast rotating thick disk at
was
determined
also by Upgren et al. (1997) from a sample of
K-M dwarfs in the solar neighborhood (
pc) with
trigonometric parallaxes and proper motions
from the Hipparcos catalogue and radial velocity measurements.
Thus, in order to test the sensitivity of our method with respect
to the adopted thick disk model, we repeated the WD selection of
the Salim et al. (2004) sample through the
distributions
and
derived using the velocity ellipsoid
from Chiba & Beers (2000). The new results are
consistent (within 1
)
with the values obtained with the
kinematics from Soubiran et al. (2003), although
the resulting densities appear typically larger than the previous
ones.
For instance, with a 99% confidence level
we find
pc-3 for both
and
when the velocity errors are not
taken into account (cf. Table 2), while the
distributions convolved with the velocity errors provide
pc-3 (cf. Table 4).
The 95% confidence level also provides similar but
systematically higher new densities up to
pc-3 and
pc-3 respectively when the velocity errors are, or
are not, convolved with the tangential velocity distributions.
It appears that, with the adopted confidence levels, significantly
higher density (e.g. close to
pc-3) may be attained only with disk ellipsoids
kinematically much "cooler'' than those expected for a typical
thick disk population.
For instance, a total density
pc-3 is only obtained counting all the 41 WDs
which are not consistent with the thin disk
kinematics (using
with a 95% confidence level), i.e. summing both halo and thick disk WDs.
To this regard, Fig. 4 shows the (U,V,W) velocities derived from
Eq. (2) for the 15 stars with available radial velocities.
Those which have been selected with a 95% confidence level by means of the
distributions
and
convolved
with the velocity errors
(Table 4) are marked with square and diamond
symbols. In addition, the
iso-probability ellipses of
the thick disk and halo velocity distributions, based on the
kinematic parameters respectively from Soubiran et al. (2003) and Casertano et al.
(1990), are also plotted.
The three panels of Fig. 2 indicate that all
the likely halo WDs have been properly identified by our kinematic
analysis based on the 2D
distributions,
thus supporting the reliability of our selection procedure.
To this regard, we have implemented a general method for the kinematic analysis of high proper motion surveys and applied it to the identification of reliable halo stars. The kinematically-selected tangential velocity distributions are derived for each star, so that no assumption on the unknown third velocity component, Vr, nor any approximation on the galactic components (U,V,W), is necessary.
We selected as bona fide halo WDs only those stars whose tangential velocity is
inconsistent, at the 95% and 99% confidence levels, with the
appropriate projected distribution,
or
,
of the observed thick disk
population, thus assuring limited contamination of thick disk
objects.
Finally, the effect of large velocity errors, which derive from
the intrinsic uncertainty of the WD photometric parallaxes, was
also discussed and taken into account.
We applied this methodology to the OHDHS sample and selected 10
probable halo WDs (that became 3 after the inclusion of the
velocity errors) at a 99% confidence level. Through the 1/V
method, we estimated a local WD density of
pc-3 (i.e. 0.1-0.2% of the local dark matter) which is consistent with the
values found by Gould et al. (1998), as well as by other authors
who reanalyzed the OHDHS sample (e.g. Reid et al. 2001; Reylé et al. 2001; Torres et al. 2002; Flynn et al. 2003).
The same methodology applied to the OHDHS sample
revised by Salim et al. (2004) yields a similar
value. These results agree with those found by Carollo et al. (2004) from a first analysis of new data of an
independent high proper motion survey in the Northern hemisphere
based on material and procedures used for the construction of the
GSC-II.
Although affected by a large uncertainty due to the small
statistics and low accuracy of the photometric parallaxes, our
results clearly indicate that ancient cool WDs do not
contribute significantly to the baryonic fraction of the galactic
dark halo, as possibly suggested by the microlensing experiments
which claimed that 20% of the dark matter is formed by
compact objects of
0.5
(Alcock et al. 2000).
Acknowledgements
We wish to acknowledge the useful discussions with R. Drimmel, S. T. Hodgkin, B. McLean, R. Smart, and L. Terranegra. We also thank the anonymous referee for his/her valuable comments.Partial financial support for this research came from the Italian Ministry of Research (MIUR) through the COFIN-2001 program.