Rotation Curve of the Milky Way out to $\sim$ 200 kpc
The rotation curve (RC) of our Galaxy, the Milky Way, is constructed starting from its very inner regions (few hundred pc) out to a large galactocentric distance of using kinematical data on a variety of tracer objects moving in the gravitational potential of the Galaxy, without assuming any theoretical models of the visible and dark matter components of the Galaxy. We study the effect on the RC due to the uncertainties in the values of the Galactic Constants (GCs) and (these being the sun’s distance from and circular rotation speed around the Galactic center, respectively) and the velocity anisotropy parameter of the halo tracer objects used for deriving the RC at large galactocentric distances. The resulting RC in the disk region is found to depend significantly on the choice of the GCs, while the dominant uncertainty in the RC at large distances beyond the stellar disk comes from the uncertainty in the value of . In general we find that the mean RC steadily declines at distances beyond , independently of the value of . Also, at a given radius, the circular speed is lower for larger values of (i.e., for more radially biased velocity anisotropy). Considering that the largest possible value of is unity, which corresponds to stellar orbits being purely radial, our results for the case of give a lower limit to the total mass of the Galaxy within , , independently of any model of the dark matter halo of the Galaxy.
Subject headings:Galaxy: rotation curve – Galaxy: dark matter – Galaxy: mass
The circular velocity, , of a test particle at a radial distance from the center of a mass distribution gives a direct measure of the total gravitational mass, , contained within that radius. A measured profile of as a function of for a spiral galaxy — often simply called its Rotation Curve (RC) — is therefore a direct probe of the spatial distribution of the total gravitating mass inside the galaxy including its dark matter (DM) content; see, e.g., Sofue & Rubin (2001), Trimble (1987) for reviews. Recent comprehensive discussions of the RC and mass models for our Galaxy, the Milky way, can be found, e.g., in Weber & de Boer (2010); Sofue (2012); Nesti & Salucci (2013).
Recently, it has been shown that the RC of the Milky Way can be directly used to derive not only the local density of DM, but also the velocity distribution of the DM particles in the Galaxy (Bhattacharjee et al., 2013), which are crucial for analyzing the results of both direct as well as indirect DM search experiments (Jungman et al., 1996); see also Cowsik et al. (2007); Chaudhury et al. (2010); Kundu & Bhattacharjee (2012); Burch & Cowsik (2013). For this purpose, it is essential to derive the RC of the Galaxy to as large a galactocentric distance as possible without referring to any specific model of the DM halo of the Galaxy. In this paper we derive the RC of the Galaxy spanning a large range of galactocentric distances starting from its inner regions () out to using kinematical data on a variety of tracer objects moving in the gravitational potential of the Galaxy, without assuming any model of the DM halo of the Galaxy.
The circular velocity of a test particle in the Galaxy is, of course, not a directly measured quantity. The RC of the Galaxy has to be derived from the kinematical as well as positional data for an appropriate set of tracer objects moving in the gravitational field of the Galaxy. Except in few cases, the full 3-D velocity information of the tracers is not available, and the RC has to be reconstructed from only the measured line-of-sight (los) velocity and positional information of various tracer objects in the Galaxy.
For deriving the RC in the disk region of the Galaxy, one usually makes the reasonable assumption that the disk tracer objects move in circular orbits around the Galactic center. From the observed heliocentric los velocities, , of the tracers and their position coordinates in the Galaxy, and with an assumed set of values of the Galactic Constants (GCs), , where and are the sun’s distance from and circular rotation speed around the Galactic center, respectively, that define the Local Standard of Rest (LSR) frame, and applying corrections for the peculiar motion of the sun with respect to the LSR, one can obtain the circular velocities around the Galactic center, , in a fairly straightforward manner (Binney & Merrifield, 1998). Observations on a variety of tracers such as HI regions, CO emission associated with HII regions, compact objects like Carbon stars (C stars), Cepheids, planetary nebulae (PNe), masers, and so on, have been used to derive the RC of the Galaxy in the disk region. Some recent compilations of RC data for the disk region of the Galaxy can be found, e.g., in Sofue et al. (2009) and Burch & Cowsik (2013).
