ترغب بنشر مسار تعليمي؟ اضغط هنا

Qualitative interpretation of galaxy spectra

359   0   0.0 ( 0 )
 نشر من قبل J. Sanchez Almeida
 تاريخ النشر 2012
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We describe a simple step-by-step guide to qualitative interpretation of galaxy spectra. Rather than an alternative to existing automated tools, it is put forward as an instrument for quick-look analysis, and for gaining physical insight when interpreting the outputs provided by automated tools. Though the recipe is of general application, it was developed for understanding the nature of the Automatic Spectroscopic K-means based (ASK) template spectra. They resulted from the classification of all the galaxy spectra in the Sloan Digital Sky Survey data release 7 (SDSS-DR7), thus being a comprehensive representation of the galaxy spectra in the local universe. Using the recipe, we give a description of the properties of the gas and the stars that characterize the ASK classes, from those corresponding to passively evolving galaxies, to HII galaxies undergoing a galaxy-wide starburst. The qualitative analysis is found to be in excellent agreement with quantitative analyses of the same spectra. A number of byproducts follow from the analysis. There is a tight correlation between the age of the stellar population and the metallicity of the gas, which is stronger than the correlations between galaxy mass and stellar age, and galaxy mass and gas metallicity. The galaxy spectra are known to follow a 1-dimensional sequence, and we identify the luminosity-weighted mean stellar age as the affine parameter that describes the sequence. All ASK classes happen to have a significant fraction of old stars, although spectrum-wise they are outshined by the youngest populations. Old stars are metal rich or metal poor depending on whether they reside in passive galaxies or in star-forming galaxies.

قيم البحث

اقرأ أيضاً

Anomalies drive scientific discovery -- they are associated with the cutting edge of the research frontier, and thus typically exploit data in the low signal-to-noise regime. In astronomy, the prevalence of systematics --- both known unknowns and unk nown unknowns --- combined with increasingly large datasets, the widespread use of ad hoc estimators for anomaly detection, and the look-elsewhere effect, can lead to spurious false detections. In this informal note, I argue that anomaly detection leading to discoveries of new physics requires a combination of physical understanding, careful experimental design to avoid confirmation bias, and self-consistent statistical methods. These points are illustrated with several concrete examples from cosmology.
90 - Anna Gallazzi 2009
Stellar masses play a crucial role in the exploration of galaxy properties and the evolution of the galaxy population. In this paper, we explore the minimum possible uncertainties in stellar mass-to-light (M/L) ratios from the assumed star formation history (SFH) and metallicity distribution, with the goals of providing a minimum set of requirements for observational studies. We use a large Monte Carlo library of SFHs to study as a function of galaxy spectral type and signal-to-noise ratio (S/N) the statistical uncertainties of M/L values using either absorption-line data or broad band colors. The accuracy of M/L estimates can be significantly improved by using metal-sensitive indices in combination with age-sensitive indices, in particular for galaxies with intermediate-age or young stellar populations. While M/L accuracy clearly depends on the spectral S/N ratio, there is no significant gain in improving the S/N much above 50/pix and limiting uncertainties of 0.03 dex are reached. Assuming that dust is accurately corrected or absent and that the redshift is known, color-based M/L estimates are only slightly more uncertain than spectroscopic estimates (at comparable spectroscopic and photometric quality), but are more easily affected by systematic biases. This is the case in particular for galaxies with bursty SFHs (high Hdelta at fixed D4000), the M/L of which cannot be constrained any better than 0.15 dex with any indicators explored here. Finally, we explore the effects of the assumed prior distribution in SFHs and metallicity, finding them to be higher for color-based estimates.
73 - I. Zhuravleva 2014
We address the problem of evaluating the power spectrum of the velocity field of the ICM using only information on the plasma density fluctuations, which can be measured today by Chandra and XMM-Newton observatories. We argue that for relaxed cluster s there is a linear relation between the rms density and velocity fluctuations across a range of scales, from the largest ones, where motions are dominated by buoyancy, down to small, turbulent scales: $(deltarho_k/rho)^2 = eta_1^2 (V_{1,k}/c_s)^2$, where $deltarho_k/rho$ is the spectral amplitude of the density perturbations at wave number $k$, $V_{1,k}^2=V_k^2/3$ is the mean square component of the velocity field, $c_s$ is the sound speed, and $eta_1$ is a dimensionless constant of order unity. Using cosmological simulations of relaxed galaxy clusters, we calibrate this relation and find $eta_1approx 1 pm 0.3$. We argue that this value is set at large scales by buoyancy physics, while at small scales the density and velocity power spectra are proportional because the former are a passive scalar advected by the latter. This opens an interesting possibility to use gas density power spectra as a proxy for the velocity power spectra in relaxed clusters, across a wide range of scales.
Using the k-means cluster analysis algorithm, we carry out an unsupervised classification of all galaxy spectra in the seventh and final Sloan Digital Sky Survey data release (SDSS/DR7). Except for the shift to restframe wavelengths, and the normaliz ation to the g-band flux, no manipulation is applied to the original spectra. The algorithm guarantees that galaxies with similar spectra belong to the same class. We find that 99 % of the galaxies can be assigned to only 17 major classes, with 11 additional minor classes including the remaining 1%. The classification is not unique since many galaxies appear in between classes, however, our rendering of the algorithm overcomes this weakness with a tool to identify borderline galaxies. Each class is characterized by a template spectrum, which is the average of all the spectra of the galaxies in the class. These low noise template spectra vary smoothly and continuously along a sequence labeled from 0 to 27, from the reddest class to the bluest class. Our Automatic Spectroscopic K-means-based (ASK) classification separates galaxies in colors, with classes characteristic of the red sequence, the blue cloud, as well as the green valley. When red sequence galaxies and green valley galaxies present emission lines, they are characteristic of AGN activity. Blue galaxy classes have emission lines corresponding to star formation regions. We find the expected correlation between spectroscopic class and Hubble type, but this relationship exhibits a high intrinsic scatter. Several potential uses of the ASK classification are identified and sketched, including fast determination of physical properties by interpolation, classes as templates in redshift determinations, and target selection in follow-up works (we find classes of Seyfert galaxies, green valley galaxies, as well as a significant number of outliers). The ASK classification is publicly accessible through various websites.
Intensity mapping is a promising technique for surveying the large scale structure of our Universe from $z=0$ to $z sim 150$, using the brightness temperature field of spectral lines to directly observe previously unexplored portions of out cosmic ti meline. Examples of targeted lines include the $21,textrm{cm}$ hyperfine transition of neutral hydrogen, rotational lines of carbon monoxide, and fine structure lines of singly ionized carbon. Recent efforts have focused on detections of the power spectrum of spatial fluctuations, but have been hindered by systematics such as foreground contamination. This has motivated the decomposition of data into Fourier modes perpendicular and parallel to the line-of-sight, which has been shown to be a particularly powerful way to diagnose systematics. However, such a method is well-defined only in the limit of a narrow-field, flat-sky approximation. This limits the sensitivity of intensity mapping experiments, as it means that wide surveys must be separately analyzed as a patchwork of smaller fields. In this paper, we develop a framework for analyzing intensity mapping data in a spherical Fourier-Bessel basis, which incorporates curved sky effects without difficulty. We use our framework to generalize a number of techniques in intensity mapping data analysis from the flat sky to the curved sky. These include visibility-based estimators for the power spectrum, treatments of interloper lines, and the foreground wedge signature of spectrally smooth foregrounds.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا