Interior-point conditioning — the series
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A condition number sent to infinity
An interior-point method manufactures an ill-conditioned matrix on every iteration, deliberately, because the separating of a diagonal is how it discovers which constraints are active. Written one way the answer keeps fifteen digits at a condition number of 3·10¹⁵. Written the other way — the way almost every code writes it — it has none left.
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The active set before the digits
An interior-point method takes fifteen iterations on a quadratic programme with forty constraints, and its iterate has eight correct digits at the eleventh. Take the constraints its diagonal calls active at the first iterate, solve the equality problem they define once, and check the answer against the conditions for optimality. It passes, to thirteen digits. The step's matrix had a condition number of 43 at that iterate, and 7·10¹⁵ at the last.
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Two repairs for one symptom
Rescale a quadratic programme's constraint rows over six decades and the crossover that certified its answer at iterate 1.5 first certifies at 69.8, with two of six programmes never certifying at all. Normalising the rows removes the spread completely — the same numbers at 10¹, 10² and 10³ either way. Starting the method at the magnitudes the rows imply repairs the iteration count completely and the identification only halfway. They are two repairs and they fix different halves.
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A test with no tolerance in it
An interior-point method's own stopping test is a tolerance on μ, and at the tightest it can be set to it stops after 15 iterations with 1.6·10⁻¹². A crossover from the iterate at 1.5 returns a point whose error is 1.8·10⁻¹⁴ — ten times sooner and a hundred times better, from an iterate carrying one correct digit. One attempt costs an eighth of a step, and the guess's own margin says which iterate to spend it on.