11institutetext:  Instituto de Astrofísica de Canarias (IAC), E-38205 La
Laguna, Tenerife, Spain 22institutetext: Depto. Astrofísica, Universidad de La
Laguna (ULL), E-38206 La Laguna, Tenerife, Spain 33institutetext: Instituto de
Astronomía,Universidad Nacional Autonóma de Mexico, A.P. 70-264, 04510,
México,D.F. 44institutetext:  Instituto de Cosmologia, Relatividade e
Astrofísica – ICRA, Centro Brasileiro de Pesquisas Físicas, Rua Dr.Xavier
Sigaud 150, CEP 22290-180, Rio de Janeiro, RJ, Brazil 55institutetext:
Instituto de Astrofísica de Andalucía (CSIC), Glorieta de la Astronomía s/n,
Aptdo. 3004, E18080-Granada, Spain 66institutetext:  European Southern
Observatory (ESO), Karl-Schwarzschild-Str. 2, D-85748 Garching b. Muenchen,
Germany 77institutetext: Max-Planck-Institut für Astronomie, Heidelberg,
Germany. 88institutetext: Estación Experimental de Zonas Aridas (CSIC), Ctra.
de Sacramento s/n, La Cañada, Almería, Spain 99institutetext: Instituto
Nacional de Astrofísica, Óptica y Electrónica, Luis E. Erro 1, 72840
Tonantzintla, Puebla, Mexico 1010institutetext: Centro de Estudios de la
Física del Cosmos de Aragón, E-44001 Teruel, Spain 1111institutetext: CEI
Campus Moncloa, UCM-UPM, Departamento de Astrofísica y CC. de la Atmósfera,
Facultad de CC. Físicas, Universidad Complutense de Madrid, Avda. Complutense
s/n, 28040 Madrid, Spain. 1212institutetext: Millennium Institute of
Astrophysics, Universidad de Chile, Santiago, Chile 1313institutetext:
Departamento de Astronomía, Universidad de Chile, Casilla 36-D, Santiago,
Chile 1414institutetext: Australian Astronomical Observatory, PO Box 915,
North Ryde, NSW 1670, Australia 1515institutetext: Department of Physics and
Astronomy, Macquarie University , NSW 2109, Australia 1616institutetext:
Leibniz-Institut für Astrophysik Potsdam (AIP), An der Sternwarte 16, D-14482
Potsdam, Germany

# Central star formation and metallicity in CALIFA interacting galaxies

J.K. Barrera-Ballesteros , Central star formation and metallicity in CALIFA
interacting galaxiesCentral star formation and metallicity in CALIFA
interacting galaxiesCentral star formation and metallicity in CALIFA
interacting galaxiesCentral star formation and metallicity in CALIFA
interacting galaxies<EMAIL_ADDRESS>S. F. Sánchez Central star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies B. García-Lorenzo Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies J. Falcón-Barroso Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies D. Mast Central star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies R. García-Benito Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies B. Husemann Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies G. van de Ven Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies J. Iglesias-Páramo Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies F.F. Rosales-Ortega Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies M.A. Pérez-Torres Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies I. Márquez Central star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies C. Kehrig Central star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies R. A. Marino Central star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies J. M. Vilchez Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies L. Galbany Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies Á.R. López-Sánchez Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxiesCentral star formation and
metallicity in CALIFA interacting galaxies C. J. Walcher Central star
formation and metallicity in CALIFA interacting galaxiesCentral star formation
and metallicity in CALIFA interacting galaxies the CALIFA collaboration

We use optical integral-field spectroscopic (IFS) data from 103 nearby
galaxies at different stages of the merging event, from close pairs to merger
remnants provided by the CALIFA survey, to study the impact of the interaction
in the specific star formation and oxygen abundance on different galactic
scales. To disentangle the effect of the interaction and merger from internal
processes, we compared our results with a control sample of 80 non-interacting
galaxies. We confirm the moderate enhancement ($\times$ 2-3 times) of specific
star formation for interacting galaxies in central regions as reported by
previous studies; however, the specific star formation is comparable when
observed in extended regions. We find that control and interacting star-
forming galaxies have similar oxygen abundances in their central regions, when
normalized to their stellar masses. Oxygen abundances of these interacting
galaxies seem to decrease compared to the control objects at the large
aperture sizes measured in effective radius. Although the enhancement in
central star formation and lower metallicities for interacting galaxies have
been attributed to tidally induced inflows, our results suggest that other
processes such as stellar feedback can contribute to the metal enrichment in
interacting galaxies.

###### Key Words.:

galaxies: evolution - galaxies: interaction - galaxies: star formation -
galaxies: abundances

##  1 Introduction

Interactions and mergers are identified as key mechanisms in increasing the
star formation rate (SFR) in galaxies (e.g., Sanders & Mirabel 1996; Borne et
al. 1999). In particular, luminous infrared galaxies (LIRGs), which are
associated almost exclusively to merger events, present strong episodes of
star formation (e.g., Ellison et al. 2013b). The scenario proposed by these
studies and hydrodynamical numerical simulations (e.g., Mihos & Hernquist
1996; Barnes & Hernquist 1996) suggests that this enhancement is the result of
tidally induced inflows of gas that favors the increment of star formation
activity in the central region of interacting and merging galaxies. On the
other hand, large samples of interacting and merging galaxies in the Sloan
Digital Sky Survey (SDSS, e.g., Ellison et al. 2008, 2013a; Scudder et al.
2012; Patton et al. 2013) indicate that although central SFR is enhanced in
these objects compared with non-interacting galaxies of similar stellar mass,
on average this increment is rather moderate. This indicates that the
triggering of starburst episodes depends on more parameters than the mere fact
of galaxies being in interaction (orbital configuration and intrinsic
properties of the progenitors; e.g., Cox et al. 2006; Di Matteo et al. 2008).

