  Atom gradiometers have emerged as compelling broadband probes of scalar
ultralight dark matter (ULDM) candidates that oscillate with frequencies
between approximately $10^{-2}$ Hz and $10^3$ Hz. ULDM signals with frequencies
greater than $\sim 1$ Hz exceed the expected Nyquist frequency of atom
gradiometers, and so are affected by aliasing and related phenomena, including
signal folding and spectral distortion. To facilitate the discovery of
super-Nyquist ULDM signals, in this work we investigate the impact of these
effects on parameter reconstruction using a robust likelihood-based framework.
We demonstrate that accurate reconstruction of ULDM parameters can be achieved
as long as the experimental frequency resolution is larger than the ULDM signal
linewidth. Notably, as ULDM candidates whose frequencies differ by integer
multiples of the sampling frequency are identified at the same aliased
frequency, our discovery analysis recovers discrete islands in parameter space.
Our study represents the first comprehensive exploration of aliasing in the
context of dark matter direct detection and paves the way for enhanced ULDM
detection strategies with atom gradiometers.
