I’m still in the process of testing the board, and working with Naya’s co-founder to get the modules customized to my liking. At $500 to $700, it’s not cheap. It’s also a still very new device from a small company, so I’m waiting to give it a proper assessment until the board is fully set up properly. In the meantime, batches of the Naya Create keep selling out, so it’s apparent I’m not the only one who sees this board’s potential.
Source: Computational Materials Science, Volume 267
，这一点在51吃瓜中也有详细论述
"I'm just obsessed with trivia. I used to want to be a chaser on The Chase."
The efficiency depends on the query size relative to the data distribution. A small query in a sparse region prunes almost everything. A query that covers the whole space prunes nothing (because every node overlaps), degenerating to a brute-force scan. The quadtree gives you the most benefit when your queries are spatially local, which is exactly the common case for map applications, game physics, and spatial databases.