To derive the RC in the outer regions of the Galaxy beyond the Galactic disk, one has to rely on distant tracers like Blue Horizontal Branch (BHB) stars, K Giant (KG) stars and relatively rare tracer objects like Globular Clusters (GCl), dwarf spheroidal (dSph) galaxies and so forth which populate the Milky Way’s extended DM halo out to galactocentric distances of several hundreds of kpc. Unlike the disk tracers, these non-disk tracers do not exhibit any systematic motion, and move about in the Galaxy along various different orbits. The standard approach then is to assume that the tracer population under consideration is isotropically distributed in the halo of the Galaxy and then use the Jeans equation (Binney & Tremaine, 2008) for spherical systems relating the circular velocity at radius to the number density and galactocentric radial as well as transverse velocity dispersions of the tracers at that radius. Of course, in absence of full 3-D velocity information, with only the observed radial velocity dispersion available, the RC constructed using Jeans equation depends on the unknown velocity anisotropy parameter ( and being the radial and transverse velocity dispersions of the tracers, respectively; see section 3 below).
The Jeans equation approach has been used in several recent studies to extend the RC of the Galaxy to distances beyond the extent of the Galaxy’s stellar disk. Accurate measurements of los velocities of a sample of 2401 BHB stars drawn from SDSS DR6 (Adelman-McCarthy et al., 2008) were used by Xue et al. (2008) to derive the RC of the Galaxy to for two constant (-independent) values of , namely (isotropic velocity distribution) and , the latter derived from results of numerical simulations. More recently, the Jeans equation has also been employed, together with certain analytical models of the phase-space distribution function of the tracer population, to construct the RC of the Galaxy to various distances of 25 to 80 kpc (Gnedin et al., 2010; Deason et al., 2012a; Kafle et al., 2012).
A crucial ingredient in the derivation of the distant RC using Jeans equation is the measured radial velocity dispersion of the tracers as a function of their galactocentric distance . An important finding in this regard is the result, first shown by Battaglia et al. (2005, 2006), that the radial velocity dispersion remains almost constant at a value of out to and then steadily declines down to a value of at . In their work Battaglia et al. (2005, 2006) used a heterogeneous sample of about 240 halo objects consisting of field blue horizontal branch stars, red giant stars, globular clusters and distant satellite galaxies. Similar trend of the radial velocity dispersion profile has been found in several subsequent studies using different samples of tracers, e.g., by Xue et al. (2008); Brown et al. (2010); Gnedin et al. (2010); Deason et al. (2012a, b), and most recently in large cosmological simulations by Rashkov et al. (2013).
In this paper we consider a combination of currently available largest samples of a variety of both disk and non-disk tracers to construct the RC of the Galaxy from to . We perform detailed analysis of the dependence of the RC on the choice of the GCs and also the dependence on the anisotropy parameter of the non-disk tracers. We find that, while the RC in the disk region is significantly influenced by the choice of the GCs, the dominant uncertainty in the RC at large distances beyond the stellar disk comes from the uncertainty in the value of . Since currently not much reliable observational information on is available, in this paper we calculate the circular velocities using Jeans equation with the velocity anisotropy of the tracers taken as (a) a radially constant free parameter varying over a possible range of values from (corresponding to complete isotropy of the tracers’ orbits) to (corresponding to completely radial orbits of the tracers), (b) a radially varying of the Osipkov-Merritt (OM) form (see Binney & Tremaine, 2008, p.297-298) given by , with the “anisotropy radius”, and (c) a radial profile of obtained from a recent large high resolution hydrodynamical simulations of formation of late-type spirals like our Galaxy (Rashkov et al., 2013).
We find that, irrespective of the value of , the mean RC steadily declines with beyond . The circular speed at a given radius decreases as is increased (i.e., as the tracers’ orbits are made more radially biased). Thus, the lowest value of the rotation speed at any obtains for the case of complete radial anisotropy () of the non-disk tracers. This fact allows us to set a lower limit on the total mass of the Galaxy, , within a radius , giving . In this context, it may be noted that the recent numerical simulation study of Rashkov et al. (2013) indicates an increasingly radially biased velocity ellipsoid of the Galaxy’s stellar population at large distances, with stellar orbits tending to be purely radial () beyond . If this behavior of is confirmed by future observational data, then the above lower limit on the Galaxy’s mass (obtained from our results with ) may in fact be a good estimate of the actual mass of the Galaxy out to .
The rest of this paper is arranged as follows. In Section 2 we derive the RC on the disk of the Galaxy up to a distance of from the Galactic center. We specify the various tracer samples used in our derivation of the RC and study the dependence of the RC on the chosen set of values of the GCs, . In Section 3 we extend the RC to larger distances (up to ) by an extensive analysis of various non-disk tracer samples discussed there in details. Finally, in Section 4, we present our unified RC and our estimates of the total mass of the Galaxy within and conclude by summarizing our main results in Section 5.
