  We consider the problem of reconstructing a signal $f$ from its spectrogram,
i.e., the magnitudes $|V_\varphi f|$ of its Gabor transform $$V_\varphi f
(x,y):=\int_{\mathbb{R}}f(t)e^{-\pi (t-x)^2}e^{-2\pi \i y t}dt, \quad x,y\in
\mathbb{R}.$$ Such problems occur in a wide range of applications, from optical
imaging of nanoscale structures to audio processing and classification. While
it is well-known that the solution of the above Gabor phase retrieval problem
is unique up to natural identifications, the stability of the reconstruction
has remained wide open. The present paper discovers a deep and surprising
connection between phase retrieval, spectral clustering and spectral geometry.
We show that the stability of the Gabor phase reconstruction is bounded by the
reciprocal of the Cheeger constant of the flat metric on $\mathbb{R}^2$,
conformally multiplied with $|V_\varphi f|$. The Cheeger constant, in turn,
plays a prominent role in the field of spectral clustering, and it precisely
quantifies the `disconnectedness' of the measurements $V_\varphi f$.
  It has long been known that a disconnected support of the measurements
results in an instability -- our result for the first time provides a converse
in the sense that there are no other sources of instabilities.
  Due to the fundamental importance of Gabor phase retrieval in coherent
diffraction imaging, we also provide a new understanding of the stability
properties of these imaging techniques: Contrary to most classical problems in
imaging science whose regularization requires the promotion of smoothness or
sparsity, the correct regularization of the phase retrieval problem promotes
the `connectedness' of the measurements in terms of bounding the Cheeger
constant from below. Our work thus, for the first time, opens the door to the
development of efficient regularization strategies.
