Nonlinear eigenvalue problem — where it appears
Named by 11 essays across 3 fields — each of them below, with the objects they name alongside it.
A problem with infinitely many eigenvalues
Let the matrix depend on λ through something that is not a polynomial and three things stop being true at once. There is no linearisation, there is no characteristic polynomial, and "compute the spectrum" is not a request that can be granted — the only finite question is how many eigenvalues are inside this circle.
The problem the solver was actually given
A linearisation is exact — it has the polynomial's eigenvalues, with their multiplicities, and the whole loss is arithmetic. A nonlinear eigenvalue problem does not offer that. Every algorithm replaces the function first, and the term that replacement contributes is committed before any number is rounded and appears in no residual.
The last digit is the cheapest
Every cost curve measured here has the same shape: the first digits are cheap and the last ones are not. One method inverts it. Doubling the work buys twice as many digits as the previous doubling did, so the price of a digit halves every time it is paid.
An error committed before the arithmetic
Before a nonlinear eigenvalue problem is solved, somebody says where they think the eigenvalues are. That sentence sets the accuracy of everything that follows by five orders, costs nothing to say, and cannot be revised once the approximation built on it is in hand.
Counting what is inside a circle
A trace of a matrix nobody wants to form, integrated around a contour, gives an integer — how many eigenvalues are inside. It converges exponentially, it is estimated with random probes, and the probe block is a ceiling that the answer does not mention.
The eigenvalues that are answers to nothing
A rational approximant of degree five turns a six-by-six problem into a thirty-six-by-thirty-six one, and thirty-six numbers come back. Six are the answer. The rest are exact eigenvalues of the approximant, lying where the function it approximates is not a real number at all.
A ceiling with a knob on it
A contour method returns at most as many eigenvalues as its probe block has columns, and the object that comes back does not distinguish that from having found everything. One line of the derivation multiplies the ceiling by a number the caller chooses, and it costs no extra solves at all.
The conditioning that rises with the ceiling
Higher moments multiply a contour method's ceiling by K and grade its block Hankel over ρ to the 2K, so the two knobs are the same knob. One division per quadrature point separates them, and the measurement of what it is worth grows from twenty to twenty thousand.
Where a contour's budget should go
A contour method's ceiling is the number of probes times the number of moments, and the moments are free in solves while the probes are not. Four ways of reaching one ceiling come out four orders apart, the ordering is not monotone, and what separates the best two is not the usual draw but the unlucky one.
The circle between two eigenvalues
A contour count's error is not approximately governed by the nearest eigenvalue; it is exactly one closed-form term per eigenvalue, and summing those terms reproduces the quadrature to a millionth at 1,720 radius and point pairs. Three things follow. The rate is the ratio of the two moduli the circle sits between, not a distance, so two circles 0.2 from their nearest eigenvalue converge three times apart. Ten digits cost about 21 points divided by log₁₀ of that ratio, 71 points with twelve eigenvalues inside and 3,476 with six. And the best circle is not halfway: at the geometric mean of two eigenvalues on one ray their two terms are equal and opposite, and ten digits cost 27 points where the midpoint needs 84.
A centre that chooses which pair cancels
A contour count's error is one closed-form term per eigenvalue, and two real eigenvalues on one ray cancel at their geometric mean — about the origin. Moved along the real axis, the centre was predicted to buy a further factor of two by putting real eigenvalues on two rays, the far one cancelling with a sign flip. The flip is parity: an eigenvalue behind the centre changes sign only at odd point counts. The factor is not two. Counting the delay problem's first two and three real eigenvalues, the best centre costs 22 and 21 points against the origin's 41 and 78; counting all four, 32 against 341, because about the origin the circle has to pass between a real eigenvalue and a complex pair and about 2.3 it does not. The centre does not add a cancellation. It chooses which pair cancels and pushes everything else away.
Named alongside it
The objects these essays reach for when they reach for this one.
Contour integralQuadratureExact ground truthContour eigensolverCondition numberRankApproximation before linearisationArithmetic costComplex arithmeticConvergence rateMomentNumerical rank