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Register a new userAccurate Identification of Galaxy Mergers with Stellar Kinematics
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To determine the importance of merging galaxies to galaxy evolution, it is necessary to design classification tools that can identify different types and stages of merging galaxies. Previously, using GADGET-3/SUNRISE simulations of merging galaxies and linear discriminant analysis (LDA), we created an accurate merging galaxy classifier from imaging predictors. Here, we develop a complementary tool based on stellar kinematic predictors derived from the same simulation suite. We design mock stellar velocity and velocity dispersion maps to mimic the specifications of the Mapping Nearby Galaxies at Apache Point (MaNGA) integral field spectroscopy (IFS) survey and utilize an LDA to create a classification based on a linear combination of 11 kinematic predictors. The classification varies significantly with mass ratio; the major (minor) merger classifications have a mean statistical accuracy of 80% (70%), a precision of 90% (85%), and a recall of 75% (60%). The major mergers are best identified by predictors that trace global kinematic features, while the minor mergers rely on local features that trace a secondary stellar component. While the kinematic classification is less accurate than the imaging classification, the kinematic predictors are better at identifying post-coalescence mergers. A combined imaging + kinematic classification has the potential to reveal more complete merger samples from imaging and IFS surveys like MaNGA. We note that since the suite of simulations used to train the classifier covers a limited range of galaxy properties (i.e., the galaxies are intermediate mass and disk-dominated), the results may not be applicable to all MaNGA galaxies.
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We develop, implement and characterise an enhanced data reduction approach which delivers precise, accurate, radial velocities from moderate resolution spectroscopy with the fibre-fed VLT/FLAMES+GIRAFFE facility. This facility, with appropriate care, delivers radial velocities adequate to resolve the intrinsic velocity dispersions of the very faint dSph dwarf galaxies. Importantly, repeated measurements let us reliably calibrate our individual velocity errors ($0.2 leq delta_Vleq 5$ km s$^{-1}$) and directly detect stars with variable radial velocities. We show, by application to the Bootes-1 dwarf spheroidal, that the intrinsic velocity dispersion of this system is significantly below 6.5,km/s reported by previous studies. Our data favor a two-population model of Bootes-1, consisting of a majority `cold stellar component, with velocity dispersion $2.4^{+0.9}_{-0.5}$,km/s, and a minority `hot stellar component, with velocity dispersion $sim 9$,km/s, although we can not completely rule out a single component distribution with velocity dispersion $4.6^{0.8}_{-0.6}$,km/s. We speculate this complex velocity distribution actually reflects the distribution of velocity anisotropy in Bootes-1, which is a measure of its formation processes.
In order to minimize environmental effects and gain an insight into the internal mechanisms that shape the properties of the early-type dwarf systems, we study one of the few isolated dwarf spheroidal galaxies (dSphs) of the Local Group (LG): Cetus. We obtained VLT/FORS2 spectra ($Rsim2600$) in the region of the nIR CaII triplet lines for 80 candidate red giant branch stars. The analysis yielded line-of-sight velocities and metallicities ([Fe/H]) for 54 bona fide member stars. The kinematic analysis shows that Cetus is a mainly pressure-supported ($sigma_v = 11.0_{-1.3}^{+1.6}$ km/s), dark-matter-dominated system ($M_{1/2}/L_V = 23.9_{-8.9}^{+9.7} M_odot/L_odot$) with no significant signs of internal rotation. We find Cetus to be a metal-poor system with a significant [Fe/H] spread (median [Fe/H] = -1.71 dex, median-absolute-deviation = 0.49 dex), as expected for its stellar mass. We report the presence of a mild metallicity gradient compatible with those found in other dSphs of the same luminosity; we trace the presence of a stellar population gradient also in the spatial distribution of stars in different evolutionary phases in ancillary SuprimeCam photometric data. There are tentative indications of two chemo-kinematically distinct sub-populations, with the more metal-poor stars showing a hotter kinematics than the metal-richer ones. Furthermore, the photometric dataset reveals the presence of a foreground population that most likely belongs to the Sagittarius stream. This study represents a first comprehensive analysis of Cetus chemo-kinematic properties. Our results add Cetus to the growing scatter in stellar-dark matter halo properties in low-mass galactic systems. The presence of a metallicity gradient akin to those found in similar systems inhabiting different environments may hint at metallicity gradients in LG early-type dwarfs being driven by internal mechanisms.
