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Aug 25, 2024 at 16:21 comment added Henrik Schumacher Also, it is not uncommon that the condition number increases with the size of the matrix. So this explain why Mathematica complained only about the larger problems.
Aug 25, 2024 at 13:07 comment added Henrik Schumacher Ill-conditioning has not effect if you use exact arithmetic. (But for larger problems, exact arithmetic will be too expensive.) Ill-conditioning does not mean that the matrix equation is not solvable. It just means that floating-point errors are likely to accumulate during the computations. This is why Mathematica warns you: The solution might have an error that is acceptable to your application or not. You have to check the quality of the solution yourself.
Aug 24, 2024 at 23:26 comment added Pedro Henrique @DanielLichtblau depends. When I utilize small matrixes the two results are identical. When I increase the size of the matrix it does not solve because “badly conditioning”. However, mathematica still solves the system of equation. I only got problem with matrix equation….
Aug 24, 2024 at 22:00 comment added Daniel Lichtblau Are the two results different? If so, that also would indicate bad conditioning.
Aug 24, 2024 at 21:23 comment added Pedro Henrique @MichaelE2 well I’m not getting any closer to the correct output :/
Aug 24, 2024 at 19:55 comment added Michael E2 @PedroHenrique "I do not understand why the matrix version cannot" -- What makes you think it did not?
Aug 24, 2024 at 17:33 comment added Pedro Henrique I do not know if that helps, but if I write the system of equations that results from m.x==b, extract the coefficients using CoefficientArrays[ ], and then use LinearSolve[ ], I get the correct answer without error messages. However, the method of creating the system of equations is quite slow, and I am trying to avoid it. Nevertheless, the system can be solved, so I do not understand why the matrix version cannot.
Aug 24, 2024 at 15:44 history answered Henrik Schumacher CC BY-SA 4.0