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To design our experiments, we'll need to have a clear picture of the landscape of different modeling methods, including the quadratic estimator. Related key issue: #4 |
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The goal is here to create a list of experiments to be run for the least publishable unit for the CMB cosmology inference using SBI and MCMC. Here are some initial ideas:
Impact of which parameters we constrain
For example, we can fix one of r, A_s or constrain both. Functionality to vary only these two cosmology parameters is currently available via DeepCMBsim.
Impacts of the noise model
DeepCMBsim has poisson noise but we could construct toy models for more complicated models, e.g., those that couple different modes.
Galactic foregrounds
These are most intuitive to deal at the map level -- which may require development in DeepCMBsim -- but we could proceed with e.g., complex noise models that capture the essence of the foregrounds.
We can think about whether we still want to do a 2-point analysis (i.e., the data vector will be a power spectrum; this will be the simplest way to do a 1-1 comparison between SBI and MCMC) or if we want to work with maps right away (on top of a 2-point analysis).
Let's use this thread to discuss things and finalize the experiments list for the first least publishable unit, alongside keeping track of any ideas for future R&D.
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