The main results of the project are concerned with factor of IID processes. Such a process essentially describes the output of a randomized local algorithm on a regular tree (i.e. an infinite network with the property that it contains no cycles and each node has the same number of connections/neighbors).
It is an interesting question how independent the states (i.e. the random outputs on different nodes) of these algorithms are. A sharp upper bound had been known on the correlation of the states of two nodes at a given distance. In this project this result was extended: if one restricts such a process to two distant connected subgraphs of the tree, then the two parts are basically uncorrelated. The order of this correlation was determined in terms of the distance of the subgraphs. This is a quantitative version of the fact that factor of IID processes have trivial 1-ended tails. In the proof the spectral properties of the graph limit object, which is the regular tree in our case, were exploited in the form of the spectrum of the so-called non-backtracking operator.
Another notion that measures independence is mutual information known from information theory. Mutual information has the advantage over correlation that the latter only detects linear dependence. Therefore it is natural to study the mutual information of the states of two given nodes. If the nodes are connected (i.e. their distance is 1), then a known inequality provides an upper bound for the (normalized) mutual information. In this project upper bounds were obtained for nodes at an arbitrary distance. Although these bounds are sharp, it was also shown that an interesting phenomenon occurs here: for any fixed process the rate of decay of the mutual information is much faster. In other words, the order of the mutual information is different for a fixed process and for any process.
The project also made progress in the topic of entropy inequalities. Given a process, one can assign entropies to different finite subgraphs of a regular tree. There are linear inequalities between these entropies that hold for any factor of IID process. A new approach for finding and proving entropy inequalities was obtained in this project. The key tool in the proof is a generalization of the edge-vertex inequality for a broader class of factor processes with fewer symmetries.
This edge-vertex inequality was further generalized in the final months of the project: a hypergraph version was proved. A hypergraph is a network where edges/connections might involve more than one vertex/node. The paper containing these results is in preparation.
Dissemination:
Harangi has finished three research papers in this project. Two of them have already been accepted for publication. All three papers have been accepted by or submitted to Q1 (first quartile) journals. One further paper is in preparation.
Harangi also presented the results of this project in several research talks in various universities.
Harangi was invited to give a talk at a public event organized and hosted by the Hungarian Academy of Sciences where he spoke about the research carried out during the period of this project and about his experience with applying for and participating in a Marie Sklodowska-Curie grant.
Harangi was interviewed by an online mathematics portal (ematlap.hu). This was a perfect opportunity for him to popularize his research to a wider audience (not exclusively consisting of researchers but also high school and university students/teachers, and other mathematics enthusiasts).
For details see the project website www.renyi.hu/~harangi/msc/ listing research papers, talks (with slides and even video links when available), public engagement activities, etc.
