We consider the number of occurrences of subwords (non-consecutive sub-sequences) in a given word. We first define the notion of subword entropy of a given word that measures the maximal number of occurrences among all possible subwords. We then give upper and lower bounds of minimal subword entropy for words of fixed length in a fixed alphabet, and also showing that minimal subword entropy per letter has a limit value. A better upper bound of minimal subword entropy for a binary alphabet is then given by looking at certain families of periodic words. We also give some conjectures based on experimental observations.

We show that the number of minimal deterministic finite automata with n+1 states recognizing a finite binary language grows asymptotically for n → ∞ like Θ(n! 8ⁿ e^{3 a₁ n^{1/3}} n^{7/8}), where a₁ ≈ -2.338 is the largest root of the Airy function. For this purpose, we use a new asymptotic enumeration method proposed by the same authors in a recent preprint (2019). We first derive a new two-parameter recurrence relation for the number of such automata up to a given size. Using this result, we prove by induction tight bounds that are sufficiently accurate for large n to determine the asymptotic form using adapted Netwon polygons.

One of the central topics in the theory of random graphs deals with the phase transition in the order of the largest components. In the binomial random graph $\mathcal{G}(n,p)$, the threshold for the appearance of the unique largest component (also known as the giant component) is $p_g = n^{-1}$. More precisely, when $p$ changes from $(1-\varepsilon)p_g$ (subcritical case) to $p_g$ and then to $(1+\varepsilon)p_g$ (supercritical case) for $\varepsilon>0$, with high probability the order of the largest component increases smoothly from $O(\varepsilon^{-2}\log(\varepsilon^3 n))$ to $\Theta(n^{2/3})$ and then to $(1 \pm o(1)) 2 \varepsilon n$. Furthermore, in the supercritical case, with high probability the largest components except the giant component are trees of order $O(\varepsilon^{-2}\log(\varepsilon^3 n))$, exhibiting a structural symmetry between the subcritical random graph and the graph obtained from the supercritical random graph by deleting its giant component. As a natural generalization of random graphs and connectedness, we consider the binomial random $k$-uniform hypergraph $\mathcal{H}^k(n,p)$ (where each $k$-tuple of vertices is present as a hyperedge with probability $p$ independently) and the following notion of high-order connectedness. Given an integer $1 \leq j \leq k-1$, two sets of $j$ vertices are called $j$-connected if there is a walk of hyperedges between them such that any two consecutive hyperedges intersect in at least $j$ vertices. A $j$-connected component is a maximal collection of pairwise $j$-connected $j$-tuples of vertices. Recently, the threshold for the appearance of the giant $j$-connected component in $\mathcal{H}^k(n,p)$ and its order were determined. In this article, we take a closer look at the subcritical random hypergraph. We determine the structure, order, and size of the largest $j$-connected components, with the help of a certain class of “hypertrees” and related objects. In our proofs, we combine various probabilistic and enumerative techniques, such as generating functions and couplings with branching processes. Our study will pave the way to establishing a symmetry between the subcritical random hypergraph and the hypergraph obtained from the supercritical random hypergraph by deleting its giant $j$-connected component.

While volunteer computing, as a restricted model of parallel computing, has proved itself to be a successful paradigm of scientific computing with excellent benefit on cost efficiency and public outreach, many problems it solves are intrinsically highly parallel. However, many efficient algorithms, including backtracking search, take the form of a tree search on an extremely uneven tree that cannot be easily parallelized efficiently in the volunteer computing paradigm. We explore in this article how to perform such searches efficiently on volunteer computing projects. We propose a parallel tree search scheme, and we describe two examples of its real-world implementation, Harmonious Tree and Odd Weird Search, both carried out at the volunteer computing project yoyo@home. To confirm the observed efficiency of our scheme, we perform a mathematical analysis, which proves that, under reasonable assumption that agrees with experimental observation, our scheme is only a constant multiplicative factor away from perfect parallelism. Details on improving the overall performance are also discussed.