About me

I have had many interests that have come and gone throughout my life, but physics and programming are two longtime passions of mine that have remained throughout the years. I pursued my interest in physics at the Ruhr-Universität Bochum, where I earned a bachelor’s and master’s degree in physics with a focus on computational solid state physics and machine learning. During this time I fell in love with Python and used it not only for my research but also for small projects in my spare time - from programming an Alexa skill to analyzing covid-19 infection data. Currently I am a PhD student at the Forschungszentrum Jülich and the University of Cologne with Matteo Rizzi.

Master Thesis

During my undergraduate studies I developed an interest in machine learning, which I strengthened by attending relevant courses at the Department of Neuroinformatics at the RUB. When it was time for my master thesis, I already had some experience with Monte Carlo simulations in the context of the Langevine equation for stochastic quantization and had played around with Restricted Boltzmann Machines for another class. After some research, I found that RBMs were being used to speed up Monte Carlo simulations and thought that a convolutional RBM, which is translationally invariant, would work better since many physical models are translationally invariant. I proposed this topic to my supervisor, Prof. I. Eremin, and was happy when he accepted it for a master’s thesis. During the master’s thesis I learned how to do research and especially how to do reproducible computational experiments, for which I wrote a small Python program called encap. I also learned how to keep up with the growing literature in the field.

“Analysis of the Ising and Kitaev Model Using the CRBM Aided Monte Carlo Method” is my master thesis, which I completed in the Ruhr Universität Bochum. A shortened and improved version of chapter 4, 5 can be found in preprint [1]. Chapter 6 remains unpublished. The main ideas can be explored in this Jupyter Notebook.

Publications

[1] D. Alcalde Puente and I. M. Eremin, “Convolutional restricted Boltzmann machine aided Monte Carlo: An application to Ising and Kitaev models”
Phys. Rev. B102,195148 (2020). Presentation

Projects

A simple tool to keep track of computational experiments.

A python library for parallel computing with little overhead.