This report serves to finalize the bachelor graduation project on the topic of self-supervised federated learning, specifically the implementation of the algorithms in Python. The goal of the project is to implement a self-supervised learning setup in a decentralized approach using Field-Programmable Gate Arrays (FPGAs) for the processing of data. This serves as a proof of concept that decentralized machine learning on unlabeled data using FPGAs is possible. Multiple algorithms based on the literature were considered to allow for a low-profile learning setup, with simplifications done to be able to reduce the compute required. The results are promising: scaled-down models that can run on an FPGA show that self-supervised learning functions as expected from the theory. By decentralizing the computations increases in performance are possible in favorable conditions. The authors hope that the concept of self-supervised federated learning can be employed to FPGAs on a larger scale to help in the processing of the abundant yet underutilized unlabeled data present at the edges of information networks.

In the history of humankind only three spacecraft have ever ventured into interstellar space [2]. How- ever, none of them have been equipped for proper exploration of interstellar space, all of these five spacecraft were equipped for exploring the outer planets and objects of the solar system but not for interstellar space and/or the heliosphere. In part due to this lack of in-situ measurements of the inter- stellar medium and the heliosphere, not a lot is known of these areas. This report aims to provide a detailed overview of the concept of an interstellar heliosphere probe to investigate the heliosphere and the interstellar medium. This report will examine the requirements that are needed for such a spacecraft and explain why these requirements exist. Moreover, a component level description of the various subsystems typically involved in spacecraft manufacturing will be provided. With these subsystems, estimations of the mass, cost, power and data will be given when appropriate in an overview of all the subsystems.