Water Masers in the Andromeda Galaxy: II. Where Do Masers Arise?
We present a comparative multi-wavelength analysis of water maser-emitting regions and non-maser-emitting luminous 24 m star-forming regions in the Andromeda Galaxy (M31) to identify the sites most likely to produce luminous water masers useful for astrometry and proper motion studies. Included in the analysis are Spitzer 24 m photometry, Herschel 70 and 160 m photometry, H emission, dust temperature, and star formation rate. We find significant differences between the maser-emitting and non-maser-emitting regions: water maser-emitting regions tend to be more IR-luminous and show higher star formation rates. The five water masers in M31 are consistent with being analogs of water masers in Galactic star-forming regions and represent the high-luminosity tail of a larger (and as yet undetected) population. Most regions likely to produce water masers bright enough for proper motion measurements using current facilities have already been surveyed, but we suggest three ways to detect additional water masers in M31: (1) Re-observe the most luminous mid- or far-IR sources with higher sensitivity than was used in the Green Bank Telescope survey; (2) Observe early-stage star-forming regions selected by mm continuum that have not already been selected by their 24 m emission, and (3) Re-observe the most luminous mid- or far-IR sources, and rely on maser variability for new detections.
[11affiliationmark: ]Current address: Jet Propulsion Laboratory, M/S 238-600, 4800 Oak Grove Dr., Pasadena, CA 91109, USA;
Water masers can arise in star-forming regions, in shocks, in stellar atmospheres, and in the vicinity of massive black holes (see reviews by Reid & Moran, 1981; Elitzur, 1992; Lo, 2005). They can indicate specific physical conditions and provide high brightness temperature sources for precise astrometry and proper motion studies (see review by Reid & Honma, 2014). While water masers’ presence and intensity cannot be predicted based on observed conditions in any given physical setting (mostly due to nonlinear amplification of small-scale conditions and anisotropic emission), there is good observational evidence indicating where water masers are most likely to be observed. In the Galaxy, for example, the water maser detection rate toward (ultra)compact H ii regions is typically 50% or higher (e.g., Churchwell et al., 1990; Urquhart et al., 2011).
The utility of water masers for extragalactic proper motion studies has been demonstrated in the Local Group and in water maser disks associated with massive black holes (e.g., Brunthaler et al., 2005; Humphreys et al., 2013). In the Local Group, the masers are associated with star formation and can be used to measure systemic proper motions and proper rotation (also known as “rotational parallax”). This has been done for M33 and IC 10 (Brunthaler et al., 2005, 2007), but detected water masers were notably absent from the Andromeda Galaxy (M31) until recently (Sullivan, 1973; Greenhill et al., 1995; Imai et al., 2001; Darling, 2011). The proper motion of M31 is a key quantity for Local Group dynamics (e.g., Loeb et al., 2005), and while Sohn et al. (2012) and van der Marel et al. (2012) obtained a constraint on the tangential velocity M31 of km s () using the Hubble Space Telescope, suggesting a nearly radial Milky Way-Andromeda trajectory, a second completely independent and possibly more precise measurement is worthwhile (Darling, 2011; Darling et al., 2016).
Water masers in M31 have been difficult to find, in large part due to the low distance-dimmed flux density and due to the large areal size of the molecular disk: the disk is too large in angular size and the masers are too faint to simply map the entire disk in a reasonable amount of observing time using current facilities. A Green Bank Telescope (GBT) 111The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. survey of 506 22 m-selected regions detected only five water masers (Darling et al., 2016). The selection method is inefficient, and the survey is barely sensitive enough to detect the most luminous Galactic analog water masers associated with star formation. Given what we know about the star-forming regions in M31 in a pan-spectral sense, we can (1) learn more about how and where luminous water masers arise, and (2) apply this knowledge to identify additional likely sites of water maser emission in M31, improving detection statistics and making future surveys more efficient. Water masers can show significant peculiar motion and variability, so the detection of additional water masers would substantially improve proper motion and rotation measurements of M31 and reduce systematic effects. An enhanced astrometric network of water masers could enable the detection of the apparent expansion of — and thus the measurement of a geometric distance to — M31 as it approaches the observer at 300 km s (Darling, 2011, 2013).
In this paper, we present a comparative multi-wavelength analysis of 22 GHz water maser-emitting and non-maser-emitting 24 m-luminous star-forming regions in M31. We use WISE, Spitzer, and Herschel222Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA. infrared continuum maps, maps of derived quantities such as star formation and dust temperature, and archival catalogs to examine the differences between maser-emitting and non-maser-emitting regions, to examine correlations between observable quantities among each population, and to constrain the parameter space most likely to produce detectable water masers. Section 2 summarizes the GBT survey presented in detail in Darling et al. (2016), Section 3 describes data sources and new measurements, Section 4 refines the sample used in the analysis, Section 5 presents the results of the measurements and data collation, Section 6 examines trends and differences among the masers and non-masing regions, and Section 7 discusses the best approach to identifying new water masers in M31. Section 8 highlights the main findings of this study.