2. Rotation curve from disk tracers
Let us consider a tracer object with Galactic coordinates () at a heliocentric distance and observed heliocentric los velocity (see Figure 1).
We shall assume that the tracer follows a nearly circular orbit about the Galactic center. The velocity of the tracer as would be measured by an observer stationary with respect to the LSR, , can be obtained from the measured through the relation
where denote the peculiar motion of the sun with respect to LSR; see Figure 1. In our calculations below we shall take () (Schönrich et al., 2010). Simple algebraic steps then allow us to relate the desired circular velocity with respect to Galactic center rest frame, , to as (Binney & Merrifield, 1998)
where, is the projection of the galactocentric distance onto the equatorial plane,
For a given set of GCs, , the Cartesian coordinates of the tracer are given by
with Galactic center at the origin and sun lying on the Galactic mid-plane () with coordinates as illustrated in the left panel of Figure 1. Hence, for known () one can solve for from Equation (2) for a given set of GCs.
Tangent Point Method (TPM) : For , one can calculate by the simple tangent point method (Binney & Merrifield, 1998) as follows: Along a given los, the maximum los velocity will occur for the tracer closest to the Galactic center, with the los tangent to the circular orbit of the tracer at that point (see right panel of Figure 1). This maximum los velocity, called the terminal velocity (), is easily seen to be related to through the relation
is the distance of the tangent point from the Galactic center, and is the corrected for the sun’s peculiar motion as in Equation (1).
For non zero galactic latitude (), Equation (5) generalizes to:
and in this case the Cartesian coordinates of the tracer are given by
Hence the circular velocity can be calculated directly from the measured terminal velocity by using Equation (7).
The details of the disk tracer samples used in this paper along with references to the corresponding data sources for each tracer genre are given in the Appendix (Table 3). The cuts on and are adopted from the published source papers. Towards the Galactic center () or anti-center (), we expect to approach zero to prevent unphysical values there [see Equation (2)]. However, observations in practice have finite values due to contamination from non circular motions dominant there. Therefore, additional restrictions have been applied on ranges so as to ensure that we avoid observations too close to Galactic center (anti-center) regions. We further impose a cut to keep only the tracers whose and so as to ensure that the selected tracers ‘belong’ to the stellar disk of the Galaxy. The – and – scatter plots for the selected disk tracers listed in Table 3 are shown in the Appendix (Figures 10 and 11, respectively).
It is clear from Equations (2) – (8) that the RC depends on the set of values of the GCs () adopted in the calculation. Values of in the range and in the range exist in literature (see, e.g., Reid, 1993; Olling & Merrifield, 1998; Ghez et al., 2008; Reid et al., 2009; McMillan & Binney, 2010; Sofue et al., 2011; Brunthaler et al., 2011; Schönrich, 2012). Actually, the ratio , and being the Oort constants (see, e.g., Binney & Merrifield, 1998), is considerably better constrained. Maser observations and measurements of stellar orbits around SgrA* near the Galactic center report values of in the range from about 29 to 32 (Reid & Brunthaler, 2004; Reid et al., 2009; McMillan & Binney, 2010). RCs have been traditionally presented with the IAU recommended set of values, , for which, however, the ratio is outside the range of values of this ratio mentioned above. A recently suggested set of values of , consistent with observations of masers and stellar orbits around SgrA* mentioned above, is (see, e.g., Bovy et al., 2009; Gillessen et al., 2009).
In general, as easily seen from Equation (2), given a RC, , for a certain set of values of , one can obtain the new RC, , for another set of values of the GCs denoted by through the relation
In order to illustrate the dependence of the RC on the choice of the GCs, in this paper we shall calculate RCs with three different sets of values of , namely the set [8.3, 244] mentioned above as well as two other sets, the IAU recommended set [8.5, 220] and the set [8.0, 200] (Sofue, 2012).
Figure 2 shows our calculated RCs for the disk region of the Galaxy. The left panel of Figure 2 shows the RCs for each of the different tracer samples listed in Table 3 for the GCs set , and the right panel shows the RCs obtained by taking the weighted averages of the combined data from all the samples shown in the left panel, for three different sets of values of the GCs as indicated.
The circular velocities and their errors for
individual disk tracer samples displayed in the
left panel of Figure 2 are
obtained in the following way: For each tracer object in a given sample
we calculate and for the object from the known position
coordinates of the object and its measured los velocity as
described above. We then bin the resulting data ( vs. ) in ,
and in each bin calculate the mean of all the values of all
the objects contained within that bin and assign it to the mean
value of the objects in that bin. The error bars on
correspond simply to the standard deviation (s.d.) of the values
in that bin
with , where and are the value and its error, respectively, of the -th data point within the bin.
