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Register a new userThe Gemini spectral library of near-IR late type stellar templates and its application for velocity dispersion measurements
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Claudia Winge Gemini Observatory
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We present a spectroscopic library of late spectral type stellar templates in the near-IR range 2.15-2.42microns, at R=5300-5900 resolution, oriented to support stellar kinematics studies in external galaxies, such as the direct determination of the masses of supermassive black-holes in nearby active (or non-active) galaxies. The combination of high spectral resolution and state-of-the-art instrumentation available in 8-m class telescopes has made the analysis of circumnuclear stellar kinematics using the near-IR CO band heads one of the most used techniques for such studies, and this library aims to provide the supporting datasets required by the higher spectral resolution and larger spectral coverage currently achieved with modern near-IR spectrographs. Examples of the application for kinematical analysis are given for data obtained with two Gemini instruments, but the templates can be easily adjusted for use with other near-IR spectrographs at similar or lower resolution. The example datasets are also used to revisit the template mismatch effect and the dependence of the velocity dispersion values obtained from the fitting process with the characteristics of the stellar templates. The library is available in electronic form from the Gemini web pages (link above).
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Integrated light spectroscopy from galaxies can be used to study the stellar populations that cannot be resolved into individual stars. This analysis relies on stellar population synthesis (SPS) techniques to study the formation history and structure of galaxies. However, the spectral templates available for SPS are limited, especially in the near-infrared. We present A-LIST (APOGEE Library of Infrared SSP Templates), a new set of high-resolution, near-IR SSP spectral templates spanning a wide range of ages (2-12 Gyr), metallicities ($rm -2.2 < [M/H] < +0.4$) and $alpha$ abundances ($rm -0.2 < [alpha/M] < +0.4$). This set of SSP templates is the highest resolution ($Rsim22500$) available in the near infrared, and the first such based on an empirical stellar library. Our models are generated using spectra of $sim$300,000 stars spread across the Milky Way, with a wide range of metallicities and abundances, from the APOGEE survey. We show that our model spectra provide accurate fits to M31 globular cluster spectra taken with APOGEE, with best-fit metallicities agreeing with those of previous estimates to within $sim$0.1 dex. We also compare these model spectra to lower-resolution E-MILES models and demonstrate that we recover the ages of these models to within $sim$1.5 Gyr. This library is available in https://github.com/aishashok/ALIST-library.
Empirical stellar libraries are extensively used to extract stellar kinematics in galaxies and to build stellar population models. An accurate knowledge of the spectral resolution of these libraries is critical to avoid propagation errors and uncertain estimates of the intrinsic stellar velocity dispersion of galaxies. In this research note we re-assess the spectral resolution of the MILES stellar library and of the stellar population models based on it. This exercise was performed, because of a recent controversy over the exact MILES resolution. We perform our test through the comparison of MILES stellar spectra with three different sets of higher-resolution templates, one fully theoretical - the MARCS library - and two empirical ones, namely the Indo-U.S. and ELODIE v3.1 libraries. The theoretical template has a well-defined very high (R=20000) resolution. Hence errors on this theoretical value do not affect our conclusions. Our approach based on the MARCS library was crucial to constrain the values of the resolution also for the other two empirical templates. We find that the MILES resolution has previously been slightly overestimated. We derive a new spectral resolution of 2.54 A FWHM, instead of the nominal 2.3 A. The reason for this difference is due to an overestimation of the resolution for the Indo-U.S. library that was previously used for estimates of the MILES resolution. For the Indo-U.S. we obtain a new value of 1.35 A FWHM. Most importantly, the results derived from the MARCS and ELODIE libraries are in very good agreement. These results are important for users of the MILES spectra library and for further development of stellar population models aimed to obtain accurate stellar kinematics in galaxies.
We used the Project 1640 near-infrared coronagraph and integral field spectrograph to observe 19 young solar type stars. Five of these stars are known binary stars and we detected the late-type secondaries and were able to measure their JH spectra with a resolution of Rsim30. The reduced, extracted, and calibrated spectra were compared to template spectra from the IRTF spectral library. With this comparison we test the accuracy and consistency of spectral type determination with the low-resolution near-infrared spectra from P1640. Additionally, we determine effective temperature and surface gravity of the companions by fitting synthetic spectra calculated with the PHOENIX model atmosphere code. We also present several new epochs of astrometry of each of the systems. Together these data increase our knowledge and understanding of the stellar make up of these systems. In addition to the astronomical results, the analysis presented helps validate the Project 1640 data reduction and spectral extraction processes and the utility of low-resolution, near-infrared spectra for characterizing late-type companions in multiple systems.
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification and regression problems like the determination of stellar atmospheric parameters Teff, log g, [Fe/H]. We propose an automated approach for the classification of stellar spectra in the optical region using Convolutional Neural Networks. Traditional machine learning (ML) methods with shallow architecture (usually up to 2 hidden layers) have been trained for these purposes in the past. However, deep learning methods with a larger number of hidden layers allow the use of finer details in the spectrum which results in improved accuracy and better generalisation. Studying finer spectral signatures also enables us to determine accurate differential stellar parameters and find rare objects. We examine various machine and deep learning algorithms like Artificial Neural Networks (ANN), Random Forest (RF), and Convolutional Neural Network (CNN) to classify stellar spectra using the Jacoby Atlas, ELODIE and MILES spectral libraries as training samples. We test the performance of the trained networks on the Indo-U.S. Library of Coude Feed Stellar Spectra (CFLIB). We show that using convolutional neural networks, we are able to lower the error up to 1.23 spectral sub-classes as compared to that of 2 sub-classes achieved in the past studies with ML approach. We further apply the trained model to classify stellar spectra retrieved from the SDSS database with SNR>20.
We analyze 40 cosmological re-simulations of individual massive galaxies with present-day stellar masses of $M_{*} > 6.3 times 10^{10} M_{odot}$ in order to investigate the physical origin of the observed strong increase in galaxy sizes and the decrease of the stellar velocity dispersions since redshift $z approx 2$. At present 25 out of 40 galaxies are quiescent with structural parameters (sizes and velocity dispersions) in agreement with local early type galaxies. At z=2 all simulated galaxies with $M_* gtrsim 10^{11}M_{odot}$ (11 out of 40) at z=2 are compact with projected half-mass radii of $approx$ 0.77 ($pm$0.24) kpc and line-of-sight velocity dispersions within the projected half-mass radius of $approx$ 262 ($pm$28) kms$^{-1}$ (3 out of 11 are already quiescent). Similar to observed compact early-type galaxies at high redshift the simulated galaxies are clearly offset from the local mass-size and mass-velocity dispersion relations. Towards redshift zero the sizes increase by a factor of $sim 5-6$, following $R_{1/2} propto (1+z)^{alpha}$ with $alpha = -1.44$ for quiescent galaxies ($alpha = -1.12$ for all galaxies). The velocity dispersions drop by about one-third since $z approx 2$, following $sigma_{1/2} propto (1+z)^{beta}$ with $beta = 0.44$ for the quiescent galaxies ($beta = 0.37$ for all galaxies). The simulated size and dispersion evolution is in good agreement with observations and results from the subsequent accretion and merging of stellar systems at $zlesssim 2$ which is a natural consequence of the hierarchical structure formation. A significant number of the simulated massive galaxies (7 out of 40) experience no merger more massive than 1:4 (usually considered as major mergers). On average, the dominant accretion mode is stellar minor mergers with a mass-weighted mass-ratio of 1:5. (abridged)
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