[HACK] LFI on neutrino mass (cosmological sims already done!)

[liuxx479]

LFI on neutrino mass from cosmology

We have 100 cosmological models (x 10,000 map realizations each) and computed higher-order statistics (power spectrum, bispectrum, PDF, peak counts) on all of them. We would like help to apply LFI on them.

Contacts: Jia Liu Participants: Jia Liu, Will Coulton

Goals and deliverable

Get a posterior using an (or multiple!) LFI method(s), and compare that with our (already done) Gaussian-likelihood result.

Resources needed

We will use statistics computed already from the MassiveNuS simulation: http://columbialensing.org/#massivenus

Detailed description

More like questions:

1. what do we need? mean and variance at each of the 100 models? or the full distribution instead of variance. If latter, I want to see the difference between the 2.
2. how do we scale to a different sky coverage that's different than our simulation size? (e.g. normally we multiple our covariance matrix by a number..)

[liuxx479]

download simulation file: https://www.dropbox.com/s/acirc59926b0ggz/Peaks_MassiveNuS.zip?dl=0 run jupyter notebook: LFI_hack.ipynb you will have: (1) param array with shape (101, 3) for 101 models, 3 parameters: M_nu, Omega_m, A_s (2) data_sim with shape (101, 9999, 50) for 101 models, 9999 realizations, 50 bins

[liuxx479]

shared google doc to keep track: https://docs.google.com/document/d/1jmH1rVQgc1PoD7RcnqH1bFl0_XZCcFHNMn9HfdVZ6RU/edit?usp=sharing

[changhoonhahn]

here's an hdf5 file for the data in case that's easier to access: https://www.dropbox.com/s/an81vjtisg2bwxj/MassiveNuS.hdf5?dl=0