As seen from Figure 2, the RC in the disk region depends significantly on the choice of GCs. As expected, at any given the circular velocity is higher for higher value of .
3. Rotation curve from non-disk tracers
In order to extend the RC beyond the Galactic disk we next consider tracer objects populating the stellar halo of the Galaxy. Unlike the nearly circularly rotating disk tracers the non-disk tracers do not exhibit any systematic circular motion. Hence the formalism described in the previous section cannot be used to derive the RC at large galactocentric distances beyond the Galactic disk. Instead, we use the Jeans equation (see, e.g., Binney & Tremaine, 2008, p.349) for spherical systems relating the number density and radial as well as transverse velocity dispersions of the tracers at radius to the circular velocity at that radius:
Here is the galactocentric radial distance of a tracer (see Figure 1), and , and are, respectively, the number density of the tracer population, their galactocentric radial velocity dispersion, and the velocity anisotropy parameter, at . The velocity anisotropy is defined as
where is the galactocentric transverse velocity dispersion of the tracers.
In this work we have chosen two independent classes of non-disk stellar tracers, namely, a sample of 4985 Blue Horizontal Branch (BHB) stars from SDSS-DR8 compiled by Xue et al. (2011) and a set of 4781 K Giant (KG) stars from SDSS-DR9 (Xue et al., 2012). These two samples allow us to probe the Galactic halo up to a galactocentric distance of . In order to reach out further we consider an additional heterogeneous (Hg) sample of 430 objects comprising of 143 Globular Clusters (GCl) (Harris, 2010,1996), 118 red halo giants (RHG) (Carney et al., 2003,2008), 108 field blue horizontal branch (FHB) stars (Clewley et al., 2004), 38 RR-Lyrae stars (RRL) (Kinman et al., 2012), and 23 dwarf spheroidals (dSph) (McConnachie, 2012). To ensure that the sample comprises of only halo objects, we apply a cut on the and coordinates of the tracers, leaving out objects with in all the non-disk tracer samples mentioned above. After these cuts, we are left with a “BHB” sample of 1457 blue horizontal branch stars, a “KG” sample of 2227 K-giant stars and a “Hg” sample of 65 objects comprising of 16 GCls, 28 FHB stars and 21 dSphs, with which we shall construct our RC for the non-disk region. The last sample allows us to extend the RC to a galactocentric distance of 190 kpc, the mean of the objects in the furthest radial bin in the Hg sample. The spatial distributions of the three final non-disk tracer samples (after position cuts mentioned above) in terms of -, - and - scatter plots are shown in the Appendix (Figure 12).
The number density of the tracers, , appearing in the Jeans equation (11) is estimated in the following way. We radially bin the objects in a given sample and estimate the tracer density from the star counts in the annular volume of each bin and assign it at the mean radius of the objects contained within that bin. In order to ensure a reasonably good number of objects per bin we adopt a variable bin size increasing with distance. For the BHB sample, a uniform bin size of 2 kpc is used over its entire range of from 25 to 55 kpc. For the KG samples, the bin widths are 2 kpc for and 4 kpc for ; objects with (up to 110 kpc) are all placed in one single bin. For the Hg sample, because of the relatively small total number (65) of objects, we adopt the following optimal, “object wise” binning in increasing order of the galactocentric distance of the objects: the first 6 radial bins contain 8 objects in each bin; the next 2 bins contain 6 objects in each bin; and, finally, the remaining 5 objects are placed in one single bin. Uncertainties in the number density estimates are obtained from Poissonian errors on the tracer counts in each bin.
The resulting density estimates for the three samples mentioned above with the GCs set are shown in Figure 3, where we also show for comparison (see the top left panel of Figure 3) the tracer densities from some earlier studies that used different tracer samples. Our results are seen to be in reasonably good agreement with those obtained in the previous studies.
We then perform power-law fits () to the radial profile of the tracer number density for each of the three samples separately. The resulting best power-law fits are also shown in Figure 3. The values of the parameters of the best power-law fit for each tracer sample are given in Table 1. Within each sample, there is no significant difference in the values of for the three different sets of GCs, as also seen from the values of the power-law fit parameters given in Table 1.
