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CONSTRAINING THE NATURE OF DARK MATTER WITH SUBSTRUCTURE LENSING: - PowerPoint PPT Presentation

CONSTRAINING THE NATURE OF DARK MATTER WITH SUBSTRUCTURE LENSING: PREDICTIONS FROM THEORY AND SIMULATIONS Giulia Despali Simona Vegetti Elisa Ritondale MPA - Garching Simon White Carlo Giocoli Mark Lovell Mark Vogelsberger Martin Sparre


  1. CONSTRAINING THE NATURE OF DARK MATTER WITH SUBSTRUCTURE LENSING: PREDICTIONS FROM THEORY AND SIMULATIONS Giulia Despali Simona Vegetti Elisa Ritondale MPA - Garching Simon White Carlo Giocoli Mark Lovell Mark Vogelsberger Martin Sparre Jesús Zavala Frank van den Bosch Miramare 02.07.2018

  2. CONSTRAINING THE NATURE OF DARK MATTER WITH SUBSTRUCTURE LENSING: PREDICTIONS FROM THEORY AND SIMULATIONS Giulia Despali Simona Vegetti Elisa Ritondale MPA - Garching Simon White Carlo Giocoli Mark Lovell Mark Vogelsberger Martin Sparre Jesús Zavala Frank van den Bosch Miramare 02.07.2018

  3. PREDICTIONS & NUMERICAL SIMULATIONS LINE-OF-SIGHT SIDM CONTRIBUTION (Despali, Sparre, Vogelsberger, Zavala, Vegetti et al in prep.) (Despali et al. 2018) impact of SIDM on the main halo 
 how many LOS haloes we expect 
 properties vs substructures in the main lens different distribution of Einstein 
 predictions for CDM vs WDM rings? subhalo counts and profiles STERILE NEUTRINOS …see Elisa’ s talk! (Despali, Lovell, Vegetti et al. in prep.) subhalo counts from sterile neutrino 
 WDM zoom simulations subhalo profiles, distribution and 
 lensing power spectrum

  4. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) lensing is sensitive to the whole mass distribution between the observer and the source Z z S Z M max n ( m, z ) dmdV N LOS = dz dz 0 M LOW ( z )

  5. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) lensing is sensitive to the whole mass distribution between the observer and the source Z z S Z M max n ( m, z ) dmdV N LOS = dz dz 0 M LOW ( z ) “EQUIVALENT LINE-OF-SIGHT” + used to rescale the sensitivity 
 + function at z ≠ z L + - - log M vir ( z ) = (0 . 41 x + 0 . 57 x 2 + 0 . 9 x 3 )

  6. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) n W DM = (1 + γ M hm M − 1 ) β n CDM CDM WDM 3.3keV

  7. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) n W DM = (1 + γ M hm M − 1 ) β n CDM CDM WDM 3.3keV current detection limit

  8. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) n W DM = (1 + γ M hm M − 1 ) β n CDM CDM future observations WDM 3.3keV current detection limit

  9. PREDICTIONS LINE-OF-SIGHT CONTRIBUTION (Despali et al. 2018) n W DM = (1 + γ M hm M − 1 ) β n CDM ratio subhaloes/line-of-sight CDM future observations WDM 3.3keV current detection limit the line-of-sight population dominates

  10. PREDICTIONS & NUMERICAL SIMULATIONS SUMMARY LINE-OF-SIGHT SIDM CONTRIBUTION the LOS population dominates 
 and provides cleaner constrains with better sensitivities we’ll be 
 able to discriminate CDM/WDM we need to be careful with mass 
 definitions STERILE NEUTRINOS

  11. SIMULATIONS STERILE NEUTRINO DM 2 x 10 13 M ⦿ 
 (Despali, Lovell et al. in prep.) 1 x 6 10 12 M ⦿ 
 - 4 ETG-analogues selected from the Eagle simulation 1x 4 10 12 M ⦿ re-simulated with 2 models of 7.1 keV sterile neutrino : L 6 = 8, 11.2 - DMO and hydro versions 
 - M SK [h -1 M O • ] 10 13 10 12 10 11 10 10 10 9 10 8 10 7 1000 Δ 2 = k 3 P(k) 100 CDM L 6 = 8.0, sin 2 (2 θ ) = 2.1x10 -10 L 6 = 9.0, sin 2 (2 θ ) = 8.1x10 -11 L 6 = 10.0, sin 2 (2 θ ) = 3.7x10 -11 L 6 = 11.2, sin 2 (2 θ ) = 2.1x10 -11 L 6 = 120.0, sin 2 (2 θ ) = 8.0x10 -13 10 1 1 10 100 200 k [h/Mpc] k [h/Mpc] z 0

  12. SIMULATIONS same number of “luminous” 
 STERILE NEUTRINO DM satellites - as in Lovell+16 difference in the “dark” population (Despali, Lovell et al. in prep.)

  13. SIMULATIONS STERILE NEUTRINO DM (Despali, Lovell et al. in prep.)

  14. SIMULATIONS STERILE NEUTRINO DM (Despali, Lovell et al. in prep.) Sterile Neutrinos “classic” WDM colder than the equivalent thermal 
 relic WDM model n W DM = (1 + γ M hm M − 1 ) β n CDM

  15. PREDICTIONS & NUMERICAL SIMULATIONS SUMMARY LINE-OF-SIGHT SIDM CONTRIBUTION the LOS population dominates 
 and provides cleaner constrains with better sensitivities we’ll be 
 able to discriminate CDM/WDM we need to be careful with mass 
 definitions STERILE NEUTRINOS the properties of the main lens remain similar slightly colder than the equivalent 
 thermal relic models fewer subhaloes 


  16. SIMULATIONS SELF-INTERACTING DM (Despali et al. in prep.) - 10 ETG-analogues selected from the Illustris simulation resimulated with SIDM + baryons - Vogelsberger et al. 2014

  17. SIMULATIONS SELF-INTERACTING DM subhaloes have on average more cored profiles (Despali et al. in prep.) might be degenerate with WDM abundances similar subhalo population

  18. SIMULATIONS SELF-INTERACTING DM (Despali et al. in prep.) the self-interaction influences the main 
 halo profile

  19. SIMULATIONS SELF-INTERACTING DM (Despali et al. in prep.) the self-interaction influences the main 
 halo profile in the presence of baryons things are more 
 complicated

  20. SIMULATIONS SELF-INTERACTING DM (Despali et al. in prep.) the self-interaction influences the main 
 halo profile in the presence of baryons things are more 
 complicated

  21. SIMULATIONS • Haloes from the Illustris and EAGLE main runs BARYONIC EFFECTS • M ~ 10 13 M ⦿ /h • z = 0.2, 0.5, 1 (Despali & Vegetti 2017)

  22. PREDICTIONS & NUMERICAL SIMULATIONS SUMMARY LINE-OF-SIGHT SIDM CONTRIBUTION similar subhalo population the LOS population dominates 
 but more cored sub profiles and provides cleaner constrains stronger effect on the main lens 
 with better sensitivities we’ll be 
 properties able to discriminate CDM/WDM ..depending on morphological 
 we need to be careful with mass 
 type? ..accretion history? definitions STERILE possible different Einstein 
 radii distribution NEUTRINOS the properties of the main lens remain similar slightly colder than the equivalent 
 thermal relic models fewer subhaloes 
 …we need to be careful 
 the baryonic physics 
 effects!

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