It is also worthwhile noting that statistical spectroscopic studies like the
one above are performed by observing a fixed projected portion of the galaxies
(e.g., SDSS or GAMA fiber sizes; Casteels et al. 2014; Robotham et al. 2014).
This yields measurements on different galactic scales, making it difficult to
assess the extension of star formation. In this regard, IFS observations of
interacting galaxies are crucial for understanding whether the enhancement in
the SFR is a global or a localized process. An example of the usefulness of
such observations has been demonstrated by Wild et al. (2014). From a detailed
study of the Mice galaxies, they found that there is a moderate increment in
the central SFR and no net enhancement in the global SFR. This study considers
a single interacting system. Statistical studies of spatially resolved star
formation in interacting galaxies are therefore required. Even more, to make a
fair comparison, a homogeneously observed sample of non-interacting galaxies
is also required. Recently, numerical simulations are starting to explore the
extend of star formation induced by the interaction. Moreno et al. (2015) find
enhancement in the star formation on the central kpc scales and moderately
suppressed activity at larger galacto-centric radii.

In the above picture, these metal-poor gas inflows decrease the central
metallicity in comparison to non-interacting galaxies (e.g., Kewley et al.
2006). As a consequence, merging galaxies are thought to contribute to the
scatter in the mass-metallicity relation (hereafter M-Z relation) of star
forming galaxies. However, recent numerical simulations that included feedback
processes have suggested that nuclear metallicity depends on more factors than
the dynamics of the gas, such as the chemical enrichment due to the ongoing
star formation, the stellar (and possible AGN) feedback, and returned material
by evolved stars into the interstellar medium (ISM) of the entire galaxy
(Torrey et al. 2012). The result of the interplay between these different
processes in these simulations could lead, in some cases, to a depression in
the central metallicity or even an enhancement with respect to isolated
galaxies. Spatially resolved observational studies are then required to shade
some light on the chemical evolution of interacting or merging galaxies.

Recently, IFS studies have been carried aimed at the understanding of
properties of the ionized gas in individual H ii regions for a large sample of
galaxies. The radial gradient of oxygen abundance in galactic disks has been
characterized, with an observed flattening in this gradient caused by
interactions and mergers (Sánchez et al. 2014). They also confirmed the global
and local nature of the M-Z relation (Sánchez et al. 2013). These studies have
been possible thank to the integral-field spectroscopic (IFS) data provided by
the CALIFA survey (Sánchez et al. 2012). CALIFA is an ongoing IFS survey aimed
at obtaining spatially resolved physical properties, covering the full optical
spatial extent (up to $\sim$ 2.5 times the effective radius), of 600 galaxies
in the nearby universe (0.0005 $<$ z $<$ 0.03) of any morphological type. It
is complete in a wide range of stellar masses ( from $\sim$ 109.5 to
$\sim$1011M⊙, Walcher et al. 2014). This dataset allows us to study for the
first time spatially resolved properties of the ionized gas in a significant
sample of interacting and merging galaxies to unveil the effect of
interactions on different spatial scales and at different stages of the
interaction. It also allows us to compare these properties with a sample of
homogeneous observations of non-interacting galaxies.

In this article we are aiming to investigate the impact of interactions in the
star formation and oxygen abundance on different galactic scales. To
accomplish this, we study the emission-line flux maps extracted from the data
cubes of interacting and post-merger galaxies. From these maps we derived
integrated properties, such as the H$\alpha$ equivalent width [EW(H$\alpha$)
hereafter] and flux ratios essential for deriving oxygen abundances. This
paper is organized as follows. In Section 2 we present the control and
interacting samples, their ionized gas maps, and the aperture measurements.
The comparison of these two samples on different galactic scales is presented
in Section 3. Finally, we summarize our results in Section 4.

##  2 Sample and data

###  2.1 Interacting and control samples

The galaxies that we use in this study are included in the CALIFA objects
observed until May 2014. The selection of the interacting or merging sample is
explained in a forthcoming article (Barrera-Ballesteros et al., submitted).
Briefly, we first selected those objects with companions from the observed
CALIFA sample that are within a projected distance of 160 kpc and systemic
velocities lower than $\Delta v$ ¡ 600 km s-1. We noted that a large number of
companion objects are not included in the CALIFA mother sample. To enhance the
number of complete pairs in the survey, we conducted a complementary project
aimed at observing companions not included in the original mother sample
(P.I.s J.K. Barrera-Ballesteros and G. van de Ven). These observations and
their reduction were carried out using the same strategy and pipeline as from
the CALIFA survey. From the remaining sample of galaxies without close
companions, we visually selected the objects with morphological evidence of
merger event as post-merger systems. Such objects are morphologically
disturbed, highly irregular, with evident tidal features or is there any
signature of a recent merging event (Ellison et al. 2013a). The sample of
interacting and merging consists of 103 objects. We compared our sample of
interacting/merging galaxies with a control sample of 80 non-interacting
galaxies to match the interacting sample in stellar mass and color. This
sample is presented in Barrera-Ballesteros et al. (2014), along with a
comparison of their stellar and ionized gas kinematics.

Figure 1:  Emission-lines properties of a galaxy in the control sample (top
panels, NGC 0214) and in the interacting sample (bottom panels, UGC 312). Left
panels show the H$\alpha$ flux. White-solid and black-dashed circles represent
the central and extended apertures in arcsecs and effective radius units,
respectively. Middle panel shows the [O iii]$\lambda$ 5007, emission line
flux. The units in both flux maps are (log10) 10-16 erg s-1 cm-2 arcsec-2.
Right panels show the logarithm of the absolute values of EW(H$\alpha$) in
units of Å.