We investigate the stellar kinematics of the bulge and disk components in 826 galaxies with a wide range of morphology from the Sydney-AAO Multi-object Integral-field spectroscopy (SAMI) Galaxy Survey. The spatially-resolved rotation velocity (V) and velocity dispersion ($sigma$) of bulge and disk components have been simultaneously estimated using the penalized pixel fitting (pPXF) method with photometrically defined weights for the two components. We introduce a new subroutine of pPXF for dealing with degeneracy in the solutions. We show that the V and $sigma$ distributions in each galaxy can be reconstructed using the kinematics and weights of the bulge and disk components. The combination of two distinct components provides a consistent description of the major kinematic features of galaxies over a wide range of morphological types. We present Tully-Fisher and Faber-Jackson relations showing that the galaxy stellar mass scales with both V and $sigma$ for both components of all galaxy types. We find a tight Faber-Jackson relation even for the disk component. We show that the bulge and disk components are kinematically distinct: (1) the two components show scaling relations with similar slopes, but different intercepts; (2) the spin parameter $lambda_R$ indicates bulges are pressure-dominated systems and disks are supported by rotation; (3) the bulge and disk components have, respectively, low and high values in intrinsic ellipticity. Our findings suggest that the relative contributions of the two components explain, at least to first order, the complex kinematic behaviour of galaxies.
The Canada-France Imaging Survey (CFIS) will consist of deep, high-resolution r-band imaging over ~5000 square degrees of the sky, representing a first-rate opportunity to identify recently-merged galaxies. Due to the large number of galaxies in CFIS, we investigate the use of a convolutional neural network (CNN) for automated merger classification. Training samples of post-merger and isolated galaxy images are generated from the IllustrisTNG simulation processed with the observational realism code RealSim. The CNNs overall classification accuracy is 88 percent, remaining stable over a wide range of intrinsic and environmental parameters. We generate a mock galaxy survey from IllustrisTNG in order to explore the expected purity of post-merger samples identified by the CNN. Despite the CNNs good performance in training, the intrinsic rarity of post-mergers leads to a sample that is only ~6 percent pure when the default decision threshold is used. We investigate trade-offs in purity and completeness with a variable decision threshold and find that we recover the statistical distribution of merger-induced star formation rate enhancements. Finally, the performance of the CNN is compared with both traditional automated methods and human classifiers. The CNN is shown to outperform Gini-M20 and asymmetry methods by an order of magnitude in post-merger sample purity on the mock survey data. Although the CNN outperforms the human classifiers on sample completeness, the purity of the post-merger sample identified by humans is frequently higher, indicating that a hybrid approach to classifications may be an effective solution to merger classifications in large surveys.
Rapid advance has been made recently in accurate distance measurements for nearby ($D < 11$ Mpc) galaxies based on the magnitude of the tip of red giant branch stars resolved with the Hubble Space Telescope. We use observational properties of galaxies presented in the last version of Updated Nearby Galaxy Catalog to derive a halo mass of luminous galaxies via orbital motion of their companions. Our sample contains 298 assumed satellites with known radial velocities around 25 Milky Way-like massive galaxies and 65 assumed satellites around 47 fainter dominant galaxies. The average total mass-to-$K$-band luminosity ratio is $31pm6 M_odot/L_odot$ for the luminous galaxies, increasing up to $sim200 M_odot/L_odot$ toward dwarfs. The bulge-dominated luminous galaxies are characterized with $langle{}M_T/L_Krangle = 73pm15 M_odot/L_odot$, while the disc-dominated spirals have $langle{}M_T/L_Krangle = 17.4pm2.8 M_odot/L_odot$. We draw attention to a particular subsample of luminous spiral galaxies with signs of declining rotation curve, which have a radial velocity dispersion of satellites less than 55 km/s and a poor dark matter halo with $langle{}M_T/L_Krangle = 5.5pm1.1 M_odot/L_odot$. We note that a fraction of quenched (dSph, dE) companions around Milky Way-like galaxies decreases with their linear projected separation as $0.75 exp(-R_p/350,mathrm{kpc})$.
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