Implement modAB algorithm for efficient root-finding

### Feature description

This is a new and extremely efficient bracketing root-finding algorithm. It combines initial bisection steps with Anderson-Bjork's (AB) steps to achieve superlinear convergence (e.i. = 1.7-1.8), preserving optimality in worst case poorly behaved functions. ModAB uses clever method switching criteria, based on actually measuring the function linearity. According to the benchmarks, it **significantly outperforms** "classical" algorithms like ITP, Brent and Ridders:

|Method |bs |fp |mfp |ill |AB |ITP |mAB |Rid |Bre |
|------:|----:|----:|----:|----:|----:|----:|----:|----:|----:|
|SUM |4176 |7709 |2089 |2684 |2700 |2581 |1227 |1990 |2625 |
|AVERAGE |46 |85 |23 |29 |30 |28 |13 |22 |29 |
|MAX |48 |200 |71 |200 |200 |50 |48 |78 |133 |

Legend:
bs – Bisection method
fp – False position
mfp – Modified false position
ill – Illinois method
AB – Anderson-Bjork
ITP – Interpolate, truncate, project
mAB – Modified Anderson-Bjork (new)
Rid – Ridders
Brе – Brent

More detailed results are provided here:
https://github.com/Proektsoftbg/Numerical/blob/main/Numerical.Benchmark/doc/Root/Root-tests.pdf

### Additional context

The algorithm is presented in this paper:
https://iopscience.iop.org/article/10.1088/1757-899X/1276/1/012010

Here is the C# source code:
https://github.com/Proektsoftbg/Numerical/blob/main/Numerical/Solver/ModAB.cs

The algorithm is currently implemented in [Calcpad](https://github.com/Proektsoftbg/Calcpad), Jacob Willam's NASA/JSC [root-fortran](https://github.com/jacobwilliams/roots-fortran) and [Julia/NonlinearSolve.jl](https://github.com/SciML/NonlinearSolve.jl).