Next, we have to calculate the galactocentric radial velocity dispersion, , that appears in the Jeans equation (11), for our non-disk samples. To do this we first transform the observed heliocentric los velocity, , of each individual tracer object to , the velocity that would be measured in the Galactic Standard of Rest (GSR) frame. This is easily done by correcting for the circular motion of the LSR and solar peculiar motion with respect to LSR, (see Figure 1):
For large samples like the BHB and KG stars described above, we calculate the for all the individual tracers in the same radial bins as used in the estimation of the tracers’ number density described above, calculate their dispersion, , and assign it to the mean radius of all the tracers contained within that bin. The corresponding uncertainty, , in our estimate of in each bin is calculated by using the standard formula (Lehmann & Castella, 1998; Evans et al., 1993; Graham et al., 1994), where is the number of objects in the bin.
For the Hg sample, however, owing to its small size, we follow a different method, similar to that used in Battaglia et al. (2005, 2006), for calculating the and its uncertainty in each radial bin: we randomly generate a sample of 10,000 mock values of for each tracer object in a radial bin using a Gaussian centered at the observed value of and a width of typically of this value. We then transform these 10,000 values for each tracer in the bin to get the corresponding 10,000 values of using equation (13), and calculate the associated dispersions in that bin. We assign the mean value of the values for all the objects in a given bin to the mean radius of all the objects in the bin. The corresponding uncertainty in is taken to be the r.m.s. deviation of the values in that bin.
Our results for for the three tracer samples are shown in Figure 4 in which we also show for comparison (see the top left panel of Figure 4) the values obtained in some earlier studies using different samples, which, again, are seen to be in reasonably good agreement with our results.
The other three panels of Figure 4 show the best power-law fits () to the radial profiles of for each of the three non-disk samples. The values of the parameters of the best power-law fits for the three tracer samples are given in Table 1. Again, as in the case of , the effect of variation of the Galactic Constants on is negligible.
Finally, the galactocentric radial velocity dispersion, , can be obtained from by using the relation (Battaglia et al., 2005, 2006)
and is the velocity anisotropy of the tracers defined in
equation (12). Equation
is derived by decomposing the ’s into their galactocentric
radial and transverse components and taking the averages of the squares
of the velocity components.
The last quantity that remains to be specified before we can solve the Jeans equation (11) is the velocity anisotropy parameter, , of the tracers. There is not much definite observational information available on the value of of the tracers because of the lack of availability of proper motion measurements on sufficiently large number of tracer objects. In general can be a function of . A recent maximum likelihood analysis (Deason et al., 2012a) of radial velocity data of a large sample of halo stars, performed within the context of a model for the (in general anisotropic) velocity distribution function of the halo stars, indicates the stellar velocity anisotropy being radially biased with a value of for from 16 kpc up to . This is also indicated by the recent results from the large numerical simulation study of Rashkov et al. (2013), which finds the velocity distribution of the Galaxy’s stellar population at large to be radially biased () with stellar orbits tending to purely radial () at . Based on these considerations, to explore various possibilities for , in this paper we shall calculate our RCs for (a) three representative constant values of , namely, (isotropic), 0.5 (mildly radially biased anisotropy), and 1 (fully radially anisotropic), (b) a radially varying of the OM form (see Binney & Tremaine, 2008, p.297-298) given by , being the “anisotropy radius”, and (c) a radial profile of obtained from the recent large high resolution hydrodynamical simulations done by Rashkov et al. (2013). In principle, and its radial profile may be different for different tracer samples. But since currently no reliable measurements of for the different samples extending to large galactocentric distances are available, any choice of different for different samples would be necessarily arbitrary. For simplicity, therefore, we assume the same values of and its radial profile for our three tracer samples.
|Number densities and radial velocity dispersions|
|of non-disk tracers|
With , and thus specified, we can now proceed to solve the Jeans equation (11) to obtain the profiles for the three different tracer samples described above. For each tracer sample we calculate the ’s in the same radial bins as used in calculating the ’s and ’s, and the best-fit power-law forms of and described above are used for calculating the radial derivatives appearing in the Jeans equation (11). The corresponding error, , on within each radial bin is calculated from those of and in the bin by standard quadrature.
The resulting RCs for the three tracer samples are shown in Figure 5. As clear from the left panels of Figure 5 the RCs for different choices of GCs almost overlap, thus indicating that the RC at large galactocentric distances beyond a few tens of kpc is fairly insensitive to the precise values of the GCs. Instead, the main uncertainty in the RC comes from the unknown value of the tracers’ velocity anisotropy parameter , as evident from the right panels of Figure 5. As expected, the lowest rotation speeds obtain for the most radially biased velocity anisotropy ().