###  2.2 CALIFA data cubes and emission-line extraction

Galaxies presented in this study were observed at the Calar Alto observatory
using the PPAK instrument (Roth et al. 2005). This instrument consists of 331
fibers of 2$\aas@@fstack{\prime\prime}$7 diameter each, concentrated in a
single hegaxon bundle covering a field of view (FoV) of $74\arcsec\times
64\arcsec$ with a filling factor of 60%. A three-point dithering technique is
used to reach a filling factor of 100% across the entire FoV (see details in
Husemann et al. 2013). For this study we used the data cubes with an
intermediate nominal spectral resolution (V500 setup) of
$\lambda$/$\Delta\lambda$ $\sim$ 850 at $\sim$5000Å. The wavelength range of
the V500 setup covers several bright emission lines (3745$-$7300Å): H$\alpha$,
H$\beta$, H$\gamma$, [O ii] $\lambda\lambda$ 3728, 3726, [O iii]
$\lambda\lambda$ 4958, 5007, [N ii] $\lambda\lambda$ 5755, 6584, [S ii]
$\lambda\lambda$ 6716, 6730, among others. The final data cube has an
homogenized spectral resolution (FWHM) over the entire wavelength range of
6.0Å, and the wavelength sampling per spaxel is 2.0Å. The total exposure time
per pointing is fixed for all the observed objects to 45 min. The data
reduction was performed by a pipeline designed specifically for this survey
(see details in Sánchez et al. 2012; Husemann et al. 2013, and García-Benito
et al. 2014 for an update to the second data release).

To extract the flux from the ionized gas emission lines, we used the FIT3D
package 111http://www.caha.es/sanchez/FIT3D/ (Sánchez et al. 2006, 2011). We
obtain these fluxes for the following lines: H$\alpha$, H$\beta$, [O iii]
$\lambda\lambda$ 4959, 5007, and [N ii] $\lambda\lambda$5755, 6584. The
analysis, including errors, was performed on a spaxel-by-spaxel basis, which
allows us to create flux maps for each of these emission lines, once
subtracted the underlying stellar population (see an example of emission-line
maps in Fig. 1). We have derived the EW(H$\alpha$) in each spectrum by
dividing the H$\alpha$ flux by the average of the continuum emission adjacent
to H$\alpha$ emission line. This average continuum was derived by measuring
the mean flux of the continuum in spectral windows of 30 Å centered at blue-
shifted and redshifted 100Å away from the H$\alpha$ emission line.

###  2.3 EW(H$\alpha$) and oxygen abundance measurements

Figure 1 shows an example of the wealth of the data provided by the data
cubes. Even for a single galaxy, several structures can be observed in the
emission line and the EW(H$\alpha$) maps, which is a proxy for the specific
star formation rate (sSFR). However, in this study we limited ourselves to the
integrated properties for each galaxy. Studies exploring the star formation
and ionized gas two-dimensional distributions in interacting galaxies will be
left for future works. Thus from the emission line flux maps, we obtained the
integrated properties for each galaxy. We selected those spaxels with errors
smaller than 10% of their flux within two apertures centered on the optical
nucleus: a central and an extended aperture.

To study the impact of the scale used to derive the properties of the ionized
gas, we selected two different scales for the diameter of the central and
extended apertures: a projected (5 and 30 arcsecs) and the effective radius
(0.3 and 2.5 Reff). We derived the effective radius for each galaxy using the
same methodology as outlined in the Appendix A of Sánchez et al. (2014). For
the projected scale, we chose the size of the central aperture to be
approximately twice the size of the spatial PSF in the survey (FWHM $\sim$ 2.5
arcsec). The central region in both samples covers between $\sim$ 0.6 and
$\sim$ 3 kpc. The extended aperture was chosen to cover a wide portion of the
galaxies. In terms of the Petrosian radius we covered a generous portion of
the galaxies (i.e, 1.5 $\lesssim$ $r_{P}$ $\lesssim$ 8). The central aperture
in units of Reff is, in most of the cases, larger than the spatial PSF. It is
also comparable to the central projected aperture. In most of the galaxies,
the extended aperture in units of Reff covers the entire FoV (see Fig. 1). In
a few cases where the two companions in a binary system are covered by a
single FoV, this aperture includes both galaxies (e.g., NGC 169). Our goal has
been to compare how the properties of the ionized gas in the central and
extended regions of interacting galaxies change when we compare it with a
control sample (see Secs. 3.1, 3.2, and 3.3). Nevertheless, our data also
allow us to study the change of the ionized gas metallicity on different
galactic scales (see Sec.3.4).

To obtain the EW(H$\alpha$) for each galaxy, we averaged the individual spaxel
absolute values included within each of the apertures. In the case of the
observed oxygen abundance in each aperture, we used the empirical calibration
O3N2 derived in Marino et al. (2013), which makes use of the logarithm of the
fluxes ratios $\log{([{O\textsc{iii}}]\leavevmode\nobreak\ \lambda
5007/\mathrm{H}\beta)}$ and $\log{([{N\textsc{ii}}]\leavevmode\nobreak\
\lambda 6584/\mathrm{H}\alpha)}$. The O3N2 empirical calibrator has been
proven to be a robust estimator of the metallicity when it is no possible to
have its direct estimation by auroral lines (López-Sánchez & Esteban 2010). In
Sec. 3.5 we study the impact of this oxygen abundance calibrator by
contrasting our measurements using the above calibrator with the one presented
by Pettini & Pagel (2004).

##  3 Results

###  3.1 BPT diagram

We plot in Fig. 2 for each aperture and scale described in Sec. 2.3 the
classical diagnostic diagram using the line ratios
$\log{([{O\textsc{iii}}]\leavevmode\nobreak\ \lambda 5007/\mathrm{H}\beta)}$
vs $\log{([{N\textsc{ii}}]\leavevmode\nobreak\ \lambda
5755/\mathrm{H}\alpha)}$ (Baldwin et al. 1981, BPT diagram hereafter) in order
to determine the fraction of star-forming galaxies in each of the samples for
a given aperture size. We also included the demarcation line described by
Kewley et al. (2001). Star-forming objects lie below this line, while AGN-
powered sources are mostly located above it. On both size scales, the trends
in each aperture are similar. For the central apertures (see left panels of
Fig. 2) in both samples, a large number of galaxies are spread over the
righthand side of the BPT diagram, from the star-forming to the AGN zone.
However, some interacting objects lie in the so-called left branch (i.e.,
$\log{(\mathrm{[{N\textsc{ii}}]}\lambda 6583)/\mathrm{H}\alpha})$ $\lesssim$
\- 0.6), associated with star-forming galaxies. In the extended apertures
(right panels of Fig. 2), a larger percentage of galaxies lie in the star-
forming zone, indicating that the integrated flux includes a larger number of
H ii regions than in the central aperture.

