Spatially Resolved Analysis of Neutral Winds, Stars, and Ionized Gas Kinematics with MEGARA/GTC: New Insights on the Nearby Galaxy UGC 10205

In this section, we describe the main characteristics of the process followed to model the galaxy continuum for the case of the LR−V grating. As commented previously, the LR−V covers the range from 5143 to 6164 Å with a spectral resolution of FWHM = 0.937 Å at λ_c = 5695 Å.

First, a Voronoi binning algorithm (Cappellari & Copin 2003) is applied to increase the signal-to-noise ratio (S/N) of the spectra in the individual spaxels, reaching an S/N ∼ 20 over the continuum. This process allows for a more homogeneous distribution of the S/N within the data cube. Then, we model the galaxy continuum in the spatially binned MEGARA data cube using a Penalized Pixel-Fitting method (pPXF; Cappellari & Emsellem 2004; Cappellari 2017). The aim of pPXF is to build the stellar template that will best reproduce the observed spectrum in each Voronoi cell. For that purpose, we used the latest theoretical stellar library by Coelho (2014) and P. Coelho et al. (2020, in preparation), which represents an expansion of the previous stellar population modeling in Coelho et al. (2005, 2007) and Walcher et al. (2009). The resolution of these models, R = 20000, is optimal for all of the MEGARA setups and especially for the highest-resolution VPHs (R ≈ 20000). We selected a total of 660 models with different ages ranging from 30 Myr to 14 Gyr and three different metallicities ([Fe/H] = −1.0, 0.0, 0.2) at both scaled-solar and α-enhanced mixtures. The stellar continuum was fitted over the spectral range (5150–6160) Å, which contains multiple stellar absorption lines. We carefully masked the ISM features, as they are the result of both the stellar and ISM contribution. Also, the He i emission line at 5875.67 Å was masked due to its proximity to the Na i D line. Finally, the best stellar model was subtracted from the observed spectra to detect the presence of Na i D interstellar absorption. To assess the robustness of the pPXF fits within the region measured and its impact on the results, we have applied a standard bootstrap analysis (see Wu 1986) using 100 simulations to each of the Voronoi spectra. First, a redistribution of the best-fit model residuals is done. Then, we fitted the resampled spectrum using pPXF. For the two first LOSVD moments (V and σ), we obtained dispersions of up to 9 and 10 km s⁻¹ after running the 100 repetitions, respectively. We also found mean differences of only 7 km s⁻¹ (5 km s⁻¹) between the original velocities (stellar velocity dispersions) values and the ones obtained after applying the bootstrapping technique.

Figure 2 shows a representative fit for one of the Voronoi cells. The position of this particular Voronoi cell within the galaxy can be seen in the inset of the figure. The black line is the observed spectrum, while the red line is the fit for the stellar component. The vertical blue shaded regions show the ISM features and sky-lines that have been masked in the fitting process. The residuals of the fitting appear in green at the bottom. There is a clear detection of ISM Na i D absorption in this spectrum.

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The analysis described in this section allows us (i) to derive fundamental parameters of the galaxy kinematics such as the first four order moments of the line-of-sight velocity distribution (V, σ, h₃, and h₄) for each Voronoi cell of the MEGARA data cube (Section 5.2), and (ii) to explore the presence of interstellar Na i D absorption in UGC 10205 and its connection with neutral gas outflows (Section 5.5).

In the following paragraphs, we describe the analysis performed to obtain a reliable measure of the Hα emission flux for the case of the HR−R grating. This setup is characterized by wavelength coverage from 6445 Å to 6837 Å and an FWHM = 0.355 Å at λ_c = 6646 Å. The HR−R observations were taken on different nights, 2017 June 30 and July 1, and the pointing was slightly offset between them (we remind the reader that the data were taken as part of the Commissioning Time). Thus, the first step was to combine both observations to create a new data cube that takes into account the relative offsets between them.

