  Coalescing massive black hole binaries (MBHBs) are one of primary sources for
space-based gravitational wave (GW) observations. The mergers of these binaries
are expected to give rise to detectable electromagnetic (EM) emissions with a
narrow time window. The premerger detection of GW signals is vital for
follow-up EM observations. The conventional approach for searching GW signals
involves high computational costs. In this study, we present a deep learning
model to search for GW signals from MBHBs. Our model is able to process 4.7
days of simulated data within 0.01 seconds and detect GW signals several hours
to days before the final merger. The model provides the possibility of the
coincident GW and EM detection of MBHBs.
