Hypervelocity Stars. A New Probe for Near-Field Cosmology. Omar Contigiani. Supervisor: Dr. E.M. Rossi. Co-supervisor: Msc. T.

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1 Hypervelocity Stars A New Probe for Near-Field Cosmology Omar Contigiani Student Colloquium, 20/06/2017, Leiden Co-supervisor: Msc. T. Marchetti Supervisor: Dr. E.M. Rossi

2 Cosmic Web Near-Field Cosmology 50 Mpc Andromeda And why a new probe would useful 10 kpc Credit: V.Springel, Max-Planck Institut für Astrophysik, Garching bei München // Adam Evans

3 Near-Field Cosmology - Structure Formation MILKY WAY

4 Near-Field Cosmology - Structure Formation MILKY WAY DM HALO DENSITY PROFILE Navarro Frenk White Oblate/Prolate

5 Near-Field Cosmology - Structure Formation MILKY WAY DM HALO DENSITY PROFILE Navarro Frenk White Oblate/Prolate PREDICTIONS, e.g. - Self interacting DM Inner spherical halo (Peter+ 2013) - Light MW halo No more missing satellites (Wang+ 2011)

6 Near-Field Cosmology - Structure Formation DM HALO DENSITY PROFILE Navarro Frenk White MILKY WAY DYNAMICAL TRACERS, e.g.: Globular clusters Credit: ESO, F. Ferraro // NASA/JPL-Caltech Stellar streams Oblate/Prolate

7 Near-Field Cosmology - Measurements To Date Credit: Wang+ 2015

8 Near-Field Cosmology - Measurements To Date Oblate/Prolate Streams Halo stars Tracers Credit: Wang Spherical Oblate Problate (Bovy 2016) (Loebman+ 2014) (Bowden+ 2016)

9 Near-Field Cosmology - Measurements To Date Oblate/Prolate Systematic biases Thorough statistical analysis required Streams Halo stars Tracers Credit: Wang Spherical Oblate Problate (Bovy 2016) (Loebman+ 2014) (Bowden+ 2016)

10 - High velocity: v Hypervelocity Stars v - Orbits crossing Galactic center NUMBER OF PAPERS vs YEAR And why they are a hot topic right now Credit: Brown 2015

11 Hypervelocity Stars - Observations To Date NUMBER [2005] RADIAL VELOCITY

12 Hypervelocity Stars - Observations To Date [2014] NUMBER RADIAL VELOCITY [2005] RADIAL VELOCITY DISTANCE FROM G.C.

13 Hypervelocity Stars - Leading mechanism [1988] - Three body interaction binary system and MBH Credit: Brown 2015

14 Hypervelocity Stars - Leading mechanism [1988] - - Three body interaction binary system and MBH S-star is left behind Credit: Brown 2015

15 Hypervelocity Stars - Leading mechanism [1988] - Three body interaction binary system and MBH - S-star is left behind - Hypervelocity star is ejected V ~1000 km/s Credit: Brown 2015

16 Hypervelocity Stars - Promising Past [2005]

17 Hypervelocity Stars - Promising Past [2017] [2005] likely kely not li kely not li kely not li

18 Hypervelocity Stars - Promising Future Quantity Quality Spectroscopic subsample w/ full 3D velocity and position 109 stars SDSS Credit: ESA/Gaia/DPAC. A. Moitinho & M. Barros (CENTRA University of Lisbon)

19 Data Model Statistical Inference Crash Course Constraints on model parameters

20 Statistical Inference - Unit (Fisher) Information Depends only on how sensible the model is to a change of parameters

21 Research Project Goals Study the kinematics of HVS to obtain:

22 Research Project Goals Study the kinematics of HVS to obtain: 1) FISHER FORECAST To assess the potential. Compute the information and display the contours for DM halo parameters. rh Mh

23 Research Project Goals Study the kinematics of HVS to obtain: 1) FISHER FORECAST To assess the potential. 2) ESTIMATED POPULATIONS How many HVSs could be there? Compute the information and display the contours for DM halo parameters. Construct mock catalog of the galactic population and infer how many of them will be observed by Gaia. rh Mh