The second step was to remove the stellar continuum of the galaxy. However, due to the lack of absorption features in the wavelength range covered by the HR−R setup, the use of codes such as pPXF is not recommended. For that reason, the method applied for the HR−R case slightly differs from the one used in the LR−V grating (Section 4.1). The approach followed here to estimate the Hα absorption-corrected emission flux is to derive (i) the equivalent width of the stellar Hα absorption (EW${}_{{\rm{H}}\alpha ,\mathrm{abs}}$) and (ii) the stellar velocity corresponding to each spaxel in the data cube by anchoring the stellar populations models to the ones obtained for the LR−V grating. The latest calculation requires us to reference the HR−R observations to the LR−V ones. Due to pointing effects, the spatial coverage of the galaxy is slightly different in both setups, so we have created data cubes with a pixel scale of 04 in each of the spatial axes. The area of these new synthetic spaxels, on which we will perform the subsequent analysis, will therefore be 0.4 × 0.4 arcsec² and will be simply referred to as spaxels. The value of the spaxel size was chosen as the best compromise between the seeing of the observing nights and the routine used to create the data cubes. To estimate the EW${}_{{\rm{H}}\alpha ,\mathrm{abs}}$ we used the CALIFA spectrum (3700–7000 Å) integrated in the same area as the one in our MEGARA FoV data cube. To recover the best-fit model of the stellar continuum, we run the pPXF code. Finally, we have obtained the Gaussian profile corresponding to the stellar absorption that is added to the Hα emission flux in the HR−R data cube. The main assumption in this approach is that the model that best reproduces the stellar continuum is the same for all of the spaxels in the MEGARA data cube. As the mean value of the recovered stellar flux at the Hα wavelength is around 9% of the total Hα flux, we applied this correction assuming that it represents a small second-order correction for the estimation of the total Hα flux. As is done in the case of the LR−V, we also increase the S/N ratio, making a spatial binning of the data cube. In this case, we have defined the S/N as the ratio between the Hα emission line and the nearest continuum and imposed an S/N > 15.

The high spectral resolution of MEGARA allow us to distinguish double- and triple-peaked Hα emission-line profiles in this galaxy. The finding of up to three kinematically distinct gaseous components is in accordance with the results from Vega Beltran et al. (1997). Some examples showing the complexity of the Hα emission-line profiles will be shown and examined in the following sections.

To investigate the gas kinematics, we make use of the Hα emission line. A previous long-slit spectroscopic study of the kinematics of the gas in UGC 10205 was performed by Vega Beltran et al. (1997) using the Intermediate Dispersion Spectrograph at the Isaac Newton Telescope obtaining a mean value of FWHM = 0.86 Å (σ ∼ 17 km s⁻¹). These authors found line splitting for three kinematically distinct gaseous components in the position–velocity diagram along the major axis of the galaxy in the inner ±13''. A double-peaked Hα emission appeared in the region −13'' ≤ r < 3'' and a third Hα component is found at distances in the range 3'' ≤ r ≤ 13''. Later, García-Lorenzo et al. (2015) presented a comprehensive analysis of the gas velocity fields for 177 galaxies among which UGC 10205 is present. The galaxies were observed as part of the CALIFA survey using the Potsdam Multi-Aperture Spectrophotometer (PMAS; Roth et al. 2005) in the PPak mode (Kelz et al. 2006), which provides a nominal resolution (R ∼ 850 at λ ∼ 5000 Å) that is not sufficient to probe the presence of multiple components in this object.

Here, the high-resolution MEGARA IFS data improves the ability to map the kinematics of the line-emitting gas in a spatially resolved manner, combining the information on the morphology and kinematics simultaneously. In the next section, we attempt an interpretation for the kinematic properties of the ionized gas phase by fitting a rotating exponential thin-disk model to the observations.

5.1.1. Thin-disk Model

Both García-Lorenzo et al. (2015) and Vega Beltran et al. (1997) derived monotonically rising rotation velocity curves for the inner regions of UGC 10205. Following these results, we adopt an arctangent parameterization with a smooth turn-over to recover the shape of the rotation curve, V_r = (2/π) v_max arctan(r/r_t) (Courteau 1997), where v_max is the asymptotic maximum rotation speed and r_t is the transition radius between the rising and flat part of the rotation curve.

A suite of 2D kinematic models is built to recover the 2D ionized velocity field of the purely rotating galactic disk. The models contain six free parameters: v_max, r_t, position angle (PA), inclination (i), and the position of the dynamical center (x0, y0). To define the parameters' range, we use reported measurements and allow variations that are consistent with our data. The corresponding ranges are: v_max = (250–350) km s⁻¹, r_t = (0.05–0.5) kpc, i = (20–89)°, and PA = (40–170)°. For the dynamical center, we use the photometric center as our reference value. The photometric center is defined as the peak of the continuum emission in the region (6540–6620) Å, and we allow a variation of 2'' around it. A systemic velocity of 6556 km s⁻¹ is taken from NED.