4. Combined rotation curves to
For the disk region () we take the averaged data for a chosen set of GCs from the right panel of Figure 2. For the non-disk region (), we combine the data from Figure 5 for the three tracer samples in every 2 kpc radial bins and calculate the resulting mean circular speed () and its uncertainty () within a bin by weighted averaging as described in section 2 [see equation (10)].
The resulting rotation curves for and three sets of values of the GCs are shown in Figure 6, and those for different values of , for one particular set of GCs, , are shown in Figure 7. For comparison, we also show in Figure 7 estimates of circular velocities at specific values of obtained from a variety of independent considerations in some earlier studies by various authors.
The dependence of the radial profile of the cumulative mass, , is shown in Figure 8. Again, estimates of from various independent considerations and given at certain specific values of in some earlier works, are also shown in Figure 8 for comparison.
Note that the lowest mass of the Galaxy corresponds to , which allows us to set a lower limit on the mass of the Galaxy, .
In Figure 9 we show the full rotation curve of the Galaxy out to for and for a radial profile of the non-disk tracers’ velocity anisotropy parameter of the OM form, , for two different values of 15 kpc and 70 kpc. In addition, we show the RC generated with a profile extracted from Figure 2 of Rashkov et al. (2013) with the corresponding numerical data in tabular form given in Table 2. The inset in the left panel of Figure 9 shows the OM profile for various values of as well as the profile obtained in Rashkov et al. (2013). The latter is seen to roughly follow the OM form and is reasonably well bracketed within OM profiles with and . In Figure 9 we also show the circular velocity data from terminal velocities and rotation curve fits for the Burkert and NFW models of the DM halo of the Galaxy given in Nesti & Salucci (2013) (up to ) in comparison with our RC generated with the profile of Rashkov et al. (2013).
As already mentioned, a noticeable feature of the rotation curve, irrespective of the velocity anisotropy of the tracer objects, is its clearly declining nature beyond about 60 kpc, as would be expected of an effectively finite size of the dark matter halo of the Galaxy.
We emphasize that, for any given , the rotation curve and mass profile of the Galaxy shown in Figures 7 and 8, respectively, are based entirely on observational data, and are obtained without making any models of the mass distributions of the various components (the bulge, disk and dark matter halo) of the Galaxy.
In this paper, we have constructed the rotation curve (RC) of the Galaxy from a galactocentric distance of out to by using kinematical data on a variety of both disk and non-disk objects that trace the gravitational potential of the Galaxy, without assuming any theoretical models of the visible and dark matter components of the Galaxy. We have studied the dependence of the RC on the choice of the Galactic constants (GCs) and also studied the dependence on the velocity anisotropy parameter of the non-disk tracers. The RC in the disk region is found to depend significantly on the choice of values of the GCs. The rotation curve at large distances beyond the stellar disk, however, depends more significantly on the parameter than on the values of the GCs. In general, the mean RC is found to steadily decline beyond , irrespective of the value of . At any given galactocentric distance , the circular speed is lower for larger values of . Considering that the largest allowed value of is unity (complete radial anisotropy), this allows us to set a model-independent lower limit on the total mass of the Galaxy, giving . We have also noted that recent results from high resolution hydrodynamical simulations of formation of galaxies like Milky Way (Rashkov et al., 2013) indicate an increasingly radially biased velocity ellipsoid of the Galaxy’s stellar population at large distances, with stellar orbits tending to be almost purely radial () beyond . This implies that the above lower limit on the Galaxy’s mass (obtained from our results with ) may in fact be a good estimate of the actual mass of the Galaxy out to .
In this Appendix, we collect together some details of the disk- and non-disk tracers used in this paper for calculating the rotation curves.
|Tracer Type||Data Source||Ranges|
|Burton & Gordon (1978)|
|(CO-B78)||Burton & Gordon (1978)|
|(HI-F89)||Fich et al. (1989)||and|
|(HII-F89)||Fich et al. (1989)||and|
HII regions &
|(HII-RN-B93)||Brand & Blitz (1993)||and|
|(Cepheid-P94)||Pont et al. (1994)||and ;|
|(PNe-M05-M84-D98)||Maciel & Lago (2005);|
|Durand et al. (1998)||;|
Open star clusters
|(OSC-F08-D02)||Frinchaboy & Majewski (2008);|
|Dias et al. (2002)||and ;|
|(HII-H09)||Hou et al. (2009)||and|
|(HII-U11)||Urquhart et al. (2011)||and|
|(C stars-D07-B12)||Demers & Battinelli (2007); Battinelli et al. (2012)||;|
- affiliation: McDonnell Center for the Space Sciences & Department of Physics, Washington University in St. Louis, Campus Box 1105, One Brookings Drive, St. Louis, MO 63130. USA.
