  We propose a resource-efficient shadow-tomography scheme using
equatorial-stabilizer measurements generated from subsets of Clifford
unitaries. For $n$-qubit systems, equatorial-stabilizer-based shadow-tomography
schemes can estimate $M$ observables (up to an additive error $\varepsilon$)
using $\mathcal{O}(\log(M),\mathrm{poly}(n),1/\varepsilon^2)$ sampling copies
for a large class of observables, including those with traceless parts
possessing polynomially-bounded Frobenius norms. For arbitrary quantum-state
observables, sampling complexity becomes $n$-independent. Our scheme only
requires an $n$-depth controlled-$Z$ (CZ) circuit [$\mathcal{O}(n^2)$ CZ gates]
and Pauli measurements per sampling copy, exhibiting a smaller maximal gate
count relative to previously-known randomized-Clifford-based proposals.
Implementation-wise, the maximal circuit depth is reduced to
$\frac{n}{2}+\mathcal{O}(\log(n))$ with controlled-NOT (CNOT) gates.
Alternatively, our scheme is realizable with $2n$-depth circuits comprising
$O(n^2)$ nearest-neighboring CNOT gates, with possible further gate-count
improvements. We numerically confirm our theoretically-derived
shadow-tomographic sampling complexities with random pure states and multiqubit
graph states. Finally, we demonstrate that equatorial-stabilizer-based shadow
tomography is more noise-tolerant than randomized-Clifford-based schemes in
terms of average gate fidelity and fidelity estimation for
Greenberger--Horne--Zeilinger (GHZ) state and W state.