We utilize a minimization based on a mean-squared error to find the best fit between the model and data. As the Hα channels show a somehow clumpy distribution (see Figure 3), we apply the minimization on the voronois that are more relevant to the shape of the rotation curve. The model parameters that best describe the data are v_max = 292 km s⁻¹, r_t = 0.12 kpc, i = 75°, and PA = 130°. In the case of the inclination, a wealth of values can be found in the literature. García-Lorenzo et al. (2015) derived a photometric inclination of 54° using the whole galaxy, while Rubin et al. (1985) reported i = 84°. Due to the recent interactions suffered by the galaxy (as suggested in Reshetnikov & Evstigneeva 1999), the gas disk of the outer parts might be mostly affected by them. Thus, the inclination for the innermost parts might be different. We have obtained i = 75° for these regions. The orientation of the line of nodes is in reasonably good agreement with the value inferred by Barrera-Ballesteros et al. (2015). They derived a morphological PA = (132.4 ± 1.6)° by fitting an ellipse to an isophote at radius 15'' in the r−band SDSS image. They also measured kinematic PA for the ionized component and derived PA = (120.3 ± 2.7)° and PA = (129.4 ± 1.5)° for the approaching and receding sides, respectively.

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Figure 3 shows the Hα channel maps of the HR−R data cube. Each map represents the line emission at a particular wavelength channel (from 6705.0 to 6709.5 Å) with a channel step of Δλ = 0.5 Å. From the analysis of this figure, we infer the presence of a highly inclined gas-rich disk located in the central regions of this galaxy. The isovelocity contours are well reproduced by our model for the central parts (see the white solid lines in the channels maps from 6707.0 to 6708.5 Å of Figure 3). However, some of the ionized gas do not follow the general rotation pattern, as indicated by the isovelocity curves (see the green and orange crosses in the channel maps from λ = 6704.5 to λ = 6707.5 Å in Figure 3). This component will be described later.

To recover the velocity maps of the ionized gas components, we need to disentangle the different emission lines in the Hα profile. We fit multiple Gaussian components and a polynomial continuum to separate up to three kinematically distinct gaseous components. The corresponding ionized gas kinematic maps are shown in the top panel of Figure 4.

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The first component (component 1) is the one associated with the thin-disk model. We trace this component based on the velocity associated with the centroid of each Voronoi cell in the disk model, i.e., we defined the Gaussian fit of this component as the closest one to the value of the velocity in the model. Panels (e) and (f) in the bottom part of Figure 4 show the best thin-disk model for component 1 and the residuals after subtracting the best thin-disk model. The latter map indicates that the residuals fluctuate around zero randomly, which confirms that the thin-disk model is a good approximation. The results by Vega Beltran et al. (1997) pointed out the existence of a second component with a similar rotation pattern to the previous one. The spatial extension of this component (component 2) is more limited to the central part of the galaxy, as can be seen in panel (b) of Figure 4. There is also a third component (component 3) with a velocity close to the systemic, ranging from −60 to 85 km s⁻¹ relative to the systemic. This last component is spatially coincident with the regions previously characterized as deviations from the general rotation pattern (the green and orange crosses in Figure 3).

Finally, we select a few characteristic Voronoi cells to show the complexity of the emission-line profiles together with the Gaussian fits of the three kinematically distinct components. The position of these Voronoi cells is shown with blue and orange colors in the middle panel of the top row in Figure 5. The blue, red, and orange Gaussian fits in the spectra of this figure correspond to components 1, 2, and 3 in Figure 4, respectively. The blue dashed line is the velocity of the thin-disk model, while the orange dashed line represents the systemic velocity. Also, a significant rotational broadening for the Hα profiles in the central regions can be seen in this figure (see panel corresponding to voronoi = 3). As we will describe later in Section 5.4, this effect is due to the steep rise of the rotational velocity curve in the innermost regions of this galaxy. We would expect the internal dynamics of these regions to be better constrained in nearly face-on or less inclined systems where the σ values are expected to be less broad by the effect of rotation. In spite of the complex structure that follows the ionized gas distribution, our thin-disk model is able to reproduce the kinematic pattern found in this object.

