Special Issue: Experiments in MathematicsVol. 1 No. S1 (2022)
The words "experiment" and "mathematics" perhaps seem disjunct to most readers. The idea that, throughout history, pure mathematicians very often experiment with playfulness before formulating theorems with austerity, is possibly unappreciated by most practitioners in STEMM who are not mathematicians. Yet, this is very much the case, and especially today, with the explosion of data in every quantitative field, "experimentation in mathematics" is more relevant than ever.
Imagine how much more the likes of Gauss would have conjectured and proven had they access to today's computing power and the internet that aids rapid communication!
For many years, Professor Yang-Hui He has been a passionate advocate for the dialogue between modern data science, theoretical physics, as well as pure and applied mathematics. Here, the "data" are of a peculiar type: they are noiseless, exact, and plentiful across all mathematical disciplines. Indeed, they at some level reveal the underlying structure of mathematics. Professor He had been one of the first to introduce the vast and topical subject of machine-learning to geometry, representation theory, number theory and mathematical physics. Since 2017, his team had been exploring how different branches of mathematics respond to machine-learning and AI techniques.
This experimental approach to mathematics, in a free-spirited fashion, unhampered by the boundaries which divide the subfields of mathematics, is very much in line with the interdisciplinarity and cross-fertility of ideas under which inSTEMM was founded. This special volume will consist of various experimentations in algebraic geometry, number theory and string theory and it is the hope of the inSTEMM Journal that it would engender further lively discussions amongst experts from different fields in pure and applied mathematical sciences.