Hypervelocity star candidates in Gaia DR1/TGAS

AbstractHypervelocity stars (HVSs) are characterized by a total velocity in excess of the Galactic escape speed, and with trajectories consistent with coming from the Galactic Centre. We apply a novel data mining routine, an artificial neural network, to discover HVSs in the TGAS subset of the first data release of the Gaia satellite, using only the astrometry of the stars. We find 80 stars with a predicted probability >90% of being HVSs, and we retrieved radial velocities for 47 of those. We discover 14 objects with a total velocity in the Galactic rest frame >400 km s−1, and 5 of these have a probability >50% of being unbound from the Milky Way. Tracing back orbits in different Galactic potentials, we discover 1 HVS candidate, 5 bound HVS candidates, and 5 runaway star candidates with remarkably high velocities, between 400 and 780 km s−1. We wait for future Gaia releases to confirm the goodness of our sample and to increase the number of HVS candidates.

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The escape speed curve of the Galaxy obtained from Gaia DR2 implies a heavy Milky Way

Astronomy and Astrophysics ◽

10.1051/0004-6361/201833748 ◽

2018 ◽

Vol 616 ◽

pp. L9 ◽

Cited By ~ 41

Author(s):

G. Monari ◽

B. Famaey ◽

I. Carrillo ◽

T. Piffl ◽

M. Steinmetz ◽

...

Keyword(s):

Mass Concentration ◽

Milky Way ◽

Galactic Centre ◽

High Concentration ◽

Circular Velocity ◽

Halo Stars ◽

Dark Matter Mass ◽

The Galaxy ◽

Escape Speed ◽

Gaia Dr2

We measure the escape speed curve of the Milky Way based on the analysis of the velocity distribution of ~2850 counter-rotating halo stars from the Gaia Data Release 2. The distances were estimated through the StarHorse code, and only stars with distance errors smaller than 10% were used in the study. The escape speed curve is measured at Galactocentric radii ranging from ~5 kpc to ~10.5 kpc. The local Galactic escape at the Sun’s position is estimated to be ve(r⊙) = 580 ± 63 km s−1, and it rises towards the Galactic centre. Defined as the minimum speed required to reach three virial radii, our estimate of the escape speed as a function of radius implies for a Navarro–Frenk–White profile and local circular velocity of 240 km s−1 a dark matter mass M200 = 1.28−0.50+0.68 × 1012 M⊙ and a high concentration c200 = 11.09−1.79+2.94. Assuming the mass-concentration relation of ΛCDM, we obtain M200 = 1.55−0.51+0.64 × 1012 M⊙ and c200 = 7.93−0.27+0.33 for a local circular velocity of 228 km s−1.

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Gaia Data Release 2

Astronomy and Astrophysics ◽

10.1051/0004-6361/201832865 ◽

2018 ◽

Vol 616 ◽

pp. A11 ◽

Cited By ~ 157

Author(s):

◽

D. Katz ◽

T. Antoja ◽

M. Romero-Gómez ◽

R. Drimmel ◽

...

Keyword(s):