We note that for both aperture sizes in these BPT diagrams, there is a non-
negligible number of interacting galaxies located in the left branch, whereas
none of the control sample galaxies are located in this zone. As explained in
Sánchez et al. (2014), objects located in this branch own a high percentage of
young stellar population. For the central aperture, these galaxies are
included in pairs or interacting systems (10 objects on both aperture scales).
This also holds for the extended aperture (13 and 12 objects for the 30 arcsec
and 2.5 effective radius apertures, respectively). Since these galaxies are
expected to have a significant percentage of young stellar population, these
results suggest an increment in the SFR in interacting galaxies with respect
to the control sample, particularly in binary systems. In the following
section, we study the impact on the change in the sSFR by the
interaction/merger across the galaxies by means of the spatially resolved
EW(H$\alpha$).

Figure 2: BPT diagnostic diagrams for the control (blue points) and
interacting (red points) samples measured within a central (left panels) and
extended (right panels) apertures centered in the optical nucleus. Fluxes in
top panels are derived using apertures on an arcsec scale, while fluxes in the
bottom panel are obtained using an effective radius scale. The solid lines in
each panel represent the division between star-forming and non-star-forming
galaxies presented in Kewley et al. (2001). The typical uncertainty is plotted
at the top of each panel.

###  3.2 Central and extended EW(H$\alpha$)

Figure 3:  Distributions of the integrated EW(H$\alpha$) for the interacting
(red) and control (blue) samples using an aperture size of 5 arcsec. Top and
bottom panels show the distributions of the star and non-star-forming
galaxies, respectively. Left and right panels show the EW(H$\alpha$)
distributions measured using the 5 (EWcentral) and 30 (EWextended) arcsec
apertures, respectively. For this classification we used the integrated
emission line fluxes ratios presented in Sec. 2 using the same selecting
aperture size.

Once we distinguished between star and non-star forming galaxies for each
aperture size in both the control and interacting samples, we explore how the
EW(H$\alpha$) changes on the different scales of these galaxies. The subsample
of star-forming galaxies is selected in both samples following the criteria
used by Sánchez et al. (2014): objects with line ratios below the Kewley
demarcation line in the BPT diagnostic diagram in Fig. 2 and EW(H$\alpha$)
larger than 6 Å. Our spatially resolved data allowed us to study the
distribution of the EW(H$\alpha$) at different aperture sizes in galaxies
classified as star-forming and non-star-forming galaxies depending on the
ionized gas fluxes in each aperture. From Fig. 2 we note that non-star-forming
sample includes mostly AGN-like objects, suggesting that the fraction of
objects with a LINER-like spectrum is negligible.

In Fig. 3 we plot the $\log$(EW(H$\alpha$)) distributions of star-forming and
non-star-forming galaxies for both samples at the 5 and 30 arcsec apertures
(EWcentral and EWextended, respectively) for galaxies classified as star-
forming and non-star-forming galaxies in the 5 arcsec aperture (see Sec. 2).
In Fig. 4 we plot the same distributions using the integrated fluxes within
the 30 arcsec aperture as classification. We repeat the same exercise using
the 0.3 and 2.5 Reff aperture sizes. (see Figs. 5 and 6). We note that the
EW(H$\alpha$) distributions in both samples using either the arcsec or
effective radii scales are similar for the central and extended aperture
sizes, respectively. To make a reasonable comparison with previous results
using single-fiber spectroscopic, we focus our analysis in the EW(H$\alpha$)
derived from the arcsec apertures.

Figure 4:  Distributions of the integrated EW(H$\alpha$) using an aperture
size of 30 arcsec. As in Fig. 3 blue and red histograms represent control and
interacting EW(H$\alpha$) distributions, respectively. Top and bottom panels
show the distributions for star-forming and non-star-forming galaxies,
respectively.

Although the fraction of galaxies selected in the central aperture as star
forming is similar for the control and interacting samples (33 and 35 objects,
respectively), when we compare their EWcentral distributions, we find that a
significant fraction of interacting galaxies (10/35) present higher values
than does the entire control sample (see top left panel of Fig. 3). Most of
these objects are either in close pairs or in binary systems with evident
signatures of interaction (33/35). A majority of these interacting galaxies
are late types (28/35). We also find clear statistical differences between
these two samples. The median $\log$(EWcentral) of the star-forming
interacting subsample is larger than the median of the control sample ([1.41
$\pm$ 0.07] $\log$(Å) and [1.09 $\pm$ 0.03] $\log$(Å), respectively) 222Errors
in the medians and standard deviations are obtained from a bootstrapping
method.. These interacting galaxies cover a wide range of logEW(H$\alpha$) in
comparison to the control sample (standard deviations of [0.38 $\pm$ 0.07]
$\log$(Å) and [0.39 $\pm$ 0.07] $\log$(Å), respectively). Moreover, a
Kolmogorov-Smirnoff test (KS-test, hereafter) reveals that these two samples
are not likely to be drawn from the same parent sample ($p_{KS}$ = 0.001). We
transform the EW(H$\alpha$) to sSFR by means of the empirical relation
presented by Sánchez et al. (2013). For the interacting star-forming galaxies,
the median sSFR is (2.3 $\pm$ 0.2) $\times$ 10-10 yr-1, while the median sSFR
for the control subsample is approximately half the interacting value ([9.3
$\pm$ 0.9] $\times$ 10-11 yr-1).

