Is there a point when computers have no return on investment of time? The longer a computer uses to analyze a position ... does it ever not improve its evaluation? Does it ever get worse?
Current engines are limited by their evaluation algorithms. They can only calculate to the best that their coding allows.
Alpha Zero highlighted some of the flaws in Stockfish 8's programming—SF8 thought it was doing fine in positions where AZ was actually winning.
Stockfish is a monster that uses centipawn values to weigh its lines. But the chess-playing AIs of the future might very well determine that centipawns are actually an inaccurate way to approach chess.
There is no doubt that they are. I can set up a legal position where Stockfish thinks it is 30 pawns up at 100 ply depth, and yet it is a dead draw. Chess is a game where the only significant thing is the final score, and the only reasonable proxy for that is an estimate of the final score (there may be nuances that differentiate between positions with the same expected score but different win probabilities, but these only matter if you are interested in something other than scoring highly).
chess.com announced today they have acquired Komodo with a new version adding Monte Carlo search and probabilistic assessments of this type, like a hybrid of AlphaZero or LeelaZero and a conventional chess engine.
AZ already seemed to hint at that: it approached the position with a clear emphasis on mobility, rather than pawn/piece values.
The reason for this was that its experience found that the combination of many positional factors was a better way of estimating the result than being excessively focused on material. A couple of the published games illustrate this stunningly.
You cannot detect perfect moves in the beginning of the game. Since you cannot do that, the idea of finding perfect games is quite silly, because you start with imperfect moves until the position is simple enough to let you find best moves. But because you started with imperfect moves the resultant lines/ games are not perfect. Obviously. You keep failing to address this anomaly in your thinking.