Throughout the manuscript, we assume a distance to M31 of 780 kpc when calculating luminosities from continuum or line flux measurements.
2 The Green Bank Water Maser Survey of M31
The water maser candidate selection for the Green Bank Telescope (GBT) survey for water masers in M31, the observing methods, data reduction, and results are presented in Darling (2011) and Darling et al. (2016). In summary, we selected bright point sources from the Spitzer 24 m map of M31 (Gordon et al., 2006), and constructed a catalog of 506 objects from the brightest down to a point where most of the 24 m emission becomes extended at about 4 MJy sr (Figure 1, top). The compact 24 m sources in M31 are likely associated with star-forming regions; strong water masers are known to arise in H ii regions in the Galaxy (e.g. Walker et al., 1982), and HO maser luminosity correlates with far-infrared (FIR) luminosity in Galactic star-forming regions as well as in star-forming galaxies (Felli et al., 1992; Castangia et al., 2008).
We observed the 6 22.23508 GHz ortho-water maser line toward the 506 24 m-selected regions in late 2010, late 2011, and early 2012 (Darling, 2011; Darling et al., 2016). Spectra were smoothed to 3.3 km s channels, reaching an rms noise of 3 mJy in individual spectra and 0.17 mJy in a spectral mean stack of 299 objects aligned to the CO velocity (Nieten et al., 2006). Five water masers were detected (Darling, 2011), and the detection rate after removing planetary nebulae and giant stars from the sample was 1.1(0.5)% (see Section 4.1 and Darling et al., 2016). The full details of the results of water maser observations, including the results of NH (1,1), NH (2,2), and H66 observations, are presented in Darling et al. (2016). In this paper, we use multi-wavelength data to investigate the physical and observed properties of water maser-emitting regions and to compare them to non-maser-emitting regions to understand where the water masers arise and how to detect additional water masers in M31.
3 Multi-Wavelength Photometry and Derived Properties\floattable
|H||0.9–1.4||Mayall Telescope||Azimlu et al. (2011)|
|3.4 m||6.1||WISE||Wright et al. (2010)|
|22 m||22||WISE||Wright et al. (2010)|
|24 m||6||Spitzer||Gordon et al. (2006)|
|70 m||5.6||Herschel||Groves et al. (2012); B. Altieri (priv. comm.)|
|160 m||11.4||Herschel||Groves et al. (2012); B. Altieri (priv. comm.)|
|T||36||Herschel and Spitzer||Smith et al. (2012)|
|SFR||6||Galex and Spitzer||Ford et al. (2013)|
3.1 Data Sources
Table 1 summarizes the archival data used in the M31 water maser study, split into sources of photometry (H, mid- and far-IR) and derived quantities (dust temperature and star formation rate [SFR]). Figure 1 shows 24 m, 70 m, 160 m, and star formation rate maps of M31, and Figure 2 shows the dust temperature map (Smith et al., 2012). Both figures show the water masers and the non-detection locations.
Spitzer observations of M31 at 24 m were performed using the Multiband Imaging Photometer (MIPS) instrument with Point Spread Function (PSF) of 6″ (Gordon et al., 2006). The map covers an area of approximately 1 oriented along the major axis of M31. The MIPS data analysis tool version 2.9 (Gordon et al., 2005) was used to produce the final mosaic map at 24 m.
We obtained the Herschel maps of M31 at 70 m and 160 m from the public data of the Herschel archive (Pilbratt et al., 2010; Poglitsch et al., 2010). The maps were re-processed by Bruno Altieri (ESA; private communication) with unimap map-maker (Piazzo, 2013). The observations were performed using the Photodetector Array Camera and Spectrometer (PACS) instrument. Full details of the observing strategy can be found in Groves et al. (2012). The maps cover an area of roughly 1. The FWHM angular resolution of the 70 m and 160 m maps is 5.6″ and 11.4″, respectively.
Smith et al. (2012) constructed the dust temperature map of M31 via pixel-by-pixel analysis of Spitzer and Herschel maps in the wavelength range 70–500 m. All of the maps were convolved to the resolution of Herschel 500 m map that has the largest FWHM resolution (36″). The dust temperature for each pixel was measured by fitting a FIR through submillimeter spectral energy distribution with a single-temperature modified blackbody model: , where is the dust absorption coefficient described by a power law with dust emissivity index such that , is the dust mass with dust temperature , is the Planck function, and is the distance to the galaxy. The estimated uncertainty in the dust temperature is 1.4 K. The dust temperature was measured where the fluxes in all six bands (five Herschel and MIPS 70 m) had a signal-to-noise ratio greater than 3.
The total star formation rate map of M31 (dust-obscured and unobscured) was constructed from the GALEX FUV and Spitzer 24 m maps by Ford et al. (2013). The contribution from the giant stellar population at 24 m was removed using the IRAC Spitzer 3.6 m band (see also Section 4.1).