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5.1.2. Deviations from the Pure Thin Disk Model

As mentioned before, the distribution of the ionized gas in the low-velocity channels (from 6704.5 to 6707.5 Å) reveals the presence of a kinematically distinct component that does not follow the rotation pattern of the gas-rich disk. To explain the gas velocity field in those particular regions, two possible interpretations arise.

On one hand, this dynamical component seems to be spatially coincident with the position of the dust lanes that might be driving the motions of the gas (see positions marked as green and orange crosses in Figure 3). Dust lanes are, in most cases, morphologically associated with a gas dense component even in early-type galaxies (Finkelman et al. 2010, 2012). Judging from the large-scale images available for UGC 10205 (see upper panel in Figure 1 as an example), the well-defined and prominent dust lanes of this object are highly inclined. Due to the reduced size of the MEGARA FoV, we are sampling a relatively small angle on the sky in comparison with the large-scale size of the object (∼1'). Assuming a close to edge-on orientation for the dust lanes, we expect to recover angles (ϕ) around 90° and 270° within this structure. Should that be the case, the difference between the radial velocity component of the gas in each Voronoi cell and the systemic velocity of the thin-disk model (i = 75°) should be nearly zero. Possible values for the inclination of the dust lane were investigated to check whether or not the velocities in these regions might be coherent with the structure of a disk model with higher inclination than the main thin-disk model (i = 75°). An optimal value of i = 83° was found.

Thus, the bottom panel in Figure 6 shows the distribution of the distances and angles probed by the Voronoi cells in the plane of the dust lanes assuming i = 83° for this plane. The SE (approaching) side of the dust lane is represented by the orange points, while the SW-to-NW (receding) side is marked by the green points. In particular, the points represent the centroid of each Voronoi cell associated with the regions where the line of sight passes through the plane of the dust lanes (positions also marked as green and orange crosses in Figure 3).

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Additionally, the difference between the velocity of this gas component and the systemic velocity of the thin-disk model (i = 75°) computed for each Voronoi cell is shown in the upper panel of Figure 6 as green/orange points. As expected, this difference in velocity (Δv) is nearly zero for ϕ ∼ 90° and ϕ ∼ 270°. As an example of a particular Voronoi cell, we include the spectrum corresponding to voronoi = 7 (Figure 5). In this spectrum, two different features can be clearly seen: (i) a component almost at the systemic velocity of the model and (ii) the component of the thin-disk model. The former one would be the gas component associated with the dust-lane structure.

At the galactocentric distances corresponding to the positions of the receding side of the dust lane (∼30''), we expect to reach the maximum velocity for the thin-disk model (v_max = 292 km s⁻¹, green solid line). i = 83° is the inclination of the dust-lane that minimizes the distance between the model and Δv. For the case of the SE side of the dust lane (orange points), the galactocentric distances are ∼10'', so the velocity curve has still not reached its maximum velocity. A velocity of 130 km s⁻¹ (orange dashed line) is the best value consistent with the inclination derived previously. Thus, having a slightly more inclined dust lane (i = 83°) with the same galaxy's potential than the thin-disk model (i = 75°) seems to be a reasonably good explanation for these regions.

On the other hand, the origin of this component could be associated with the merging scenario that creates a localized enhancement of the star formation with a distinct kinematic pattern, and the gas might be tracing non-circular motions in those regions. The numerical model presented by Reshetnikov & Evstigneeva (1999) relied on the tidal disruption of a small E/SO object by the massive early-type galaxy. Non-circular gas motions in the nuclear region of UGC 10205 were suggested by these authors. However, the nice match between both the Δv values and its azimuthal variation with respect to the one of highly inclined dust lanes seems to favor the former scenario.

The MEGARA absorption-line kinematics for the central regions of the galaxy UGC 10205 are presented in Figure 7. This figure shows both the stellar velocity field and the stellar velocity dispersion maps derived from our pPXF analysis. pPXF yields the values of the stellar mean velocity and stellar velocity dispersion for each Voronoi cell applying an S/N rejection criterion of 20. The reader is referred to Section 4.1 where the main procedure followed to create these maps is explained in detail.