The distributions of EWextended for galaxies selected as star forming in the
central aperture are fairly similar (see top right panel of Fig. 3), and
median values are similar in both samples ([1.07 $\pm$ 0.01] $\log$(Å) and
[1.18 $\pm$ 0.02] $\log$(Å), respectively). The moderate sSFR enhancement we
observe in central regions of interacting galaxies ($\sim$ 2.5 times) has been
reported by previous statistical studies (e.g., Kewley et al. 2006; Ellison et
al. 2008; Knapen & James 2009; Patton et al. 2013). However, we point out that
those studies covered a portion that was larger than the central region. In
fact, their aperture sizes are similar to our extended aperture where we find
a moderate reduction of the sSFR compared to isolated galaxies ($\sim$ 0.74).

Figure 5:  Distributions of integrated EW(H$\alpha$) for the interacting (red)
and control (blue) galaxies. The distribution of the panels is similar to Fig.
3. For these histograms we use an aperture size of 0.3 Reff. Figure 6:
Distributions of integrated EW(H$\alpha$) for the interacting (red) and
control (blue) galaxies using an aperture size of 2.5 Reff. The distribution
of the panels is similar to Fig. 5.

In comparison to the star-forming galaxies, the non-star-forming galaxies
selected by the central aperture in both samples present a rather similar
distribution toward low EWcentral values (see bottom left panel of Fig. 3). We
would like to point out here that these subsamples include objects located in
the AGN zone in the BPT diagram or those with EW(H$\alpha$) smaller than 6Å.
Although it is beyond the scope of this study, the similarity between these
distributions deserve more attention so we can understand the impact of the
interaction in triggering the nuclear activity of galaxies. We find however, a
clear difference between the distributions of EWextended for the same sample
of galaxies (see bottom right panel of Fig. 3). The median EWextended of the
interacting sample is four times smaller than the control one ([0.20 $\pm$
0.08] $\log$(Å) and [0.82 $\pm$ 0.05] $\log$(Å), respectively).

The control star-forming galaxies selected using the extended aperture almost
doubles the interacting ones (see top left panel of Fig. 4). The median
$\log$(EWcentral) for the interacting subsample is almost three times larger
than the median of the control sample ([1.41 $\pm$ 0.1]$\log$(Å) and [0.99
$\pm$ 0.03] $\log$(Å), respectively). For the same subsample of star-forming
galaxies, EWextended is similar for the interacting and control samples ([1.11
$\pm$ 0.02] $\log$(Å), see top right panel in Fig. 4). A KS-test reveals that
these two samples could be drawn from the same parent sample ($p_{KS}$ = 0.3).
This suggests that the net enhancement of the sSFR occurs mainly in the
central region of the interacting galaxies rather than in the outer regions.

In the extended aperture, the selection of non-star-forming galaxies yields
almost three times more interacting objects than control ones. The
distribution, as well as the median of EWcentral, is similar for both samples
([0.18 $\pm$ 0.07] $\log$(Å), see bottom left panel in Fig. 4). On the other
hand, EWextended present significant differences between the interacting and
control samples (see bottom right panel in Fig. 4). The median EWextended for
this interacting subsample is three times smaller than the control one ([0.17
$\pm$ 0.06] $\log$(Å) and [0.64 $\pm$ 0.03] $\log$(Å), respectively). In fact,
a KS-test indicates that these two distributions are not likely to be drawn
from the same parent sample ($p_{KS}$ = 0.001).

Our analysis shows that regardless of the criteria we use to select star-
forming galaxies, the interacting sample has a consistent moderate enhancement
in the central sSFR when compared with isolated star-forming objects. On
extended scales, both samples present similar distributions of EWextended and,
depending on the aperture used to classify the star-forming galaxies, similar
or moderately suppressed total sSFR. Most of these interacting objects are
late-type galaxies in pairs or merging systems. These results suggest that
moderate enhancement ($\sim$ 2-3 times larger) in the sSFR only occurs in the
central region of interacting galaxies. This scenario is consistent with gas
been funneled to the central region of galaxies owing to the interaction:
large amounts of gas (subsequently enhanced sSFR) is found in the central
region of interacting galaxies, whereas the integrated sSFR remains similar or
moderately suppressed. Our spatially resolved study agrees with the numerical
simulations presented by Moreno et al. (2015). They find that the increment of
star formation in merging galaxies is observed within the central kpc, while
in outer galacto-centric radii, the activity is moderately suppressed. Our
results also agree with studies of supernovae radial distributions (e.g.,
Habergham et al. 2012; Herrero-Illana et al. 2012) that find Type-Ibc
supernovae, those more correlated to the ongoing star formation (Galbany et
al. 2014), are more centrally concentrated in disturbed/interacting galaxies.

In galaxies considered as non-star-forming, the central EW(H$\alpha$)
distribution is similar between interacting and isolated objects, whereas the
extended EW(H$\alpha$) is systematically smaller for the interacting sample.
This points out that the process responsible for the observed central
EW(H$\alpha$) in non-star-forming galaxies for both samples could be similar.
From the BPT diagrams (see Fig. 2), this process could involve only AGN
activity. On the other hand, low values of the extended EW(H$\alpha$) for
interacting galaxies could imply either a low budget of gas available to be
ionized or a weak radiation field across the merging galaxies. Since these
galaxies are the complement to the star-forming subsample, they cover a wide
range of interaction stages and morphological types. A further division of the
non-star-forming galaxies EW(H$\alpha$) in the above properties led a few
objects in each bin, making it difficult to derive reliable results. We
require a large sample of merging galaxies in particular in the post-merger
and remnant stages to derive statistical meaningful conclusions about the
mechanisms responsible for the observed trends in the central and extended
EW(H$\alpha$) in non-star-forming merging galaxies.

###  3.3 Central oxygen abundances

Figure 7:  _Left:_ Distributions of $\Delta$O/H in the central (5 arcsec)
aperture for the interacting (red) and the control (blue) star-forming
galaxies, see text for details. _Right:_ Distributions of $\Delta$O/H using a
central aperture of 0.3 Reff.

