Add notes about O(n) vs. O(n log n) make_heap issue

README.md

@@ -203,6 +203,9 @@ than O(n log n) time. In both cases, sorting the heap dominates the algorithm an
 original algorithm described by Bron & Hesselink or the revisited algorithm that I will describe later, both are split
 into these two distinct phases.
 
+*Note: I am actually wondering whether one of the `make_heap` functions described here runs in O(n), see the
+[corresponding issue](https://github.com/Morwenn/poplar-heap/issues/1).*
+
 ## Original poplar sort
 
 The original poplar sort algorithm actually stores up to log2(n) integers to represent the positions of the poplars. We
@@ -755,6 +758,9 @@ due to the insertion sort optimization, but also to the fact computing the size
 O(1) and not in O(log n). That said, the complexity is the same: O(n log n) time and O(1) space. We might not have
 found an O(n) algorithm to construct the poplar heap, but this one is definitely interesting.
 
+*Note: I am actually wondering whether this version of `make_heap` runs in O(n), see the [corresponding
+issue](https://github.com/Morwenn/poplar-heap/issues/1).*
+
 ## Additional poplar heap algorithms
 
 While these functions are not needed to implement poplar sort, the C++ standard library also defines two functions to