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The stellar velocity map (upper panel in Figure 7) shows a clear stellar rotation pattern with a symmetric velocity field with respect to the galaxy center and with a maximum radial velocity of ∼6628 km s⁻¹. Typical errors in our stellar velocity measurements range from 4 to 23 km s⁻¹ with mean errors of 10 km s⁻¹. To check the accuracy of our kinematic analysis, a visual inspection is performed using the results presented in Falcón-Barroso et al. (2017). These authors found a similar stellar rotation pattern using the mid-resolution CALIFA data (V1200 with R ∼ 1650) in the wavelength range 3850–4600 Å.

The stellar velocity dispersion map (bottom panel in Figure 7) displays values ranging from 124 to 230 km s⁻¹, with values in the nuclear region ∼190 km s⁻¹. These values are already corrected for the instrumental resolution, which, in our case, is σ ∼ 21 km s⁻¹. Although no signs of kinematically decoupled components appeared to be present, we have performed the analysis of the Gauss–Hermite moment h3 (skewness of the velocity profile) to examine this effect. The h3 map (not shown) indicates that we can safely discard the presence of an anticorrelation between these values and those of the stellar velocities.

By applying an asymmetric drift correction (ADC), it is possible to account for the effect of the stellar random motions within galaxies. Basically, the mean tangential velocity of a stellar population lags the actual circular velocity as defined by the gravitational potential of the galaxy. ADC accounts for this difference. The effect of the ADC phenomenon will be more significant in those cases where the velocity dispersion of different stellar populations is higher. Although this effect was first noted in the solar neighborhood (Strömberg 1924, 1925), ADCs have been extensively used in the literature to reconcile gas and stellar rotation curves observed in external galaxies.

The Stellar Velocity Ellipsoid (SVE) is described in cylindrical coordinates by its radial, tangential, and vertical components: σ_R, σ_ϕ, and σ_Z. The shape of the SVE could be parameterized by the axial ratios σ_Z/σ_R, σ_ϕ/σ_R, and σ_Z/σ_ϕ. For the purpose of this work, we focus our attention on the α = σ_Z/σ_R and β = σ_ϕ/σ_R parameters. In particular, Mogotsi & Romeo (2019) found a global vertical-to-radial velocity dispersion ratio of α = 0.97 ± 0.07 for UGC 10205. Similar values of the radial and vertical dispersions point to an isotropic heating.

Here, we assume that the stellar azimuthal anisotropy (β_ϕ) can be approximated using the epicycle anisotropy, i.e., the stellar orbits are considered nearly circular (Gerssen et al. 1997, 2000; Shapiro et al. 2003; Ciardullo et al. 2004; Westfall et al. 2011; Gerssen & Shapiro Griffin 2012; Blanc et al. 2013; Gentile et al. 2015). Thus, we measure β_EA (hereafter β for simplicity) using the following expression:

$$\begin{eqnarray}&&\beta =\sqrt{\displaystyle \frac{1}{2}\left(\displaystyle \frac{\partial {ln}({v}_{\phi })}{\partial {ln}(R)}+1\right)}\end{eqnarray} \tag{ 1 }$$

where v_ϕ is the tangential speed of the stars. We found a mean value of β = 0.86 ± 0.12. Due to the small dispersion found and in order to simplify the calculations, we assume the previous value for all of the Voronoi cells.

Once α and β are known, we infer σ_R in each Voronoi cell using the values of σ_LOS previously obtained (bottom panel of Figure 7):

$$\begin{eqnarray}&&{\sigma }_{\mathrm{LOS}}^{2}={\sigma }_{R}^{2}\sin {\phi }^{2}\sin {i}^{2}+{\sigma }_{\phi }^{2}\cos {\phi }^{2}\sin {i}^{2}+{\sigma }_{Z}^{2}\cos {i}^{2}\end{eqnarray} \tag{ 2 }$$

where ϕ is the angle of the central position of each Voronoi cell in the plane of the galaxy measured from the line of nodes and i refers to the inclination. We assume the same inclination for each Voronoi cell, i.e., in this case, we adopt the same inclination for the innermost regions of the galaxy. Due to the agreement between the ionized gas rotation axis and the stellar rotation axis with a difference of (6 ± 3)°, we use an inclination of 75° for the ADC.

