  The quantum advantage threshold determines when a quantum processing unit
(QPU) is more efficient with respect to classical computing hardware in terms
of algorithmic complexity. The "green" quantum advantage threshold $-$ based on
a comparison of energetic efficiency between the two $-$ is going to play a
fundamental role in the comparison between quantum and classical hardware.
Indeed, its characterization would enable better decisions on energy-saving
strategies, e.g. for distributing the workload in hybrid quantum-classical
algorithms. Here, we show that the green quantum advantage threshold crucially
depends on (i) the quality of the experimental quantum gates and (ii) the
entanglement generated in the QPU. Indeed, for NISQ hardware and algorithms
requiring a moderate amount of entanglement, a classical tensor network
emulation can be more energy-efficient at equal final state fidelity than
quantum computation. We compute the green quantum advantage threshold for a few
paradigmatic examples in terms of algorithms and hardware platforms, and
identify algorithms with a power-law decay of singular values of bipartitions
$-$ with power-law exponent $\alpha \lesssim 1$ $-$ as the green quantum
advantage threshold in the near future.
