1 / 14

GBT 21 cm intensity mapping collaboration

GBT 21 cm intensity mapping collaboration. Academia Sinica (Tzu-Ching Chang, Victor Yu-wei Liao ) Beijing (Xuelei Chen, Yi-Chao Li ) Carnegie Mellon University ( Aravind Natarajan , Jeff Peterson, Tabitha Voytek )

diem
Télécharger la présentation

GBT 21 cm intensity mapping collaboration

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. GBT 21 cm intensity mapping collaboration • Academia Sinica (Tzu-Ching Chang, Victor Yu-wei Liao) • Beijing (Xuelei Chen, Yi-Chao Li) • Carnegie Mellon University (Aravind Natarajan, Jeff Peterson, Tabitha Voytek) • CITA/UToronto (Nidhi Banavar, Liviu Calin, Adam Lewis, Kiyo Masui, Ue-Li Pen, Richard Shaw, Eric Switzer) • McGill (Kevin Bandura)

  2. ARAA review article May 2010 (Morales and Wyithe) comparing to z ~ 10: Two months later:

  3. IM: now and then

  4. RFI Liu and Tegmark 2011

  5. The real data

  6. Signal-only simulations 20 Mpc ΩHI = 10-3

  7. Relaxed quadratic estimation Most general: Inverse covariance, down-weight foreground in both angle and frequency. Imperfect spectral baseline – need non-parametric removal: SVD on cross maps Liu & Tegmark MNRAS, Volume 419, Issue 4, pp. 3491-3504. Projecting (idempotent) LOS modes is “good enough” vs. optimal downweighting. These suggest that our method is slightly sub-optimal (in theory), but ideal in practice because we use the covariance of the real data!

  8. SVD eigenvalues Eigenvalue Mode number (sorted) Modes falling off rapidly: few DOF to describe most of the foregrounds.

  9. Real data, cleaned (25 modes removed here.)

  10. Cross-pairs: GBT power ( Weight A ) * Map A ( ) Weight B × * Map B

  11. Cross-pairs: WiggleZ crosspower ( ) Weight A * Map A ( ) Selection function × * Galaxy catalog

  12. Preliminary

  13. Fisher-matrix predictions

  14. Conclusions • End-to-end demonstration: calibration, ionosphere, point sources, galaxy, spectral response, etc. No show stoppers. Lessons learned for EoR. • Foreground subtraction under control: ready for z~1 21cm intensity mapping. • Consistent autonomous 21cm maps and power spectra. • Proposal for GBT 0.5<z<1 BAO survey using new ASIAA 9 pixel receiver array starting 2013. • Retires major risk for CHIME!

More Related