_acb_dirichlet_l_fmpq_use_afe, _acb_dirichlet_l_jet_use_afe

Return whether the approximate functional equation is estimated to be faster than the generic algorithms for $L(s,\chi)$, respectively for its expansion to length len, where $q$ is the conductor of $\chi$ ($q = 1$ for the Riemann zeta function). These are the heuristics used by acb_dirichlet_l, acb_dirichlet_l_fmpq, acb_dirichlet_l_jet, acb_dirichlet_zeta and acb_dirichlet_zeta_jet (and therefore by acb_dirichlet_stieltjes and arb_const_glaisher, which call acb_dirichlet_zeta_jet). The cutoffs come from timings (wall time) with 1 and 8 threads. They decrease with $q$ (for $q > 50$, values at half-integers, and for $q > 200$, jets, always use the approximate functional equation), and with the number of threads $T$ (flint_get_num_threads), since the terms of the approximate functional equation are computed in parallel with nearly perfect speedup while Euler–Maclaurin summation and the Hurwitz zeta functions gain less from threads. For $q = 1$ they are about $4 \cdot 10^4 T^{-1/2}$ bits for $\zeta(1/2)$, $10^5 T^{-0.9}$ bits for other values, $1.5 \cdot 10^5 T^{-1}$ bits for jets at $s = 1/2$ and $4.4 \cdot 10^5 T^{-0.8}$ bits for other jets of length 2 (somewhat higher for longer jets), the latter capped at $3.5 \cdot 10^5$ bits because of the $O(p^2)$ memory of Euler–Maclaurin summation (4 GB at $3.3 \cdot 10^5$ bits). The choice of algorithm, and hence the radius of the output, can therefore depend on the number of threads.