Once a die-hard pen and paper enthusiast, these days I’m getting a lot more interested in high-performance numerical techniques and in developing new tools to meet the challenges of modern research.
Having spent years determinedly avoiding learning to program, eventually I caved in and began working on numerical techniques in 2016 when I started work at the Institut de Physique Théorique.
Ultimately, physics is pretty complicated and very little of it can be solved exactly. We frequently have to make the choice between finding approximations and simplifications in order to proceed analytically (with pen and paper), or solve exact equations numerically using a computer. When the approximations we have to make become too cartoonishly removed from reality, or otherwise don’t cover the physics that we’re most interested in, then proceeding with a computer becomes the only option.
I use a mixture of Python (for ease of use), C (for performace), and Mathematica (for data processing and visualisation), and have experience using high-performance computational facilities.