Need resources for solving nonlinear matrix equations

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Discussion Overview

The discussion centers around finding resources and methods for solving nonlinear matrix equations of the form (Ax).*(Bx) + Cx = d, where A, B, and C are non-unitary square matrices, and x and d are column vectors. The scope includes theoretical approaches and potential applications in fluid dynamics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant notes that the equation can be viewed as a system of multivariate quadratic equations rather than a matrix equation, suggesting that it may not have a unique solution.
  • Another participant mentions methods for finding symbolic solutions to multivariate polynomial equations, specifically Buchberger's algorithm and Wu's method, while questioning if the matrix representation implies any special properties for the solutions.
  • A different participant indicates that they can find solutions using linearization and iteration, suggesting the existence of multiple solutions under certain conditions related to the magnitudes of C, A, and B.
  • Another perspective compares the equation to a Quadratic Programming problem, proposing that it might be reformulated for minimization or related to multi-dimensional root-finding techniques.

Areas of Agreement / Disagreement

Participants express varying viewpoints on the nature of the equation and the methods for solving it, indicating that multiple competing views remain without a consensus on the best approach or the nature of the solutions.

Contextual Notes

There are limitations regarding the assumptions made about the existence and uniqueness of solutions, as well as the dependence on the definitions of the terms involved in the equations.

Kosh Naranek
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In my work I've encountered equations of the type:

(Ax).*(Bx) + Cx = d

Where A,B and C are non-unitary square matrices, x and d column vectors and .* denote component-wise multiplication.

I have a few books which discuss nonlinear matrix equations, but not of this kind. Any suggestions?
 
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Kosh Naranek said:
(Ax).*(Bx) + Cx = d

Where A,B and C are non-unitary square matrices, x and d column vectors and .* denote component-wise multiplication.

If you want to solve for the vector x, I wouldn't call the equation a "matrix" equation since there is no unknown matrix. It would be equivalent to a system of multivariate quadratic equations in the components x1,x2,.. of the vector x.

Systematic ways to find symbolic solutions to multivariate polynomial equations are Buchberger's algorithm and Wu's method (called "Wu's method of the characteristic set" in the Wikipedia and "Wu's method of elimination" in other sources).

Of course it's an interesting mathematical question whether the fact that your equation is compactly stated as an equation with matrix coefficients implies that there is something special about the simultaneous quadratic equations, something that would make their solutions have a special form, perhaps a form that could be expressed concisely using matrices. I don't know whether that's the case.
 
Thank you. Perhaps I should mention that I can find a solution using linearization and iteration. The physical origins is in a branch of fluid dynamics. Typically one assume only one solution. However I think that there should be several solutions, at least if |C| is small compared to |A| and |B|.
 
Hi, Kosh.

That equation looks very similar to a Quadratic Programming problem:
minimize F(x) = (1/2) xT[H]x + cT x + α .
Except in your case you are trying to zero the function, not minimize it.
I wonder if it could be turned into such a problem with a little manipulation.

Alternately, it might be a problem appropriate for multi-dimensional root-finding.
Given N equations in N unknowns, in which the equations are non-linear, find a zero.
Do a search for "multi-dimensional root-finding". You will find a lot of information, and several algorithms.
 

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