  Implicit methods are attractive for hybrid quantum-classical CFD solvers as
the flow equations are combined into a single coupled matrix that is solved on
the quantum device, leaving only the CFD discretisation and matrix assembly on
the classical device. In this paper, an implicit hybrid solver is investigated
using emulated HHL circuits. The hybrid solutions are compared with classical
solutions including full eigen-system decompositions. A thorough analysis is
made of how the number of qubits in the HHL eigenvalue inversion circuit affect
the CFD solver's convergence rates. Loss of precision in the minimum and
maximum eigenvalues have different effects and are understood by relating the
corresponding eigenvectors to error waves in the CFD solver. An iterative
feed-forward mechanism is identified that allows loss of precision in the HHL
circuit to amplify the associated error waves. These results will be relevant
to early fault tolerant CFD applications where every (logical) qubit will
count. The importance of good classical estimators for the minimum and maximum
eigenvalues is also relevant to the calculation of condition number for Quantum
Singular Value Transformation approaches to matrix inversion.
