Python tool provides trusted calculations for geometric function theory problems
Geometric Function Atlas: certified computing for geometric function theory in Python
Mathematical Software
Summary
Calculations in geometric function theory can be tricky and require precise methods. The authors created a Python package called geometric-function-atlas to perform these calculations reliably using different levels of checking for accuracy. The tool uses a catalog of known mathematical functions to produce exact numbers and results with proofs that can be verified later. It also records detailed information about how each answer was obtained to ensure trustworthiness. This package helps researchers and users get certified correct answers for complex geometric problems.
geometric function theoryTaylor coefficientsFekete–Szegő constantMa–Minda functionspolynomial membership testingrational arithmeticinterval arithmeticcertified computingsymbolic algebraPython package
Authors
Kishan Gurumurthy, Pushparaj Devadiga, Prasanna Devadiga, Arya Suneesh, Asha Sebastian
Abstract
We describe geometric-function-atlas, our open-source Python package for the sharp extremal problems of geometric function theory. We organise it around a catalogue of thirty-nine Ma--Minda starlike generators. From this catalogue we compute exact Taylor coefficients, closed-form Fekete--Szegő constants, exact coefficients of the Ma--Minda extremal function, and admissibility screens. Our verifier answers membership questions for normalised polynomials at three levels of evidence: a floating-point grid screen, an exact sufficient condition decided in rational arithmetic, and a certified interval enclosure at the worst screened point. Every answer names the level at which we obtained it. We ship a checksummed artifact snapshot with three hundred and six coefficient certificates and seven hundred and two directed inclusion radii. Eight reviewed radius lanes carry certificates whose proof chains we replay symbolically, and we re-execute every coefficient certificate through our exact Schur-parameter machinery on request. We emit all results through one versioned envelope that records the method, the evidence status, the assumptions, and the artifact identifiers. Two optional laboratories apply the same discipline to cryptographic S-box metrics and to image-quality metrics. We present our design, state as propositions what each tier establishes, follow one radius lane from screen to replayed certificate, report measured timings, and place our package among symbolic-algebra, rigorous-numerics, and mathematical-database software. We release geometric-function-atlas under the MIT licence on the Python Package Index and at https://github.com/Prasanna28Devadiga/geometric-function-atlas.