To estimate the ADC in each Voronoi cell, we apply the following expression as reproduced from equation (4–33) of Binney & Tremaine (1987):

$$\begin{eqnarray}\begin{array}{rcl}{V}_{C}^{2} & = & {v}_{\phi }^{2}-{\sigma }_{R}^{2}\left[\displaystyle \frac{\partial {ln}({\nu }_{R})}{\partial {ln}(R)}+\displaystyle \frac{\partial {ln}({\sigma }_{R}^{2})}{\partial {ln}(R)}\right.\\ & & +\,\left.1-\displaystyle \frac{{\sigma }_{\phi }^{2}}{{\sigma }_{R}^{2}}+\displaystyle \frac{R}{{\sigma }_{R}^{2}}\displaystyle \frac{\partial ({v}_{R}{v}_{Z})}{\partial Z}\right].\end{array}\end{eqnarray} \tag{ 3 }$$

This expression shows the difference between the true velocity (i.e., V_C is the circular velocity of a test particle in the potential) and the observed circular velocity. If the SVE is aligned with the cylindrical coordinate system (R,ϕ,z), the last term in Equation (3) could be neglected.

The term ν_R in Equation (3) is proportional to the stellar mass surface density (Σ) under the assumption that Σ is well traced by the surface brightness profile of the galaxy. In this case, to trace the radial dependence of ν, we apply a one-dimensional (1D) photometric decomposition over the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS; Chambers et al. 2016) y-band light profile. Among all of the Pan-STARRS bands, the near-infrared one is considered the best tracer of the stellar mass as the light is mainly dominated by old MS and red giant branch stars. Also, problems associated with the interstellar dust (as shown by the presence of prominent dust lanes in UGC 10205) are partly avoided. The fit was performed following the procedure explained in Dullo et al. (2019). We discard non-symmetric features due to bars or spiral arms in the fitting process. The bulge component is parameterized using a Sérsic profile (Sérsic 1968) with a best-fitting Sérsic index n = 1.48 ± 0.22 and a half-light radius r_e = 410 ± 081. The galaxy disk component is described with an exponential profile with scale length h = 108 ± 13.

Figure 8 shows the results obtained after applying the ADC to the stellar component. For comparison, the predictions for the rotation curves of Sérsic bulges obtained by Noordermeer (2008) are also shown. These curves have been scaled up to take into account the mass and the effective radius of the bulge component. The effective radius, obtained directly from our 1D decomposition, is r_e = 410 ± 081 (r_e ∼ 1.97 kpc). For the stellar mass derivation, we apply the bulge-to-total flux ratio (B/T = 0.19 ± 0.3) obtained as a result of the 1D decomposition and the total stellar mass of the galaxy derived in Walcher et al. (2014) (log(M_⋆) = 10.997 ± 0.111 M_☉). As the 1D decomposition yields n = 1.48 ± 0.22, we represent the rotation curve for a fiducial bulge with a Sérsic concentration parameter n = 2 as the best approximation in our case. For the same n = 2, the blue dashed line curves correspond to variations of the axis ratio q = 0.2 (top) and q = 1 (bottom) in Figure 8. It is expected that the rotation curves from Noordermeer (2008) are a lower limit, as they only consider the bulge mass component, but our V_C measurements also trace the mass in the inner disk of the galaxy.

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We have also included in Figure 8 some observational data found in the literature for this galaxy. In particular, the stellar rotation curve derived in Kalinova et al. (2017) is shown in orange. In the new classification proposed by these authors, the rotation curve of UGC 10205 is classified as round-peaked, meaning that "the circular velocity rises steeply and has a round peak, gradually changing to the flat part of the circular velocity curve (CVC) at radius ∼0.5 R_e," where R_e is the value they derived for the whole galaxy. They also found that this class is the most common one among early-type galaxies (E4−S0a) and spiral galaxies classified as Sa−Sbc. The typical value expected for the average amplitude of the CVC is around 300 km s⁻¹, similar to the v_max value derived in Section 5.1 for the thin-disk model.