24 Research Project Goals Study the kinematics of HVS to obtain: 1) FISHER FORECAST To assess the potential. 2) ESTIMATED POPULATIONS How many HVSs could be there? 3) LIKELIHOOD PIPELINE Develop a technique! Compute the information and display the contours for DM halo parameters. Construct mock catalog of the galactic population and infer how many of them will be observed by Gaia. Feed the mock catalog into it and obtain realistic constraints. rh Mh

25 Treat HVS as a statistical ensemble defined in the configuration space Formalism Stellar mass Starting from the physics Phase-space coordinate Number density in configuration space

26 Phase-space distribution - Assumptions 1) Steady state Time-independent potential Time-independent ejection rate

27 Phase-space distribution - Assumptions Steady state 2) Source How many HVSs are ejected per unit mass, volume, velocity? Usually done with Monte Carlo simulations. In our case, analytic function (Rossi+ 2014) which fits MC. (initial) 1)

28 Phase-space distribution - Assumptions 1) Steady state 2) Source Analytic function which fits MC. 3) Sink When to HVS disappear?

29 Phase-space distribution - Assumptions 1) Steady state 2) Source Analytic function which fits MC. 3) Sink When to HVS disappear? Uniformly distributed between [0, 1]

30 Phase-space distribution - Solving continuity equation SINK SOURCE

31 Phase-space distribution - Solving continuity equation Analytic formula, that can be computed for any assumed & Ejection rate Dying rate Unfortunately, it requires the numerical integration of the trajectory

32 Fisher Forecast Estimates based on Unit Information - assuming a 1D toy model of the galaxy Credit: Selletin+ 2014

33 Fisher Forecast - Contours ASSUMPTIONS: - 1D toy model - 5 M HVSs

34 Fisher Forecast - Contours BAD NEWS: Large relative errors.

35 Fisher Forecast - Contours BAD NEWS: Large relative errors. GOOD NEWS: Strong degeneracy, worth investigating.

36 Previous Results Predicted ejection rate theory (Yu+Tremaine 2013) & observations (Kollmeier+ 2010) Mock catalogs Simulation of the HVS Galactic and Gaia populations Predicted pop. of M within 100 kpc Observations (Brown 2015)

37 Mock catalogs- Ingredients 1) Ejection Rate & Flight time distribution Previously modelled

38 Mock catalogs- Ingredients 1) Ejection Rate & Flight time distribution Previously modelled 2) Galactic Model Kenyon (Potential) Halo + Bulge (spherical) Disc (axisymmetric ) Bovy+ 2015a ( 3D Dustmap) Green+ 15, Marshall+ 06, Drimmel+ 03

39 Mock catalogs- Ingredients 1) Ejection Rate & Flight time distribution Previously modelled 2) Galactic Model Kenyon (Potential) Bovy+ 2015a (Dustmap) 3) Gaia Selection Function GRVS < 16 pygaia (A. Brown) to reconstruct Errorbars on proper motions / parallax / radial velocity

40 Mock catalogs- HVS Galactic population Total Galactic population 60% unbound

41 Mock catalogs- HVS Galactic population Gaia 3d velocities and positions 10% unbound

42 Mock catalogs- HVS Galactic population Gaia 3d velocities and positions (high velocity) ~200 stars

43 Full likelihood Finally! Observed data from mock catalogs Formalism can predict different PDF for different parameters Mh, rh, c/a

44 Full Likelihood

45 Full Likelihood GOOD NEWS 1) 2) No bias

46 Full Likelihood GOOD NEWS 1) No bias 2) MIXED NEWS Effective constraint:

47 Summary FORMALISM 1) FISHER FORECAST To assess the potential. 2) ESTIMATED POPULATIONS How many HVSs are expected. 3) LIKELIHOOD PIPELINE Develop a technique! Scientific Outlook 1) BARYONIC POTENTIAL Can HVSs constrain the disk/bulge? 2) CHECK CONTAMINATION Weighted likelihood? 3) BREAK DEGENERACY More contours!

48 Mock catalogs- HVSs Galactic population vs Gaia

49 Fisher Forecast - P-S distribution ASSUMPTIONS: - 2D toy model - 5 M HVSs

50 Fisher Forecast - P-S distribution

51 Statistical Inference - Likelihood Parametric PDF Likelihood Likelihood Principle: Maximum Likelihood Estimation: All knowledge about the real parameters is in the likelihood. The point of maximum of the likelihood is a good estimator of the real parameters.