- affiliation: AstroParticle Physics & Cosmology Division and Centre for AstroParticle Physics, Saha Institute of Nuclear Physics, 1/AF Bidhannagar, Kolkata 700064. India.
- affiliation: E-mail: email@example.com
- affiliation: AstroParticle Physics & Cosmology Division and Centre for AstroParticle Physics, Saha Institute of Nuclear Physics, 1/AF Bidhannagar, Kolkata 700064. India.
- affiliation: E-mail: firstname.lastname@example.org
- affiliation: AstroParticle Physics & Cosmology Division and Centre for AstroParticle Physics, Saha Institute of Nuclear Physics, 1/AF Bidhannagar, Kolkata 700064. India.
- affiliation: E-mail: email@example.com
- Note that the los velocities of individual tracer objects are measured fairly accurately and their measurement errors contribute negligibly little to the final errors on the values.
- Note that equation (3) given in the 2005 paper of Battaglia et al. (2005, 2006) is incorrect. The correct equation, same as equation (14) above, is given in the 2006 (Erratum) paper of Battaglia et al. (2005, 2006) and also in Dehnen et al. (2006).
- Adelman-McCarthy, J. K., Agüeros, M. A., Allam, S. S., et al. 2008, ApJS, 175, 297
- Battaglia, G., Helmi, A., Morrison, H., et al. 2005, MNRAS, 364, 433; 2006, MNRAS, 370, 1055 (Erratum)
- Battinelli, P., Demers, S., Rossi, C., & Gigoyan, K. S. 2013, Ap, 56, 68
- Bevington, P.R., & Robinson, D.K. 2003, Data reduction and error analysis for the physical sciences, 3rd Ed. (New York, NY: McGraw-Hill)
- Bhattacharjee, P., Chaudhury, S., Kundu, S., & Majumdar, S. 2013, PhRvD, 87, 083525
- Binney, J., & Merrifield, M. 1998, Galactic Astronomy (Princeton, NJ: Princeton Univ. Press)
- Binney, J., & Tremaine, S. 2008, Galactic Dynamics (2nd Ed.) (Princeton, NJ: Princeton Univ. Press)
- Bond, N. A., Ivezic, Z., Sesar, B., et al. 2010, ApJ, 716, 1
- Bovy, J., Hogg, D. W., & Hans-Walter, R. 2009, ApJ, 704, 1704
- Brand, J., & Blitz, L. 1993, A&A, 275, 67
- Brown, W. R., Geller, M. J., Kenyon, S. J., & Diaferio, A. 2010, AJ, 139, 59
- Brunthaler, A., Reid, M. J., Menten, K. M., et al. 2011, AN, 332, 461
- Burch, B., & Cowsik, R. 2013, ApJ, 779, 35
- Burton, W. B., & Gordon, M. A. 1978, A&A, 63, 7
- Carney, B. W., Latham, D. W., Stefanik, R. P., Laird, J. B., & Morse, J. A. 2003, AJ, 125, 293; Carney, B. W., Latham, D. W., Stefanik, R. P., & Laird, J. B. 2008, AJ, 135, 196
- Catena, R., & Ullio, P. 2010, JCAP, 08, 004
- Chaudhury, S., Bhattacharjee, P., & Cowsik, R. 2010, JCAP, 09, 020
- Clemens, D. P. 1985, ApJ, 295, 422
- Clewley, L., Warren, S. J., Hewett, P. C., Norris, J. E., & Evans, N. W. 2004, MNRAS, 352, 285
- Cowsik, R., Ratnam, C., Bhattacharjee, P., & Majumdar, S. 2007, NewA, 12, 507
- Deason, A. J., Belokurov, V., Evans, N. W., & An, J. 2012, MNRAS, 424, L44 [D12a]
- Deason, A. J., Belokurov, V., Evans, N. W., et al. 2012, MNRAS, 425, 2840 [D12b]
- Dehnen, W., & Binney, J. 1998, MNRAS 294, 429
- Dehnen, W., McLaughlin, D. E., & Sachania, J. 2006, MNRAS 369, 1688
- Demers, S., & Battinelli, P. 2007, A&A, 473, 143
- Dias, W. S., Alessi, B. S., Moitinho, A., & Lépine, J. R. D. 2002, A&A, 389, 871
- Durand, S., Acker, A., & Zijlstra, A. 1998, A&AS, 132, 13
- Evans, M., Hastings, N., & Peacock, B. 1993, Statistical distributions (Wiley, New York)
- Fich, M., Blitz, L., & Stark, A. A. 1989, ApJ, 342, 272
- Frinchaboy, P. M., & Majewski, S. R. 2008, AJ, 136, 118
- Ghez, A. M., Salim, S., Weinberg, N. N., et al. 2008, ApJ, 689, 1044
- Gillessen, S., Eisenhauer, F., Trippe, S., et al. 2009, ApJ, 692, 1075
- Gnedin, O. Y., Brown, W. R., Geller, M. J., & Kenyon, S. J. 2010, ApJ, 720, L108
- Graham, R. L., Knuth, D. E., & Patashnik, O. 1994, Concrete mathematics: A foundation for computer science (Addison-Wesley, Reading)
- Harris, W. E. 2010, arXiv:1012.3224; 1996, AJ, 112, 1487
- Honma, M., Bushimata, T., Choi, Y. K., et al. 2007, PASJ, 59, 839.