On the other hand, measurements of the ionized gas velocity rotation curve are also included. As the thin-disk model derived in Section 5.1 was recovered using mainly the inner regions of the galaxy, we include here other literature data that cover the entire galaxy. The velocity curve based on the Hα + [NII] emission-line data obtained by García-Lorenzo et al. (2015) within CALIFA appears as the green dotted–dashed lines in Figure 8. The UGC 10205 major-axis kinematic curves derived by Vega Beltran et al. (1997) for the multiple Hα components found on this object using long-slit spectroscopy data are shown by the gray dotted lines. Both García-Lorenzo et al. (2015) and Vega Beltran et al. (1997) derived monotonically rising rotation velocity curves for the inner regions of UGC 10205. These data have been homogenized to i = 75°. Our stellar data points once corrected by ADC effects are in good agreement with the values obtained by the previous authors up to a galactocentric distance of R ∼ 17''. For R > 17'', our measurements match the ones by Vega Beltran et al. (1997) along the NW side of the major axis of the galaxy. These results suggest that assuming an inclination of 75° for the stellar component in the central part of this galaxy was a reasonable approach. Also, the adoption of a tangential parameterization with a smooth turn-over to recover the shape of the thin-disk model in Section 5.1 is justified by the shape of the previous rotation curves.

Average values of the ADC in local disk galaxies are usually 10%–20% in late-type systems (see Ciardullo et al. 2004; Merrett et al. 2006; Noordermeer et al. 2008; Herrmann & Ciardullo 2009; Westfall et al. 2011; Martinsson et al. 2013). Higher values for the ADC are expected for E/S0 and early-type spirals. Here, we are analyzing the central part of an S0/Sa galaxy. We found a mean value of V_rot(stars)/V_rot(gas) = 0.75 ± 0.08. This result is consistent with the one by Cortese et al. (2014). These authors explored only the central parts of a sample mainly composed by early-type spirals finding an average ratio of V_rot(stars)/V_rot(gas) = 0.75. These results point out the necessity of having high values of the ADC in order to reconcile the discrepancy between the ionized and the stellar velocity rotation curves for these morphological types.

Galactic winds are an essential element that determines the evolution of galaxies through cosmic time. In particular, as explained in the introduction, galactic outflows are thought to play a key role in self-regulating star formation in galaxies, and they also constitute necessary mechanisms to explain the chemical evolution and metal enrichment of the circumgalactic medium (Oppenheimer & Davé 2006, 2008).

At optical wavelengths, the ISM Na i D absorption doublet is commonly used to trace the properties of neutral atomic gas inflows and outflows in the ISM (Heckman et al. 2000; Schwartz & Martin 2004; Martin 2005, 2006; Rupke et al. 2005; Veilleux et al. 2005; Chen et al. 2010; Sarzi et al. 2016; Roberts-Borsani & Saintonge 2019). Due to the high inclination of this object, the Na i D absorption-line profiles are confused with multiple components along the line of sight. Searching for signatures of inflowing/outflowing material in highly inclined systems require having high spatial and spectral-resolution observations to break up the absorption profile into different components. Here, the observations provided by MEGARA show the variety of the profiles and the distinct kinematic components for the Na i D excess. Some examples of the ISM absorption Na i D lines that will be explained later (Sections 5.5.1 and 5.5.2) are provided in Figure 9.

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For the discussions about inflows/outflows that appear in the following sections, we assume that the foreground gas is the dominant source of the absorptions found in the Na i D profiles. In this scenario, blueshifted absorption is a signature of gas moving toward the observer (outflow) while redshifted absorption is indicative of gas moving toward the galaxy (inflow). We do not detect re-emission of absorbed photons from the background gas. For more details about this topic, the reader is referred to the detailed discussion found in Roberts-Borsani & Saintonge (2019).

5.5.1. Infalling Neutral Gas

5.5.2. Presence of Outflow Signatures: Mass and Outflow Rate of the Wind

Major galaxy mergers and ULIRGS in the local universe exhibit outflows with relatively large velocities and a conical shape (Rupke et al. 2002; Rupke & Veilleux 2005; Soto et al. 2012; Westmoquette et al. 2012; Cazzoli et al. 2014; Perna et al. 2019). Here, we present results from a less active star-forming galaxy. The right panel in Figure 9 shows that clear blueshifted Na I D absorption signatures are present in this galaxy. The spectra clearly show the presence of double-peaked components in the Na I D absorption-line profiles. High spectral resolution is needed to distinguish these components. The analysis of the spatially resolved optical spectroscopy of the blueshifted NaI D suggests the presence of a wide-angle conical outflow emerging from the central regions of UGC 10205 and perpendicular to the galactic plane (Figure 10). The outflow shows a maximum projected velocity of up to −87 km s⁻¹, blueshifted with respect to the systemic.

