How fast can we play Tetris greedily with rectangular pieces?

Consider a variant of Tetris played on a board of width ������ and infinite height, where the pieces are axis -aligned rectangles of arbitrary integer dimensions, the pieces can only be moved before letting them drop, and a row does not disappear once it is full. Suppose we want to follow a greedy strategy: let each rectangle fall where it will end up the lowest given the current state of the board. To do so, we want a data structure which can always suggest a greedy move. In other words, we want a data structure which maintains a set of ������(������) rectangles, supports queries which return where to drop the rectangle, and updates which insert a rectangle dropped at a certain position and return the height of the highest point in the updated set of rectangles. We show via a reduction from the Multiphase problem [Patra,scu, 2010] that on a board of width ������ = 0(������), if the OMv conjecture [Henzinger et al., 2015] is true, then both operations cannot be supported in time ������(������1/2-������) simultaneously. The reduction also implies polynomial bounds from the 3 -SUM conjecture and the APSP conjecture. On the other hand, we show that there is a data structure supporting both operations in ������(������1/2 log3/2 ������) time on boards of width ������������(1) , matching the lower bound up to an ������������ (1) factor.