- Hou, L. G., Han, J. L., & Shi, W. B. 2009, A&A, 499, 473
- Jungman, G., Kamionkowski, M., & Griest, K. 1996, PhR, 267, 195
- Kafle, P. R., Sharma, S., Lewis, G. F., & Bland-Hawthorn, J. 2012, ApJ, 761, 98
- Kinman, T. D., Cacciari, C., Bragaglia, A., Smart, R., & Spagna, A. 2012, MNRAS, 422, 2116
- Kundu, S., & Bhattacharjee, P. 2012, PhRvD, 85, 123533
- Lehmann, E. L., & Casella, G. 1998, Theory of point estimation (Springer-Verlag, New York)
- Maciel, W. J. 1984, A&AS, 55, 253
- Maciel, W. J., & Lago, L. G. 2005, RMxAA, 41, 383
- McConnachie, A. W. 2012, AJ, 144, 4
- McMillan, P. J. 2011, MNRAS, 414, 2446
- McMillan, P. J., & Binney, J. 2010, MNRAS, 402, 934
- Nesti, F., & Salucci, P. 2013, JCAP, 1307, 016
- Olling, R. P., & Merrifield, M. R. 1998, MNRAS, 297, 943
- Pont, F., Mayor, M., & Burki, G. 1994, A&A, 285, 415
- Rashkov, V., Pillepich, A., Deason, A. J., et al. 2013, ApJ, 773, 32
- Reid, M. J. 1993, ARA&A, 31, 345
- Reid, M. J., Menten, K. M., Zheng, X. W., et al. 2009, ApJ, 700, 137
- Reid, M. J., & Brunthaler, A. 2004, ApJ, 616, 872
- Samurović, S., & Lalović, A. 2011, A&A, 531, A82
- Schönrich, R. 2012, MNRAS, 427, 274
- Schönrich, R., Binney, J., & Dehnen, W. 2010, MNRAS, 403, 1829
- Smith, M. C., Evans, N. W., Belokurov, V., et al. 2009, MNRAS, 399, 1223
- Sofue, Y., & Rubin, V. 2001, ARA&A, 39, 137
- Sofue, Y., Honma, M., & Omodaka, T. 2009, PASJ, 61, 227
- Sofue, Y., Nagayama, T., Matsui, M., & Nakagawa, A. 2011, PASJ, 63, 867
- Sofue, Y. 2012, PASJ, 64, 75
- Trimble, V. 1987, ARA&A, 25, 425
- Urquhart, J. S., Hoare, M. G., Lumsden, S. L., et al. 2012, MNRAS, 420, 1656
- Watkins, L. L., Evans, N. W., & An, J. H. 2010, MNRAS, 406, 264
- Weber, M., & de Boer, W. 2010, A&A, 509, A25
- Westerhout, G. 1976, Maryland-Bonn Galactic 21-cm Line Survey, University of Maryland, College Park.
- Wilkinson, M. I., & Evans, N. W. 1999, MNRAS, 310, 645
- Xue, X. X., Rix, H. W., Zhao, G., et al. 2008, ApJ, 684, 1143
- Xue, X. X., Rix, H. W., Yanny, B., et al. 2011, ApJ, 738, 79
- Xue, X. X., Ma, Z., Rix, H. W., et al. 2012, ApJ, submitted (arXiv:1211.0549)