nearly fully fleshed out now

refinements.typ

@@ -21,7 +21,12 @@
     #pause
   ],
   [
-    ...
+    $->$ inaccurate when applied to all halos
+
+    $->$ #text(weight: "bold")[inconsistent] with the N-body output
+
+    #pause
+    $->$ stochasticity for a more realistic description?
   ]
 )
 
@@ -31,13 +36,41 @@
 
 #image_cell(notebook, cell_id: "profile_plot_alpha_dependence")
 
+$M_"h" = 6.08 dot 10^11 M_dot.circle$ (fixed)
+
+$==>$ correction up to $times 5$
+
+// COMMENTS
+// That will be directly affect the global signal as well
+// shifting
+//
+// Yu-Siu already investigated the more nuanced effect of stochasticity but the approach we propose should supersede that
+
+#pagebreak()
 
 == Inferring growth from #smallcaps[Thesan] data
-#lorem(50)
+- already includes precomputed merger trees @Springel2005
+// ideal for rapid iterations
+
+- follow main progenitor branch back in time
+
+- fit the exponential model to main progrenitor branch
+// in a parallelized fashion => want to stay fast
+// fix the original mass for max. consistency
+// fix the allowed dynamic range
+
+- use *individual growth* to select profile
+// this sort of "breaks the degeneracy" between halos of the same mass but different growth histories
+
+- *self-consistent*#pause$*$#meanwhile treatment of halo growth leveraging the snapshots
+
+
+#pagebreak()
+
 #let notebook = json("../workdir/11_visualization/show_trees.ipynb")
 #[
   #set image(width: 100%, fit: "contain")
   #image_cell(notebook, cell_id: "merger_tree_and_fitting")
 ]
-
-
+// COMMENTS:
+// no clear trend between mass and growth rate