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Constraining the cosmological parameters with X-ray galaxy clusters

Constraining the cosmological parameters with X-ray galaxy clusters. S.Ettori (INAF Bologna) P.Tozzi (INAF Trieste), F.Terenziani (Univ. Bologna), L.Lovisari (Univ. Bologna), S.Borgani (Univ. Trieste), P.Rosati (ESO) et al. Number density. Abundance of galaxy clusters is sensitive

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Constraining the cosmological parameters with X-ray galaxy clusters

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  1. Constraining the cosmological parameters with X-ray galaxy clusters S.Ettori (INAF Bologna) P.Tozzi (INAF Trieste), F.Terenziani (Univ. Bologna), L.Lovisari (Univ. Bologna), S.Borgani (Univ. Trieste), P.Rosati (ESO) et al.

  2. Number density Abundance of galaxy clusters is sensitive to the normalization (8) and shape (mh) of the present-day power spectrum Voevodkin & Vikhlinin 04 71

  3. Number density Abundance of galaxy clusters is sensitive to the normalization (8) and shape (mh) of the present-day power spectrum Reiprich 06

  4. Gas mass fraction To constrain the cosmological model Ωm +Ω+Ωk =1 We combine a dynamical and a geometricalmethod: • baryonic content of galaxy clusters is representative of the cosmic baryon fraction Ωb / Ωm(White et al. 93, …) • fgas is assumed constant in cosmic time in very massive systems (Sasaki 96, Pen 97, Ettori & Fabian 99, …)

  5. Gas mass fraction: the method 2= i(fbar, i / Y Ωb / Ωm)2 / i2 fbar, i = fgas, i + fstar, i fgas(<r500) = Mgas/ Mtot dang (m,, w) 3/2 fstar = 1.640.10 e-2 (Mtot / 3e14) -0.26 0.09(Lin et al. 2003) = 0.1-0.2 fgas Ωb h2= 0.0189 ±0.0010 (PN, Burles et al. 01), Ωb h2= 0.0223 ±0.0008 (CMB, Spergel et al. 06), H0 = 72 ± 8 km/s/Mpc (Freedman et al. 2001).

  6. Gas mass fraction: Y(z) Y500= 0.903 (±0.004) +0.048 (±0.010) z R500 R500 Ettori et al. 06

  7. Chandra data for 56 clusters @ 0.14<z<1.24 (Rosati et al. 02, Ettori et al. 03 & 04, Tozzi et al. 03, Balestra et al. 06)

  8. An example: RXJ1252, z=1.235

  9. A front is there:cold or hot?

  10. An example: RXJ1252, z=1.237

  11. An example: RXJ1252, z=1.237

  12. An example: RXJ1252, z=1.237 R500 = 0.592 (0.547, 0.741) Mpc (H0=70, m=1-  =0.3) fgas= 0.097 (0.062, 0.120)

  13. The sample: 56 hot clusters

  14. Constraints on Ωm- Ω Ωm= 0.23 (0.20, 0.29) Ω=0.79 (<1.25) at 2 (95.4% 1 param)

  15. Constraints on Ωm- Ω

  16. Constraints on Ωm- w Ωm= 0.22 (0.14, 0.27) w = -1.36 (-3.18, -0.45) at 2 (95.4% 1 param)

  17. Complementary constraints on DE Rapetti, Allen & Weller (2005) • Three data sets: SN, CMB • (WMAP1st+CBI+ACBAR) and • Clusters • Marginalized constraints (68.3%) • w0 = -1.05 ±0.11 • Wm = 0.29 ±0.03

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