Diffuse Stellar Component in State-of-the-art Cosmological - - PowerPoint PPT Presentation

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Diffuse Stellar Component in State-of-the-art Cosmological Hydrodynamical Simulations Stellar Halos 2018 Rodrigo Caas rodrigo.canas@icrar.org Claudia Lagos Chris Power Pascal Elahi Charlotte Welker What do we mean by diffuse? Stellar

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Diffuse Stellar Component in State-of-the-art Cosmological Hydrodynamical Simulations

Rodrigo Cañas

rodrigo.canas@icrar.org

Claudia Lagos Chris Power Pascal Elahi Charlotte Welker

Stellar Halos 2018

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What do we mean by diffuse?

  • Stellar Haloes
  • Intra-Group Light
  • Intra-Cluster Light

Stellar material that surrounds galaxies

Intra-Halo Stellar Component (IHSC)

scale independent!

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Merritt et al., 2016

Motivation - at MW masses

Stellar Mass Diffuse Fraction

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Motivation - Intra-Cluster Light

Morishita et al., 2017

`

Cluster MACS0416

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.

From MW to ICL - observations

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Multiple approaches N-body simuations

  • “Idealized” simulations

(Bullock & Johnston 2005)

  • SAMs (Contini+2014)
  • SAMs + Particle tagging

(Cooper+2010, 2013, 2015, 2017)

  • Accreted mass

How IHSC is measured in simulations?

Cooper et al. (2010) Bullock & Johnston (2005)

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Multiple approaches

Hydro-sims

  • In-situ vs Ex-situ
  • Follow satellites (e.g. Ana-Roxana’s talk)
  • Sharp cuts
  • Fixed spherical appertures
  • X kpc
  • N-times effective or half mass radius

How IHSC is measured in simulations?

Monachesi+2018 Auriga Huang et al (in preparation) Alexie’s talk

  • This could introduce biases due to mass

distribution of disks and spheroids

  • Does the galaxy ends/IHSC starts for all

galaxies at X kpc?

  • Satellite particles never become part of the

central?

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From MW to ICL - simulations

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Our approach

``Equivalent’’ approach as observations

  • Galaxies are modeled/identified and diffuse

component is separated

How IHSC is measured in simulations?

Robustly

1) Identify Galaxies 2) Separate IHSC

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Source: Illustris Project

Group Central Galaxy

SUBFIND Poole et al., 2017 SUBFIND

Robust identification of galaxies

Common galaxy finding problems

GiggleZ-HR simulation

  • Particle assignment to density peaks
  • Identification of galaxies is different from dark matter haloes
  • Same algorithms and assumptions for dark matter haloes are used for

galaxy identification

  • Strongly interacting galaxies
  • Densely populated systems

(Groups and Clusters)

  • Delimitation of galaxies
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VELOCIraptor

FOF algorithm in 6D to find structures in simulations

  • Haloes
  • Streams
  • Shells

Elahi et al., 2011 Elahi et al., in prep

How do we solve this?

3D-FOF Field Search 6D-FOF Field Search 6D-FOF Iterative Core Search Phase-Space Core Growth

Modifications and improvements to robustly find galaxies in hydrodynamical simulations

Cañas et al. (arXiv:1806.11417)

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Galaxy Cluster HaloMaker VELOCIraptor

S m

  • t

h p r

  • f

i l e s ! A v

  • i

d i n c l u d i n g

  • t

h e r g a l a x i e s ’ s t a r s

C1 C2

Improvements of algorithm

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We get tidal features for free!

We can study the evolution

  • f the whole satellite population

as they go from Satelitte → satellite + Tidal → Tidal → IHSC

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Robust Identification of Galaxies

Galaxy Cluster

This features in IllustrisTNG

HaloMaker VELOCIraptor

Summary 1

  • Important to solve these

problems before analysis

  • Density profiles / stellar

population properties profiles can be affected 3D and 2D!