Phase Space ◽

Velocity Field ◽

Milky Way ◽

Solar Neighbourhood ◽

Galactic Centre ◽

Full Potential ◽

Galactic Disc ◽

Giant Stars ◽

Data Release ◽

Velocity Dispersions

Context. The second Gaia data release (Gaia DR2) contains high-precision positions, parallaxes, and proper motions for 1.3 billion sources as well as line-of-sight velocities for 7.2 million stars brighter than GRVS = 12 mag. Both samples provide a full sky coverage. Aims. To illustrate the potential of Gaia DR2, we provide a first look at the kinematics of the Milky Way disc, within a radius of several kiloparsecs around the Sun. Methods. We benefit for the first time from a sample of 6.4 million F-G-K stars with full 6D phase-space coordinates, precise parallaxes (σϖ∕ϖ ≤ 20%), and precise Galactic cylindrical velocities (median uncertainties of 0.9-1.4 km s-1 and 20% of the stars with uncertainties smaller than 1 km s-1 on all three components). From this sample, we extracted a sub-sample of 3.2 million giant stars to map the velocity field of the Galactic disc from ~5 kpc to ~13 kpc from the Galactic centre and up to 2 kpc above and below the plane. We also study the distribution of 0.3 million solar neighbourhood stars (r < 200 pc), with median velocity uncertainties of 0.4 km s-1, in velocity space and use the full sample to examine how the over-densities evolve in more distant regions. Results. Gaia DR2 allows us to draw 3D maps of the Galactocentric median velocities and velocity dispersions with unprecedented accuracy, precision, and spatial resolution. The maps show the complexity and richness of the velocity field of the galactic disc. We observe streaming motions in all the components of the velocities as well as patterns in the velocity dispersions. For example, we confirm the previously reported negative and positive galactocentric radial velocity gradients in the inner and outer disc, respectively. Here, we see them as part of a non-axisymmetric kinematic oscillation, and we map its azimuthal and vertical behaviour. We also witness a new global arrangement of stars in the velocity plane of the solar neighbourhood and in distant regions in which stars are organised in thin substructures with the shape of circular arches that are oriented approximately along the horizontal direction in the U − V plane. Moreover, in distant regions, we see variations in the velocity substructures more clearly than ever before, in particular, variations in the velocity of the Hercules stream. Conclusions. Gaia DR2 provides the largest existing full 6D phase-space coordinates catalogue. It also vastly increases the number of available distances and transverse velocities with respect to Gaia DR1. Gaia DR2 offers a great wealth of information on the Milky Way and reveals clear non-axisymmetric kinematic signatures within the Galactic disc, for instance. It is now up to the astronomical community to explore its full potential.

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Deflection of the hypervelocity stars by the pull of the Large Magellanic Cloud on the Milky Way

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa2211 ◽

2020 ◽

Vol 497 (3) ◽

pp. 2930-2940

Author(s):

D Boubert ◽

D Erkal ◽

A Gualandris

Keyword(s):

Dark Matter ◽

Milky Way ◽

Large Magellanic Cloud ◽

Magellanic Cloud ◽

Dark Matter Halo ◽

Galactic Centre ◽

Supermassive Black Hole ◽

Galactic Dark Matter ◽

Straight Lines ◽

Escape Speed

ABSTRACT Stars slingshotted by the supermassive black hole at the Galactic Centre escape from the Milky Way so quickly that their trajectories are almost straight lines. Previous works have shown how these ‘hypervelocity stars’ (stars moving faster than the local Galactic escape speed) are subsequently deflected by the gravitational field of the Milky Way and the Large Magellanic Cloud (LMC), but have neglected to account for the reflex motion of the Milky Way in response to the fly-by of the LMC. A consequence of this motion is that the hypervelocity stars we see in the outskirts of the Milky Way today were ejected from where the Milky Way centre was hundreds of millions of years ago. This change in perspective causes large apparent deflections of several degrees in the trajectories of the hypervelocity stars. We quantify these deflections by simulating the ejection of hypervelocity stars from an isolated Milky Way (with a spherical or flattened dark matter halo), from a fixed-in-place Milky Way with a passing LMC, and from a Milky Way that responds to the passage of the LMC, finding that LMC passage causes larger deflections than can be caused by a flattened Galactic dark matter halo in ΛCDM. The $10\, \mu \mathrm{as}\, \mathrm{yr}^{-1}$ proper motion precision necessary to measure these deflections will be possible with the combination of Gaia with the proposed GaiaNIR successor mission, and these measurements will directly probe the shape of the Milky Way, the mass of the LMC, and the dance of these two galaxies.

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The nature of giant clumps in high-z discs: a deep-learning comparison of simulations and observations

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa3778 ◽

2020 ◽

Vol 501 (1) ◽

pp. 730-746

Author(s):

Omri Ginzburg ◽

Marc Huertas-Company ◽

Avishai Dekel ◽

Nir Mandelker ◽

Gregory Snyder ◽

...