We also used the optically identified H ii region catalog of Azimlu et al. (2011) for this study. Azimlu et al. (2011) used the data from the Nearby Galaxies Survey of Massey et al. (2006), which includes H and R-band mosaics of ten overlapping fields across the disk of M31. Azimlu et al. (2011) identified 3961 H ii regions above a 10 H flux limit of 10 erg cm s.
Finally, we obtained Wide-field Infrared Survey Explorer (WISE) maps of M31 at 3.4 m (Figure 3, top) and 22 m from the NASA/IPAC Infrared Science Archive333http://hachi.ipac.caltech.edu:8080/montage. WISE mapped the sky in four bands at 3.4, 4.6, 12, and 22 m with an angular resolution of 6.1″, 6.4″, 6.5″, and 12.0″, respectively (Wright et al., 2010).
Photometric measurements at 24 m, 70 m, and 160 m were performed using the Aperture Photometry Tool (APT, Laher et al., 2012). The point spread function (PSF) FWHM of the 24 m, 70 m, and 160 m images is 6″, 5.6″, and 11.4″, respectively, and the pixel size is 1.24″, 3.2″, and 6.4″. We select aperture radii of 6.2″, 6.4″, and 6.4″. We chose similar aperture sizes at all wavelengths in order to match physical sizes in the photometry.
We performed aperture photometry on the SFR map using an aperture radius of 6″. The dust temperatures were obtained from the dust temperature map at each 24 m source position (Figure 1). Five regions did not meet the 3 dust temperature threshold (Section 3.1) and were therefore omitted from the analysis sample (Section 4).
|Maser||T||log(SFR)||log(24 m)||log(70 m)||log(160 m)||log(H)||HO||L||log(L)|
|(J2000)||(K)||( yr)||(Jy)||(Jy)||(Jy)||(mW m)||(mJy km s)||(L)||(L)|
Note. – The integrated HO maser flux densities and luminosities were obtained from Darling (2011). Parenthetical values indicate 1 statistical uncertainties. The 1 uncertainties for photometric flux densities and SFR indicate statistical uncertainties for images with high signal to noise ratios, but the systematic uncertainties are likely to be higher.
Due to crowding in the molecular ring, estimation of the local background is difficult. We subtract a local non-annulus sky background using the default “Model F” algorithm in the APT that estimates the sky background using bilinear interpolation of the mode statistic. This model has been suggested for photometry in crowded fields (Laher et al., 2012).
Although re-scaling all maps to the largest resolution of 11.4″ at 160 m would be appropriate to obtain photometry over a uniform physical scale, we chose to perform photometry at the original resolution of the maps. This is due to the fact that the resolution of 24 m, 70 m, and SFR maps are similar and in the range 5.6″–6″. Since the objects are in a crowded field, re-scaling the maps to a larger resolution would lead to (additional) confusion.
We obtained the encircled energy fraction (EEF) for the Herschel images from the PACS Photometer Point-Source Flux Calibration document444http://herschel.esac.esa.int/twiki/pub/Public/ PacsCalibrationWeb/pacs_bolo_fluxcal_report_v1.pdf; the estimated aperture correction factor (1/EEF) for aperture radii of 6.4″ (70 m) and 6.4″ (160 m) corresponds to 1.56 and 2.6, respectively. For the 24 m map, we adopt an aperture correction factor of 1.61 for the 6″ aperture radius555http://irsa.ipac.caltech.edu/data/SPITZER/docs/ mips/mipsinstrumenthandbook/50/.
The uncertainties assigned to the measured photometric flux densities correspond to the standard deviation of the photometric flux of a large number of blank sources in each image. We obtain aperture photometric flux for 50 blank sky locations and measure the standard deviation of the photometric flux of the blank sources; this gives a good measure of the true photometric error of the targets. The estimated 1 uncertainties in the 24 m, 70 m, and 160 m maps correspond to 1.1610, 0.0168, 0.0186 Jy, respectively. The 1 uncertainty for star formation rate corresponds to 1.2 yr. The 1 uncertainties for photometric flux densities and SFR represent statistical uncertainties for images with high signal to noise ratios, and the systematic uncertainties are likely to be higher. Measured flux densities and SFR for the water maser and non-maser sample regions are shown in Table 2 and Table 3, respectively.
The multi-wavelength data used in this work were obtained at different resolutions. While the resolution of the Spitzer and Herschel maps ranges from 5.6″ to 11.4″, the resolution of the dust temperature map is 36″ based on the resolution of Herschel maps at longer wavelengths (e.g., 500 m, Smith et al., 2012). Additionally, the crowded field and the large PSF of Spitzer and Herschel maps (5.6″–11.4″) may introduce contamination from nearby or confused sources (e.g., Calzetti et al., 2005).
|Object||T||log(SFR)||log(24 m)||log(70 m)||log(160 m)||log(H)||log(L)|
|(J2000)||(K)||( yr)||(Jy)||(Jy)||(Jy)||(mW m)||(L)|