Observational studies suggest that the enhancement in the star formation
activity in the central region of interacting galaxies is connected with a
dilution of the oxygen abundance (e.g., Kewley et al. 2006; Ellison et al.
2008; Sánchez Almeida et al. 2014a, b), which in turns contributes to the
scatter of the M-Z relation. This decrement is associated with the supply of
metal-poor gas to the central region via inflows. To test this scenario, we
studied the scatter between the observed metallicity and the M-Z relation for
a given stellar mass in star-forming galaxies. From the emission line fluxes,
we derived the oxygen abundance of each galaxy classified in Sec. 3.2 as star-
forming in the central aperture for both the interacting and control samples.
Then, we provided the difference (or scatter) between the abundance determined
from the flux ratios and the one expected from the M-Z relation ($\Delta$O/H)
derived by Sánchez et al. (2013). For the objects included in the CALIFA
survey, we used the stellar masses presented by Walcher et al. (2014). For the
companions not included in the survey, stellar masses were derived in a
similar fashion to the CALIFA galaxies. As explained in Sánchez et al. (2013),
this empirical M-Z relation is derived for metallicities at one effective
radius. Nevertheless, we can transform this abundance at different radii, in
particular to the central aperture radius, by means of the metallicity
gradient in disk galaxies (Sánchez et al. 2014).

In Fig. 7 we plot the distributions of $\Delta$O/H for both the interacting
and control samples in the central aperture (5 arcsec and 0.3 Reff, left and
right histograms, respectively). The distribution for the control sample in
the 5 arcsec aperture is centered well on zero, with a median value of (0.001
$\pm$ 0.006) dex and a rather narrow distribution
($\sigma\Delta\mathrm{O/H}_{\mathrm{control}}$ = 0.056 $\pm$ 0.006 dex). On
the other hand, the median of the distribution from the interacting sample is
slightly larger than the one from the control sample (0.03 $\pm$ 0.01 dex).
However, the interacting sample has a wider range of values in comparison with
the control sample ($\sigma\Delta\mathrm{O/H}_{\mathrm{merger}}$ = 0.10 $\pm$
0.01 dex). A KS-test indicates that these two samples are likely to be drawn
from the same parent sample distribution ($p_{KS}$ = 0.32). We find a similar
distribution for the 0.3 Reff aperture with median values of (-0.001 $\pm$
0.006) dex and (0.021 $\pm$ 0.02) dex for the control and interacting samples,
respectively. The interacting sample is slightly more metal rich than the
control sample (0.02 $\pm$ 0.02 dex). This indicates that in central regions,
star-forming merging galaxies have similar oxygen abundance to the control
sample. Even though both apertures provide similar results, the most reliable
one comes from the 0.3 Reff aperture size since it covers a similar physical
region in all the galaxies in both samples. This first IFS census suggests
that even though there is an enhancement of the sSFR in the central region of
interacting galaxies, the oxygen abundance remains similar to the one found in
isolated galaxies. In other words, the scatter observed in the M-Z relation
does not seem to be linked to the star formation rate of the galaxies
presented in this study.

Our results differ from the single-fiber spectroscopic studies carried out
with the SDSS galaxy-pair sample (Ellison et al. 2008). They found a lower
oxygen abundance of $\sim$ 0.05 - 0.1 dex between their galaxy-pair samples
and control sample. One evident reason for the disparity between these two
studies could be attributed to the number of objects in each sample. SDSS
pairs and control samples included 1716 galaxies in binary systems and 40095
galaxies, respectively, whereas our samples of star-forming galaxies include
33 and 35 objects in both interacting and control samples, respectively.
Despite this difference in the size of the samples, we are able to account for
the enhancement in the central SFR of interacting galaxies (see Figs. 3 and
5), in agreement with the SDSS studies, but not for the dilution in central
metallicities. We note that our reported small variations in the metallicity
in the central aperture may be biased by aperture effects or even the
calibration used to derived the metallicity. In the following two sections, we
explore the possible bias in our results for these two factors.

Figure 8:  Differences in the median values of $\Delta$O/H between the
interacting and control samples at different aperture sizes. _Left:_ The
aperture sizes are measured in arcsecs. _Right:_ Aperture scales are measured
in effective radius. The dashed line represents the difference reported by
Ellison et al. (2008). Errors bars are determined using bootstrapping in both
samples. On any of the scales, the differences reach the values found in
single-fiber spectrocopic studies.

###  3.4 Metallicity as function of the aperture size

Our IFS data allows exploring the effect of measuring the gas metallicity for
different aperture sizes and scales. In particular, we can study whether the
lower abundances presented in single-fiber studies for the star-forming
interacting galaxies (e.g., Ellison et al. 2008) could be caused by aperture
effects. More important, we will have an estimation of how the metallicity
changes at different galactic scales. In Fig. 8 we plot the differences in the
median metallicity value for the interacting and control star-forming galaxies
at different aperture sizes. We plot these differences for two aperture scales
in arcsecs and in effective radius. The sample of galaxies selected for these
plots are those classified as star-forming galaxies in the central aperture of
each scale.

For the aperture scale in arcsecs, we observe that the difference in
metallicities between the two samples decreases as the aperture size
increases, reaching a plateau at $\sim$ 15 arcsec. After this size the
differences in metallicity are rather constant for different aperture sizes
($\sim$ -0.01 dex). Using the effective radius of each galaxy as aperture
scale, the difference in metallicity for the two samples decreases as the size
of the aperture increases. For the largest aperture (2.5 Reff), the
interacting galaxies shows a lower metallicity of $\sim$ 0.02 dex with respect
to control galaxies. Although there is a decrement in the metallicity of
merging galaxies for large apertures, we do not observe the difference
presented by previous spectroscopic studies (e.g., Kewley et al. 2006; Ellison
et al. 2008). Even more in the physical motivated aperture (Reff), we find
rather similar metallicities in the central regions with hints of a dilution
of metallicities of the interacting galaxies on larger scales. This suggests
that despite the inflows of ionized gas induced by the interaction, the
metallicity in the central regions of interacting galaxies presents similar
properties to those for isolated galaxies. On large scales, there seems to be
a dilution in the metallicity of interacting objects.