  • In principle we could use

identified streams to trace complete evolution from satellite to tidal feature to IHSC

Patrick Ondratschek’s poster

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Intra-Halo Stellar Component

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What does it look like?

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What does it look like?

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Follow the evolution of IHSC

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Follow the evolution of IHSC

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Follow the evolution of IHSC

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Follow the evolution of IHSC

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Follow the evolution of IHSC

z

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Individual system paths

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Individual system paths

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Individual system paths

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Individual system paths

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Individual system paths

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Individual system paths

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How about other simulations?

Coming on December 7th…… IllustrisTNG

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Compare different codes and different galaxy formation models Lets not forget Crain+2015 galaxy mass function can be reproduced by different prespcriptions with the right tunning

How about other simulations?

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How about other simulations?

Coming on December 7th…… IllustrisTNG

Poor statistics

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The 300

300 Galaxy Clusters from MultiDark Simulation Klypin et al., 2016

Credit: Alexander Knebe Mock Perth

Full physics re-simulations 4 codes - 2 Gadget

  • 2 Gizmo

How about other simulations?

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How about other simulations?

Coming on December 7th…… IllustrisT

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From MW to ICL - our results

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From MW to ICL - final comments

Statistics

  • 300 Project
  • IllustrigTNG-300
  • C-EAGLE
  • EAGLE-XL

Resolve IHSC

  • EAGLE boxes
  • Higher resolution

simulations

  • IllustrisTNG-50 ?

Resolution dependence, Convergence, Smoothness of IHSC

  • EAGLE boxes
  • Illustris (same IC different resolution)
  • 300 Project (same IC different resolutions and codes)
  • IllustrisTNG ?
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`

Morishita et al., 2017 Cañas et al., in prep

Simulation Mock Image Observations

Cluster ICL

Possible future projects

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Summary

  • Definition of Stellar Halo / ICL changes from study to study
  • We have presented a new method that can be applied to a wide range of

masses

  • We need to use the same method on different hydrodynamical simulations to

make fair comparisons

  • We need different simulations, codes, resolutions, to really be able to resolve

and have statistics at all stellar masses

  • Probably we can understand a little bit more (constrain?) better galaxy

formation model(s)

  • Comparison with observations is crucial
  • Having 3D information, we can project and apply observational methods

to see the differences

  • Open for comments, ideas, and most importantly collaborations!

Observations and Simulations!

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Thanks!

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  • Barnes, D., et al., 2017, MNRAS.471.1088B
  • Bullock & Johnston 2005, ApJ...635..931B
  • Buitrago F., et al., 2017 MNRAS.466.4888B
  • Contini, E., et al., 2014 MNRAS.437.3787C
  • Cooper A., et al., 2010, MNRAS.406..744C
  • Cooper A., et al., 2013, MNRAS.434.3348C
  • Cooper A., et al., 2015, MNRAS.451.2703C
  • Cooper A., et al., 2015, MNRAS.454.3185C
  • Cooper A., et al., 2017, MNRAS.469.1691C
  • Dubois Y., et al., 2014, MNRAS, 444, 1453
  • Elahi P. J., et al., 2011, MNRAS, 418, 320
  • Harmsen, B., et al., 2017, MNRAS.466.1491H
  • Huang, S., et al., 2018, MNRAS.475.3348H
  • Klypin, A., et al., 2016, MNRAS, 457, 4340

References

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References

  • Klypin, A., et al., 2016, MNRAS, 457, 4340
  • Martínez-Delgado, D., et al., 2010, AJ, 140, 962
  • Merritt, A., et al., 2016, ApJ, 830, 62
  • Monachesi, A., et al., 2018, arXiv:1804.07798M
  • Morishita, T., et al., 2017, ApJ...846..139M
  • Pillepich, A., et al., 2015, ApJ...799..184P
  • Rodriguez-Gomez, V., et al., 2016, MNRAS.458.2371R
  • Sanderson, R., et al., 2017, arXiv:1712.05808S