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The main aim of this repository is to provide Continuous Integration (CI) to other projects in a simple way.

Other projects can include jobs from this repo to enhance their own CI.

test project to test chat gpt

Jupyter notebook for generating instances of the garden optimization QUBO problem.

MF-LBM: A Portable, Scalable and High-performance Lattice Boltzmann Code for DNS of Flow in Porous Media

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.

A teeny tiny demo of how to publish your code on GitLab to Zenodo, following good practices with Citation File Format and CI/CD.

⚠️ NOTE :: THIS DOES NOT WORK YET :: NOTE ⚠️

Tool for generating random exact-cover problems. It prints out the exact-cover matrix and the unique ground state.