###  3.5 Metallicity as function of the abundance calibrator

In general, the variations in metallicity between the control and interacting
galaxies are not larger than 0.1 dex. This regime of small variations can be
biased by several factors. In this section we explore and quantify the impact
of these differences by the abundance calibrator. In Fig. 9 we plot the
differences as a function of aperture sizes using the improved empirical
calibration for the O3N2 indicator given by Marino et al. (2013). We overplot
these differences using a different calibration provided by Pettini & Pagel
(2004). As we note above, the differences between the interacting and control
sample are very small when using the improved calibrator, flattening out at
$\sim$ 15 arcsecs to $\sim$ -0.01 dex. However, when we use the calibrator
from Pettini & Pagel (2004), we find that in larger apertures, the interacting
galaxies have lower metallicities than control galaxies. Even more at $\sim$
20 arcsec the differences in metallicity reach the value found by Ellison et
al. (2008).

To explain this apparent difference between our results and those using
another calibrator, we note that our sample is closer than the sample
presented by Ellison et al. (2008). At the median redshift of the SDSS-pair
sample ($z\sim$ 0.06, see their Fig.2), an aperture of 3 arcsec is equivalent
to central regions of $\sim$ 3.5 kpc. On the other hand, an aperture of the 5
arcsec used to define the central region in this study covers a central
portion of $\sim$ 1 kpc at the median redshift of our sample ($z\sim$ 0.01).
As a consequence, the SDSS-pair single-fiber observations cover a wider region
than the area covered by our central aperture. In fact, at the 20 arcsec
aperture where the differences in metallicity (using the calibrator from
Pettini & Pagel (2004)) are similar to those found by Ellison et al. (2008),
this aperture covers a region of $\sim$ 3.5 kpc at the median redshift of our
sample. Although we did not use the same indicators for metallicity as for the
single-fiber spectroscopic survey studies, we suggest that by using abundance
calibrators presented in the literature, it is possible to obtain the same
lower metallicity in interacting galaxies.

Figure 9: Similar to Fig. 8. Differences in the median values of $\Delta$O/H
between the interacting and control samples at different aperture sizes. In
this case we compare using apertures in arcsec units with the differences in
metallicity using different calibrators. Blue circles represent the
differences obtained from the O3N2 revisited calibrator used in this study
given in Marino et al. (2013). Red diamonds show the difference obtained from
the calibrator presented by Pettini & Pagel (2004). The dashed line represent
the difference reported by Ellison et al. (2008).

Finally we want to highlight that regardless of the indicator used to derive
the oxygen abundance, the metallicity in the central regions for interacting
galaxies is similar to the one derived for the control sample.

##  4 Conclusions

We used the spatially resolved information provided by the CALIFA survey to
carry out the first statistical study of the impact of the merger event on the
sSFR and the oxygen abundance on different galactic scales for a sample over
100 galaxies at different stages of interaction. Moreover, this survey allows
us to homogeneously determine the same properties in a control sample of 80
non-interacting galaxies. We separated the galaxies in both samples between
star-forming and non-star-forming galaxies (see Secs. 3.1 and 3.2). For the
first subsample, we find a (moderate) enhancement in the sSFR in the central
region of interacting galaxies. However, in outer regions, the sSFR is similar
to or moderately suppressed in comparison to the control sample (see Sec.
3.2). This agrees with previous observational studies (e.g., Ellison et al.
2008; Yuan et al. 2012), as well as with numerical simulations (e.g., Hopkins
et al. 2013; Moreno et al. 2015). These studies indicate that tidally induced
star formation becomes evident in the central region of the galaxies as a
consequence of gas inflows. In this scenario, the new supply of metal-poor gas
to the central region produces a dilute metallicity. In contrast to this
picture, we find similar metallicities in the central region of star-forming,
interacting galaxies to those derived for isolated galaxies (see Sec. 3.3).
When we consider larger apertures (in effective radius units), we find hints
of dilute metallicities in the interacting galaxies (see Sec. 3.4). Our
results support the notion of a tight interplay between different physical
processes in the central part of interacting galaxies. Although metal-poor gas
inflows can be considered as the main process that affects the chemical
evolution toward the center of interacting galaxies, there are some other
processes to be taken into account that could enrich the ionized gas, such as
stellar (or AGN) feedback or returned material into the ISM. The results
presented here encourage IFS studies in larger samples of interacting galaxies
in order to understand the evolution of the galactic chemical content and to
quantify how different merging configurations can affect the merger-induced
metallicity dilution.

## Acknowledgments

The authors thank the referee for the useful comments and suggestions. This
study made use of the data provided by the Calar Alto Legacy Field Area
(CALIFA) survey (http://www.califa.caha.es). It was based on observations
collected at the Centro Astronómico Hispano Alemán (CAHA) at Calar Alto,
operated jointly by the Max-Planck-Institut für Astronomie and the Instituto
de Astrofísica de Andalucia (CSIC). CALIFA is the first legacy survey
performed at the Calar Alto. The CALIFA collaboration would like to thank the
IAA-CSIC and MPIA-MPG as major partners of the observatory, and CAHA itself,
for the unique access to the telescope time and support in manpower and
infrastructures. The CALIFA collaboration also thanks the CAHA staff for their
dedication to this project. J.B-B. and B.G-L acknowledge support from the Plan
Nacional de I+D+i (PNAYA) funding programs (AYA-2012-39408-C02-1 and
AYA-2013-41656-P) of the Spanish Ministry of Economy and Competitiveness
(MINECO). J.F.B. acknowledges support from the Plan Nacional de I+D+i (PNAYA)
funding programs from MINECO (AYA2013-48226-03-1-P, RAVET). J.I.P.
acknowledges financial support from the Spanish MINECO through grant
AYA2010-21887-C04-01 and from the Junta de Andalucía Excellence Project
PEX2011-FQM7058. R.A.M is funded by the Spanish program of International
Campus of Excellence Moncloa (CEI). Support for L.G. is provided by the
Ministry of Economy, Development, and Tourism’s Millennium Science Initiative
through grant IC120009, awarded to The Millennium Institute of Astrophysics,
MAS. L.G. acknowledges support by CONICYT through FONDECYT grant 3140566.
C.J.W. acknowledges support through the Marie Curie Career Integration Grant
303912.

