Abstract: In this talk, we present our results for the 1-bit phase retrieval problem: the recovery of a possibly sparse signal $x$ from the observations $y=sign(|Ax|-1)$. This problem is closely related to 1-bit compressed sensing where we observe $y=sign(Ax)$, and phase retrieval where we observe $y=|Ax|$. We show that the major findings in 1-bit compressed sensing theory, including hyperplane tessellation, optimal rate and a very recent efficient and optimal algorithm, can be developed in this phase retrieval setting. This is a joint work with Ming Yuan: https://arxiv.org/abs/2405.04733.