Keyword(s):

Neural Network ◽

Deep Learning ◽

Main Sequence ◽

High Redshift ◽

High Mass ◽

Galactic Centre ◽

Preferential Formation ◽

Maximum Resolution ◽

Supernova Feedback ◽

Disc Galaxies

ABSTRACT We use deep learning to explore the nature of observed giant clumps in high-redshift disc galaxies, based on their identification and classification in cosmological simulations. Simulated clumps are detected using the 3D gas and stellar densities in the VELA zoom-in cosmological simulation suite, with ${\sim}25\ \rm {pc}$ maximum resolution, targeting main-sequence galaxies at 1 < z < 3. The clumps are classified as long-lived clumps (LLCs) or short-lived clumps (SLCs) based on their longevity in the simulations. We then train neural networks to detect and classify the simulated clumps in mock, multicolour, dusty, and noisy HST-like images. The clumps are detected using an encoder–decoder convolutional neural network (CNN), and are classified according to their longevity using a vanilla CNN. Tests using the simulations show our detector and classifier to be ${\sim}80{{\ \rm per\ cent}}$ complete and ${\sim}80{{\ \rm per\ cent}}$ pure for clumps more massive than ∼107.5 M⊙. When applied to observed galaxies in the CANDELS/GOODS S+N fields, we find both types of clumps to appear in similar abundances in the simulations and the observations. LLCs are, on average, more massive than SLCs by ∼0.5 dex, and they dominate the clump population above Mc ≳ 107.6 M⊙. LLCs tend to be found closer to the galactic centre, indicating clump migration to the centre or preferential formation at smaller radii. The LLCs are found to reside in high-mass galaxies, indicating better clump survivability under supernova feedback there, due to clumps being more massive in these galaxies. We find the clump masses and radial positions in the simulations and the observations to agree within a factor of 2.

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Application of Combined Grey Neural Network and Data Mining in Information Technology Education

2009 Second International Conference on Education Technology and Training ◽

10.1109/ett.2009.8 ◽

2009 ◽

Cited By ~ 2

Author(s):

Qu Zhiming ◽

Hou Wei

Keyword(s):

Neural Network ◽

Data Mining ◽

Information Technology ◽

Technology Education ◽

Information Technology Education

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Quantifying tidal stream disruption in a simulated Milky Way

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stx1268 ◽

2017 ◽

Vol 470 (1) ◽

pp. 522-538 ◽

Cited By ~ 10

Author(s):

Emily Sandford ◽

Andreas H. W. Küpper ◽

Kathryn V. Johnston ◽

Jürg Diemand

Keyword(s):

Dark Matter ◽

Milky Way ◽

Galactic Halo ◽

Mass Range ◽

Galactic Centre ◽

High Dimensions ◽

Density Profiles ◽

Upper Limits ◽

Tidal Stream ◽

Tidal Streams

Abstract Simulations of tidal streams show that close encounters with dark matter subhaloes induce density gaps and distortions in on-sky path along the streams. Accordingly, observing disrupted streams in the Galactic halo would substantiate the hypothesis that dark matter substructure exists there, while in contrast, observing collimated streams with smoothly varying density profiles would place strong upper limits on the number density and mass spectrum of subhaloes. Here, we examine several measures of stellar stream ‘disruption' and their power to distinguish between halo potentials with and without substructure and with different global shapes. We create and evolve a population of 1280 streams on a range of orbits in the Via Lactea II simulation of a Milky Way-like halo, replete with a full mass range of Λcold dark matter subhaloes, and compare it to two control stream populations evolved in smooth spherical and smooth triaxial potentials, respectively. We find that the number of gaps observed in a stellar stream is a poor indicator of the halo potential, but that (i) the thinness of the stream on-sky, (ii) the symmetry of the leading and trailing tails and (iii) the deviation of the tails from a low-order polynomial path on-sky (‘path regularity') distinguish between the three potentials more effectively. We furthermore find that globular cluster streams on low-eccentricity orbits far from the galactic centre (apocentric radius ∼30–80 kpc) are most powerful in distinguishing between the three potentials. If they exist, such streams will shortly be discoverable and mapped in high dimensions with near-future photometric and spectroscopic surveys.

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