Here I collect and organise the code developed as part of my research.
Each subdirectory is associated to a specific project and it includes the simulation scripts, postprocessing routines and plotting utilities for reproducibility.
In each subdirectory a README file explains the main content of the project and provides a description of each experiment in exp/.
If you are interested in a particular work you can follow one of the links listed below.
These are repositories associated to peer-reviewed papers that have been Published in a scientific journal.
- Quadrature of functions with endpoint singular and generalised polynomial behaviour in computational physics (2024, external repository).
- The neural network shifted-proper orthogonal decomposition: a machine learning approach for non-linear reduction of hyperbolic equations (2022, external repository).
Under review projects are works whose manuscripts have been submitted to a journal and are under peer-review. If accepted, they are promoted" to Published repositories; if rejected, that's life I guess '¯_(ツ)_/¯.
In progress are projects whose manuscript is currently being typed and close to submission.
- Dynamics, bifurcations and extensions of models of unified growth (Late 2026, estimated).
- Optimal and skilfull prediction of high-dimensional tipping events (Late 2026, estimated).
Projects at the Preliminary investigation stage are in early development, meaning that test cases and theoretical advancement are currently being researched.
- Localised patterns of the Lugiato-Lefever equation in 2 dimensions.
- Rate-induced tipping in a feedback-controlled, game-theoretic model.
- Characterisation of rate-induced tipping on parameteric families of parameter shifts.
- Nonlinear neural reduced manifold reconstruction of parametrised hyperbolic PDEs.
- Just a bunch of uncategorised tests.
A fair question to ask.
I strongly believe that scientific progress should be as transparent as possible. This, in my opinion, not only comes in the form of open access publications but also in the data that we collect and in the software that we use.
Now more than ever before, the scientific community relies on computational resources, simulations and high-performance scientific computing, not only to validate their hypothesis, but to formulate their theories in an increasingly stronger fashion. It is astonishing to me that, despite this, many (many, many, many, many...) peer-reviewed papers that heavily use these tools do not provide nor share the code they used in the production of the manuscript (e.g. in figures).
Not only this is hugely disripectful to developers (and sometimes fellow academics) who invested a considerable amount of time and effort to build these amazing tools we all use (in one way or another) to carry out our scientific investigations, but it is also hindering the process of actual peer-review (the one that happens AFTER the paper gets published) while contributing to the ongoing reproducibility crisis in science.
I thus think I should not be alone in making these sort of repositories, especially in an age in which text-based large-language models trivialized a lot of technicalities away in setting up systems like this one.
So if you are reading this, you find this repository useful, you are a fellow member of the scientific community AND you haven't yet created your own, please consider doing so. You will be providing a great service to the rest of us.