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How do you encode combinatorial optimization problems when they have inequality constraints on quantum computers? well, the usual approach is using slack variables. But, this approach is quite expensive and makes the search for possible solutions even harder. In this work, https://arxiv.org/abs/2211.13914, we present “unbalanced penalization” a new approach to encode the inequality constraints of combinatorial optimization problems.

Postprocessing routines to evaluate the results of the analysis of emission factors within the UBA project

Collection of software tools for the scientific community to facilitate access to and processing of TOAR data

This repository includes the simulation and figure generation code for Kölzer et al., Commun. Mater. 2, 116 (2021) [arXiv:2012.15118], [doi:10.1038/s43246-021-00213-3]

Source code and data corresponding to the publication 'Reliability and subject specificity of personalized whole-brain dynamical models'

Master's thesis on using quantum Boltzmann machines in quantitative finance.