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talking_points.md
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talking_points.md
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# Comments for the presentation
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## Introduction
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---
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---
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---
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// COMMENTS:
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---
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// Explanation
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- further modulation by _RSD_
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// From first principles
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// small scales to resolve sources + sinks + feedback
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// large scales to capture statistics
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// IF ASKED: difference with `21cmFAST`:
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// based on excursion formalistm -> only valid >= 1Mpc, which is ideal for large volumes + statistics => 21-cm forecasts
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// interesting to build emulators for instance
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---
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// From the xray emission
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// primordial + heating term
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// expansion + deposition by xrays
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// => xrays are assumed to be the only source of heating
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// $
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// x_("HII")(r bar M, z) = theta_"H" lr([R_b (M, z) - r], size: #150%)
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// $
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---
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// COMMENTS:
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// - contribution from the lyman lines
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// - 1/r^2 decrease from spreading photons
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// - more steep outwards + sharp drop due to redshifting out of line
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---
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== Revisiting the 21cm signal
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---
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### Procedure
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Painting using all halos that match in a SINGLE step
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---
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OVERLAP EXPLICITLY ALLOWED
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---
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### Postprocessing
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- ionization overlaps
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- corrections due to RSD
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- computation of derived quantities
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- summary statistics
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---
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### Maps
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---
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### Signal
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---
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## Halo growth
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### Motivation
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### Effect on the flux profiles
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// COMMENTS
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// That will be directly affect the global signal as well
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// shifting
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//
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// Yu-Siu already investigated the more nuanced effect of stochasticity but the approach we propose should supersede that
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### Inferring growth from #smallcaps[Thesan] data
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// ideal for rapid iterations
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// in a parallelized fashion => want to stay fast
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// fix the original mass for max. consistency
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// fix the allowed dynamic range
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// this sort of "breaks the degeneracy" between halos of the same mass but different growth histories
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---
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RESULT OF LOADING:
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// COMMENTS:
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// no clear trend between mass and growth rate
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---
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## Adaptations
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---
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### Central changes
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// important since the bins are more now
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// largely through vectorization -> still "native" python
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// usage of HDF5
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// solid caching mechanisms -> resume simulations, etc...
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### Simplified usage
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In a page or less
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---
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## Results
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### Map outputs
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// the ones where the accretion rate is likely higher
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// in particular: no values where the coupling has become weaker
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// will become apparent in the signal as well
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---
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// those are the ones where the diff vanishes: e.g. top right
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---
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// more variation due to the different accretion rates
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---
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// Globally:
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// more dynamic range while the mean systematically shifts towards the (biased) lower accretion rates
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// Intermezzo - compare with lower alpha range - mostly similar but occasional contributions from higher alpha values
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// => recommend keeping a wide range since it does not affect performance (if the bins are empty anyway)
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// the more intersting discussion to be had is the effect of a more fine binning - thesan data already gives an indication which values will be most frequent
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// => the implementation to test that is there
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// the halos themselves produce a stronger singal while the background is usually
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---
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### Signals
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---
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## Conclusion
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---
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### Summary
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// since it affects the SFR and thus the emissivity
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// change in profiles trivially
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// which could in theory be absorbed by shifting other paremeters
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// which we can hope to observe (although many are subtle)
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// unique position of 21-cm cosmology -> cannot discuss observational constraints
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// invite you to check out
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### Outlook
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// finally ready for direct comparison with c2ray? now that parameters and loading have been properly implemented
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// Assuming other relations related to production of photons is (hopefully by now well motivated) complex
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// these cannot directly be inferred => expressed as a distribution as a function of another halo property
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// the scale-up -> large volumes with usable merger trees
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// comitting to reserving some 100s of node hours (which I would still quantify as fast)
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