Just installing Maple 2023 on my office machine (a mac); installed it on my travel computer (a Surface Pro running Windows) yesterday.
Configured Jupyter notebooks to use the 2023 Maple Kernel and it all went smoothly. I was *delighted* to notice that plotting Lambert W in Jupyter with the command
plot( [W(x), W(-1,x)], x=-1..4, view=[-1..4, -3.5..1.5], colour=[red,blue], scaling=constrained, labels=[x,W(x)] );
produced a *better* plot near the branch point. This is hard to do automatically! It turns out this is a side effect of the better/faster/more memory efficient adaptive plotting software, which I gather from "What's New" was written for efficiency not for quality. But the quality is better, too! Nice!
I am working my. way through the "What's New" and I'm really pleased to learn about the new univariate polynomial rootfinder, *not least because it cites the paper describing the algorithm*. Lots of other goodies too; the new methods of integration look like serious improvements. Well done. (One thing there: "parallel Risch" is a term of art, and may lead people to believe that Maple is doing something with parallel computing there. I don't think so. Could a reference be supplied?)
The new colour schemes and plotting features in 3d and contour plotting look fabulous.
Direct Python language support from a code edit region is not at all what I expected to see---I wonder if it will work in a Jupyter notebook? I'm going to have to try it...
I'm quite impressed. The folks at Maplesoft have been working very hard indeed. Congratulations on a fine release!