## References

  * Baldwin et al. (1981) Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5
  * Barnes & Hernquist (1996) Barnes, J. E. & Hernquist, L. 1996, ApJ, 471, 115
  * Barrera-Ballesteros et al. (2014) Barrera-Ballesteros, J. K., Falcón-Barroso, J., García-Lorenzo, B., et al. 2014, A&A, 568, A70
  * Borne et al. (1999) Borne, K. D., Bushouse, H., Colina, L., et al. 1999, Ap&SS, 266, 137
  * Casteels et al. (2014) Casteels, K. R. V., Conselice, C. J., Bamford, S. P., et al. 2014, MNRAS, 445, 1157
  * Cox et al. (2006) Cox, T. J., Jonsson, P., Primack, J. R., & Somerville, R. S. 2006, MNRAS, 373, 1013
  * Di Matteo et al. (2008) Di Matteo, P., Bournaud, F., Martig, M., et al. 2008, A&A, 492, 31
  * Ellison et al. (2013a) Ellison, S. L., Mendel, J. T., Patton, D. R., & Scudder, J. M. 2013a, MNRAS, 435, 3627
  * Ellison et al. (2013b) Ellison, S. L., Mendel, J. T., Scudder, J. M., Patton, D. R., & Palmer, M. J. D. 2013b, MNRAS, 430, 3128
  * Ellison et al. (2008) Ellison, S. L., Patton, D. R., Simard, L., & McConnachie, A. W. 2008, AJ, 135, 1877
  * Galbany et al. (2014) Galbany, L., Stanishev, V., Mourão, A. M., et al. 2014, A&A, 572, A38
  * García-Benito et al. (2014) García-Benito, R., Zibetti, S., Sánchez, S. F., et al. 2014, ArXiv e-prints
  * Habergham et al. (2012) Habergham, S. M., James, P. A., & Anderson, J. P. 2012, MNRAS, 424, 2841
  * Herrero-Illana et al. (2012) Herrero-Illana, R., Pérez-Torres, M. Á., & Alberdi, A. 2012, A&A, 540, L5
  * Hopkins et al. (2013) Hopkins, P. F., Cox, T. J., Hernquist, L., et al. 2013, MNRAS, 430, 1901
  * Husemann et al. (2013) Husemann, B., Jahnke, K., Sánchez, S. F., et al. 2013, A&A, 549, A87
  * Kewley et al. (2001) Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, ApJ, 556, 121
  * Kewley et al. (2006) Kewley, L. J., Geller, M. J., & Barton, E. J. 2006, AJ, 131, 2004
  * Knapen & James (2009) Knapen, J. H. & James, P. A. 2009, ApJ, 698, 1437
  * López-Sánchez & Esteban (2010) López-Sánchez, Á. R. & Esteban, C. 2010, A&A, 517, A85
  * Marino et al. (2013) Marino, R. A., Rosales-Ortega, F. F., Sánchez, S. F., et al. 2013, A&A, 559, A114
  * Mihos & Hernquist (1996) Mihos, J. C. & Hernquist, L. 1996, ApJ, 464, 641
  * Moreno et al. (2015) Moreno, J., Torrey, P., Ellison, S. L., et al. 2015, MNRAS, 448, 1107
  * Patton et al. (2013) Patton, D. R., Torrey, P., Ellison, S. L., Mendel, J. T., & Scudder, J. M. 2013, MNRAS, 433, L59
  * Pettini & Pagel (2004) Pettini, M. & Pagel, B. E. J. 2004, MNRAS, 348, L59
  * Robotham et al. (2014) Robotham, A. S. G., Driver, S. P., Davies, L. J. M., et al. 2014, MNRAS, 444, 3986
  * Roth et al. (2005) Roth, M. M., Kelz, A., Fechner, T., et al. 2005, PASP, 117, 620
  * Sánchez et al. (2006) Sánchez, S. F., García-Lorenzo, B., Jahnke, K., et al. 2006, Astronomische Nachrichten, 327, 167
  * Sánchez et al. (2012) Sánchez, S. F., Kennicutt, R. C., Gil de Paz, A., et al. 2012, åp, 538, A8
  * Sánchez et al. (2014) Sánchez, S. F., Rosales-Ortega, F. F., Iglesias-Páramo, J., et al. 2014, A&A, 563, A49
  * Sánchez et al. (2013) Sánchez, S. F., Rosales-Ortega, F. F., Jungwiert, B., et al. 2013, A&A, 554, A58
  * Sánchez et al. (2011) Sánchez, S. F., Rosales-Ortega, F. F., Kennicutt, R. C., et al. 2011, MNRAS, 410, 313
  * Sánchez Almeida et al. (2014a) Sánchez Almeida, J., Elmegreen, B. G., Muñoz-Tuñón, C., & Elmegreen, D. M. 2014a, A&A Rev., 22, 71
  * Sánchez Almeida et al. (2014b) Sánchez Almeida, J., Morales-Luis, A. B., Muñoz-Tuñón, C., et al. 2014b, ApJ, 783, 45
  * Sanders & Mirabel (1996) Sanders, D. B. & Mirabel, I. F. 1996, ARA&A, 34, 749
  * Scudder et al. (2012) Scudder, J. M., Ellison, S. L., Torrey, P., Patton, D. R., & Mendel, J. T. 2012, MNRAS, 426, 549
  * Torrey et al. (2012) Torrey, P., Cox, T. J., Kewley, L., & Hernquist, L. 2012, ApJ, 746, 108
  * Walcher et al. (2014) Walcher, C. J., Wisotzki, L., Bekeraité, S., et al. 2014, A&A, 569, A1
  * Wild et al. (2014) Wild, V., Rosales-Ortega, F., Falcón-Barroso, J., et al. 2014, A&A, 567, A132
  * Yuan et al. (2012) Yuan, F.-T., Takeuchi, T. T., Matsuoka, Y., et al. 2012, A&A, 548, A117