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auto mpsi under-resolves the edge, giving spurious dW and Delta-prime #302
Description
With grid_type = log_asymptotic and automatic radial resolution (mpsi = 0), the
optimal-mpsi heuristic allocates very few edge grid points (about a dozen near the
boundary). The resulting edge under-resolution produces spurious ideal dW and
Delta-prime values, especially when a near-separatrix rational surface is captured.
Workaround: set a fixed mpsi (e.g. mpsi = 256), which resolves the edge and gives
stable dW / Delta-prime.
The fix should make the automatic mpsi selection allocate adequate edge resolution
(or warn when the edge is under-resolved). Note this is an auto-mpsi problem, not
log_asymptotic itself: log_asymptotic with a fixed mpsi is fine.
Activity
EQUIL - IMPROVEMENT - Update DIII-D-like example: edge-matched equili…
d-burg commentedon Jun 25, 2026
@logan-nc I scanned
psi_accuracywithlog_asymptotic+ auto-mpsi and compared againstldp+ fixedmpsi=256, checking the least-stable eigenvalue et[1] (the correct value, cross-checked against fortran DCON and the parallel-integration test, is ~0.80):So you were right that
psi_accuracyis the knob -- the default 1e-3 insufficiently populates the edge (N_edge=5) and gives a spurious δW, tightening to 1e-5 converges to theldpvalue.Cost is the problem -- the converged auto-grid needs mpsi ≈ 1012, and that total is dominated by N_mid=950, not the edge. The edge count grows much more slowly with
psi_accuracythan the mid does, so to get enough edge points you over-resolve the mid and end up ~4x the total knots for the same answer thatldpgets in 256. In other words the inefficiency here is the N_edge/N_mid imbalance inmake_optimal_mpsi, not core-packing inldp.Until this issue is resolved in a new PR, I'll keep
ldp+ fixedmpsi=256for the baseline in our #295 merge since it's both correct and ~4x cheaper. Once auto-mpsi resolves the edge efficiently,log_asymptotic+ auto-mpsi can go back to being the default and I'll re-pin the regression. Does this sound good to you?