ترغب بنشر مسار تعليمي؟ اضغط هنا

The Implications of Local Fluctuations in the Galactic Midplane for Dynamical Analysis in the Gaia Era

139   0   0.0 ( 0 )
 نشر من قبل Angus Beane
 تاريخ النشر 2019
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

Orbital properties of stars, computed from their six-dimensional phase space measurements and an assumed Galactic potential, are used to understand the structure and evolution of the Galaxy. Stellar actions, computed from orbits, have the attractive quality of being invariant under certain assumptions and are therefore used as quantitative labels of a stars orbit. We report a subtle but important systematic error that is induced in the actions as a consequence of local midplane variations expected for the Milky Way. This error is difficult to model because it is non-Gaussian and bimodal, with neither mode peaking on the null value. An offset in the vertical position of the Galactic midplane of $sim15,text{pc}$ for a thin disk-like orbit or $sim 120,text{pc}$ for a thick disk-like orbit induces a $25%$ systematic error in the vertical action $J_z$. In FIRE simulations of Milky Way-mass galaxies, these variations are on the order of $sim100,text{pc}$ at the solar circle. From observations of the mean vertical velocity variation of $sim5text{--}10,text{km},text{s}^{-1}$ with radius, we estimate that the Milky Way midplane variations are $sim60text{--}170,text{pc}$, consistent with three-dimensional dust maps. Action calculations and orbit integrations, which assume the global and local midplanes are identical, are likely to include this induced error, depending on the volume considered. Variation in the local standard of rest or distance to the Galactic center causes similar issues. The variation of the midplane must be taken into account when performing dynamical analysis across the large regions of the disk accessible to Gaia and future missions.



قيم البحث

اقرأ أيضاً

The velocity anisotropy parameter, beta, is a measure of the kinematic state of orbits in the stellar halo which holds promise for constraining the merger history of the Milky Way (MW). We determine global trends for beta as a function of radius from three suites of simulations, including accretion only and cosmological hydrodynamic simulations. We find that both types of simulations are consistent and predict strong radial anisotropy (<beta>~0.7) for Galactocentric radii greater than 10 kpc. Previous observations of beta for the MWs stellar halo claim a detection of an isotropic or tangential dip at r~20 kpc. Using the N-body+SPH simulations, we investigate the temporal persistence, population origin, and severity of dips in beta. We find dips in the in situ stellar halo are long-lived, while dips in the accreted stellar halo are short-lived and tied to the recent accretion of satellite material. We also find that a major merger as early as z~1 can result in a present day low (isotropic to tangential) value of beta over a wide range of radii and angular expanse. While all of these mechanisms are plausible drivers for the beta dip observed in the MW, in the simulations, each mechanism has a unique metallicity signature associated with it, implying that future spectroscopic surveys could distinguish between them. Since an accurate knowledge of beta(r) is required for measuring the mass of the MW halo, we note significant transient dips in beta could cause an overestimate of the halos mass when using spherical Jeans equation modeling.
118 - Michael A. Kuhn 2020
We present ~120,000 Spitzer/IRAC candidate young stellar objects (YSOs) based on surveys of the Galactic midplane between l~255 deg and 110 deg, including the GLIMPSE I, II, and 3D, Vela-Carina, Cygnus X, and SMOG surveys (613 square degrees), augmen ted by near-infrared catalogs. We employed a classification scheme that uses the flexibility of a tailored statistical learning method and curated YSO datasets to take full advantage of IRACs spatial resolution and sensitivity in the mid-infrared ~3-9 micron range. Multi-wavelength color/magnitude distributions provide intuition about how the classifier separates YSOs from other red IRAC sources and validate that the sample is consistent with expectations for disk/envelope-bearing pre-main-sequence stars. We also identify areas of IRAC color space associated with objects with strong silicate absorption or polycyclic aromatic hydrocarbon emission. Spatial distributions and variability properties help corroborate the youthful nature of our sample. Most of the candidates are in regions with mid-IR nebulosity, associated with star-forming clouds, but others appear distributed in the field. Using Gaia DR2 distance estimates, we find groups of YSO candidates associated with the Local Arm, the Sagittarius-Carina Arm, and the Scutum-Centaurus Arm. Candidate YSOs visible to the Zwicky Transient Facility tend to exhibit higher variability amplitudes than randomly selected field stars of the same magnitude, with many high-amplitude variables having light-curve morphologies characteristic of YSOs. Given that no current or planned instruments will significantly exceed IRACs spatial resolution while possessing its wide-area mapping capabilities, Spitzer-based catalogs such as ours will remain the main resources for mid-infrared YSOs in the Galactic midplane for the near future.
The structural and dynamical properties of star clusters are generally derived by means of the comparison between steady-state analytic models and the available observables. With the aim of studying the biases of this approach, we fitted different an alytic models to simulated observations obtained from a suite of direct N-body simulations of star clusters in different stages of their evolution and under different levels of tidal stress to derive mass, mass function and degree of anisotropy. We find that masses can be under/over-estimated up to 50% depending on the degree of relaxation reached by the cluster, the available range of observed masses and distances of radial velocity measures from the cluster center and the strength of the tidal field. The mass function slope appears to be better constrainable and less sensitive to model inadequacies unless strongly dynamically evolved clusters and a non-optimal location of the measured luminosity function are considered. The degree and the characteristics of the anisotropy developed in the N-body simulations are not adequately reproduced by popular analytic models and can be detected only if accurate proper motions are available. We show how to reduce the uncertainties in the mass, mass-function and anisotropy estimation and provide predictions for the improvements expected when Gaia proper motions will be available in the near future.
110 - Angela Bragaglia 2017
Stellar clusters are important for astrophysics in many ways, for instance as optimal tracers of the Galactic populations to which they belong or as one of the best test bench for stellar evolutionary models. Gaia DR1, with TGAS, is just skimming the wealth of exquisite information we are expecting from the more advanced catalogues, but already offers good opportunities and indicates the vast potentialities. Gaia results can be efficiently complemented by ground-based data, in particular by large spectroscopic and photometric surveys. Examples of some scientific results of the Gaia-ESO survey are presented, as a teaser for what will be possible once advanced Gaia releases and ground-based data will be combined.
Open clusters are key targets for both Galaxy structure and evolution and stellar physics studies. Since textit{Gaia} DR2 publication, the discovery of undetected clusters has proven that our samples were not complete. Our aim is to exploit the Big D ata capabilities of machine learning to detect new open clusters in textit{Gaia} DR2, and to complete the open cluster sample to enable further studies on the Galactic disc. We use a machine learning based methodology to systematically search in the Galactic disc, looking for overdensities in the astrometric space and identifying them as open clusters using photometric information. First, we use an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in textit{Gaia} DR2 $(l,b,varpi,mu_{alpha^*},mu_delta)$. After that, we use a deep learning artificial neural network trained on colour-magnitude diagrams to identify isochrone patterns in these overdensities, and to confirm them as open clusters. We find $582$ new open clusters distributed along the Galactic disc, in the region $|b| < 20$. We can detect substructure in complex regions, and identify the tidal tails of a disrupting cluster UBC~$274$ of $sim 3$ Gyr located at $sim 2$ kpc. Adapting the methodology into a Big Data environment allows us to target the search driven by physical properties of the open clusters, instead of being driven by its computational requirements. This blind search for open clusters in the Galactic disc increases in a $45%$ the number of known open clusters.
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