pub const DENSE_ENTRIES: usize = 250_000;Expand description
Up to this many entries the stationarity system is factored densely (a
thin SVD, rank by LAPACK’s threshold); above it, by the interior-point
method’s own sparse LDLᵀ of the least-squares augmented system
([sparse_least_squares]). The dense SVD’s cost grows as n·k²: on a
650-pair chain model (n = 1950) the solve took 4.8 s with the dense
certificate and 0.51 s with the sparse one, and at 1100 pairs 31 s
against 0.93 s, same class and answer. Below 2.5·10⁵ entries the SVD costs little and keeps the path
the certificate was validated on against stationarity.py (the Gate 0
corpus, bunny-hop, ball-in-cup); the CALIPSO rocket (n = 856) is past
it and certifies S on the sparse path exactly as it did densely. The
unit tests hold the two paths to the same class on every point they
check.