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To explore to what extent this neutral gas outflow might remove relatively large amounts of gas from the galaxy, we estimate both the total mass in the wind and the outflow mass rate applying the thin-shell free wind model (Equations (13) and (14) in Rupke et al. 2005). Since we have information on the spatial distribution of the wind thanks to the IFS data, we follow the approach of Shih & Rupke (2010), Rupke & Veilleux (2013), and Cazzoli et al. (2014, 2016) using a Voronoi-by-Voronoi basis and assuming a series of thin shells to make it a valid approach for this case. Following the previous prescription, the outflow mass rate is proportional to the deprojected velocity, the H i column density, and the deprojected solid angle measured in each Voronoi cell. The prescriptions applied to convert Na column densities into H i column densities are largely affected by the assumptions made on the ionization fraction, the depletion onto dust grains and the Na abundance. To avoid the previous uncertainties in the estimation of the column density of H i atoms, we adopt here the same approach as in Cazzoli et al. (2014, 2016). These authors make use of both the relation between the H i and the color excess proposed by Bohlin et al. (1978) (N_HI = 4.8 × ${E}_{(B-V)}$ × 10²¹ cm⁻²) and the relation between the color excess and the equivalent width as in Turatto et al. (2003) $({E}_{(B-V)}\,=-0.04+0.51\times {\mathrm{EW}}_{\mathrm{NaD}})$. We calculate a mean value of 1.65 ± 0.07 × 10²¹ cm⁻² for the H i column density that is in the range of the expected values for low-z galaxies as reported in Heckman et al. (2015) and Martín-Fernández et al. (2016). The cold-gas mass outflow rate is 0.78 ± 0.03 M_☉ yr⁻¹, and the total mass in the wind is equal to 4.55 ± 0.06 × 10⁷ M_☉. These values are consistent with the ones derived using the formalism of the thin-shell model in galaxies with lower star formation rates (SFRs), as in Roberts-Borsani & Saintonge (2019) where the authors used galaxies with SFRs in the range 1.45 < SFR [M_☉ yr⁻¹] < 16.98, obtaining outflow mass rates ranging from $0.15\lt {\dot{M}}_{\mathrm{out}}$ [M_☉ yr⁻¹] < 1.74.

A significant mass loss has been postulated to regulate the star formation processes within galaxies. The mass loading factor, expressed as the ratio $\eta ={\dot{M}}_{\mathrm{out}}$/SFR, is used to describe the strength of the winds. This factor has important consequences for the predictions in the theoretical models, with some findings suggesting that η increases with redshift (Barai et al. 2015; Muratov et al. 2015; Sugahara et al. 2017). To calculate the SFR, we have derived dust-corrected Hα growth curves using CALIFA data (following the methodology explained in detail in Catalán-Torrecilla et al. 2017). In the region covered by the MEGARA FoV and applying the conversion SFR(Hα) = 5.5 × 10⁻⁴² L(Hα_corr) (Kennicutt et al. 2009), we obtained SFR(Hα_corr) = 0.49 M_☉ yr⁻¹ and η = 1.59. Due to the large amount of dust present in this galaxy, the attenuation correction based on Balmer Decrement measurements might be underestimating the SFR and affecting the real value of η. To mitigate this problem, we make use of hybrid calibrations combining luminosities measured directly with that of the light emitted by dust after being heated by young massive stars (Gordon et al. 2000; Inoue et al. 2001; Iglesias-Páramo et al. 2006; Calzetti et al. 2007; Hao et al. 2011; Kennicutt & Evans 2012; Catalán-Torrecilla et al. 2015). We adopt the Hα_obs, FUV_obs, 22 μm and TIR luminosities calculated for this object in Catalán-Torrecilla et al. (2015) as our best estimations. Using the hybrid SFR prescriptions for the different combinations of Hα + a × IR and FUV + b × IR, we derived a mean SFR of SFR = 1.32 M_☉ yr⁻¹ and a loading factor of η = 0.59. As these SFR measurements are for the whole galaxy while the effect of the outflow has been computed at a restricted distance limited to our current FoV, the estimated value of η serves here as a lower limit. Mass loading factors below unity are typically found on galaxies similar to UGC 10205 (see Roberts-Borsani & Saintonge 2019). Large-scale observations that trace the wind extension outside the disk are needed to explore the effect in the neighboring ISM and circumgalactic medium.