On combinatorial structures in linear codes

In this work we show that given a connectivity graph $G$ of a $[[n,k,d]]$ quantum code, there exists $\{K_i\}_i, K_i \subset G$, such that $\sum_i |K_i|\in \Omega(k), \ |K_i| \in \Omega(d)$, and the $K_i$'s are $\tilde{\Omega}( \sqrt{{k}/{n}})$-expander. If the codes are classical we show instead that the $K_i$'s are $\tilde{\Omega}\left({{k}/{n}}\right)$-expander. We also show converses to these bounds. In particular, we show that the BPT bound for classical codes is tight in all Euclidean dimensions. Finally, we prove structural theorems for graphs with no "dense" subgraphs which might be of independent interest

Local Treewidth of Random and Noisy Graphs with Applications to Stopping Contagion in Networks

We study the notion of local treewidth in sparse random graphs: the maximum treewidth over all k-vertex subgraphs of an n-vertex graph. When k is not too large, we give nearly tight bounds for this local treewidth parameter; we also derive nearly tight bounds for the local treewidth of noisy trees, trees where every non-edge is added independently with small probability. We apply our upper bounds on the local treewidth to obtain fixed parameter tractable algorithms (on random graphs and noisy trees) for edge-removal problems centered around containing a contagious process evolving over a network. In these problems, our main parameter of study is k, the number of initially "infected" vertices in the network. For the random graph models we consider and a certain range of parameters the running time of our algorithms on n-vertex graphs is 2^o(k) poly(n), improving upon the 2^?(k) poly(n) performance of the best-known algorithms designed for worst-case instances of these edge deletion problems

Local treewidth of random and noisy graphs with applications to stopping contagion in networks

We study the notion of local treewidth in sparse random graphs: the maximum treewidth over all $k$-vertex subgraphs of an $n$-vertex graph. When $k$ is not too large, we give nearly tight bounds for this local treewidth parameter; we also derive tight bounds for the local treewidth of noisy trees, trees where every non-edge is added independently with small probability. We apply our upper bounds on the local treewidth to obtain fixed parameter tractable algorithms (on random graphs and noisy trees) for edge-removal problems centered around containing a contagious process evolving over a network. In these problems, our main parameter of study is $k$, the number of "infected" vertices in the network. For a certain range of parameters the running time of our algorithms on $n$-vertex graphs is $2^{o(k)}\textrm{poly}(n)$, improving upon the $2^{\Omega(k)}\textrm{poly}(n)$ performance of the best-known algorithms designed for worst-case instances of these edge deletion problems

Expanding Graphs and Balanced Separators

Ένα γράφημα ονομάζεται εξαπλωτής αν είναι αραιό αλλά ταυτόχρονα έχει ισχυρές ιδιότητες συνεκτικότητας. Οι εξαπλωτές είναι μία κατηγορία γραφημάτων η οποία, κυρίως λόγω των πολλών εφαρμογών τους σε διαφορετικά πεδία των μαθηματικών, έχουν μελετηθεί εκτενώς. Ο στόχος αυτής της εργασίας είναι να αναλύσουμε τη σύνδεση των εξαπλωτών με άλλες έννοιες της θεωρίας γραφημάτων, και να μελετήσουμε τις δομές που μπορούμε να βρούμε σε αυτούς. Συγκεκριμένα, θα επικεντρωθούμε στους ισορροπημένους διαχωριστές και πώς αυτοί συνδέονται με τους εξαπλωτές. Επιπλέον θα δούμε πιο σύντομα, πώς οι ιδιοτιμές του πίνακα γειτνίασης ενός γραφήματος συνδέονται με την εξάπλωσή του αλλά και με άλλες ιδιότητές του. Τέλος, θα ασχοληθούμε ιδιαίτερα με τα ελάσσονα γραφήματα ενός εξαπλωτή.A graph is an expander if it is sparse and has strong connectivity properties. Expanders are widely studied graphs, mainly due to their numerous applications in many different mathematical fields. The purpose of this thesis is to analyze the connections between expanders and other notions of graph theory, and study their substructures. Specifically, we will focus on the connection of balanced separators and expanders and provide an introduction on how the expansion of a graph is connected to the eigenvalues of its adjacency matrix. We will also study in detail the minors one can find in expanders