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Motivated by a property of linear resistive electrical networks, we introduce the class of Rayleigh matroids. These form a subclass of the balanced matroids defined by Feder and Mihail [9] in 1992. We prove a variety of results relating Rayleigh matroids to other well-known classes – in particular, we show that a binary matroid is Rayleigh if and only if it does not contain $\mathcal{S}_{8}$ as a minor. This has the consequence that a binary matroid is balanced if and only if it is Rayleigh, and provides the first complete proof in print that $\mathcal{S}_{8}$ is the only minor-minimal binary non-balanced matroid, as claimed in [9]. We also give an example of a balanced matroid which is not Rayleigh.
Bootstrap percolation on an arbitrary graph has a random initial configuration, where each vertex is occupied with probability $p$, independently of each other, and a deterministic spreading rule with a fixed parameter $k$: if a vacant site has at least $k$ occupied neighbours at a certain time step, then it becomes occupied in the next step. This process is well studied on ${\mathbb Z}^d$; here we investigate it on regular and general infinite trees and on non-amenable Cayley graphs. The critical probability is the infimum of those values of $p$ for which the process achieves complete occupation with positive probability. On trees we find the following discontinuity: if the branching number of a tree is strictly smaller than $k$, then the critical probability is 1, while it is $1-1/k$ on the $k$-ary tree. A related result is that in any rooted tree $T$ there is a way of erasing $k$ children of the root, together with all their descendants, and repeating this for all remaining children, and so on, such that the remaining tree $T'$ has branching number $\mbox{\rm br}(T')\leq \max\{\mbox{\rm br}(T)-k,\,0\}$. We also prove that on any $2k$-regular non-amenable graph, the critical probability for the $k$-rule is strictly positive.
A graph is $k$-linked if for every list of $2k$ vertices $\{s_1,{\ldots}\,s_k, t_1,{\ldots}\,t_k\}$, there exist internally disjoint paths $P_1,{\ldots}\, P_k$ such that each $P_i$ is an $s_i,t_i$-path. We consider degree conditions and connectivity conditions sufficient to force a graph to be $k$-linked.
Let $D(n,k)$ be the minimum positive integer $d$ such that every $n$-vertex graph with minimum degree at least $d$ is $k$-linked and let $R(n,k)$ be the minimum positive integer $r$ such that every $n$-vertex graph in which the sum of degrees of each pair of non-adjacent vertices is at least $r$ is $k$-linked. The main result of the paper is finding the exact values of $D(n,k)$ and $R(n,k)$ for every $n$ and $k$.
Thomas and Wollan [14] used the bound $D(n,k)\leq (n+3k)/2-2$ to give sufficient conditions for a graph to be $k$-linked in terms of connectivity. Our bound allows us to modify the Thomas–Wollan proof slightly to show that every $2k$-connected graph with average degree at least $12k$ is $k$-linked.
Let $p_c({\mathbb Q}_n)$ and $p_c({\mathbb Z}^n)$ denote the critical values for nearest-neighbour bond percolation on the $n$-cube ${\mathbb Q}_n = \{0,1\}^n$ and on ${\mathbb Z}^n$, respectively. Let $\Omega = n$ for ${\mathbb G} = {\mathbb Q}_n$ and $\Omega = 2n$ for ${\mathbb G} = {\mathbb Z}^n$ denote the degree of ${\mathbb G}$. We use the lace expansion to prove that for both ${\mathbb G} = {\mathbb Q}_n$ and ${\mathbb G} = {\mathbb Z}^n$, \[p_c({\mathbb G}) = \Omega^{-1} + \Omega^{-2} + \frac{7}{2} \Omega^{-3} + O(\Omega^{-4}).\] This extends by two terms the result $p_c({\mathbb Q}_n) = \Omega^{-1} + O(\Omega^{-2})$ of Borgs, Chayes, van der Hofstad, Slade and Spencer, and provides a simplified proof of a previous result of Hara and Slade for ${\mathbb Z}^n$.
We give results for the age-dependent distribution of vertex degree and number of vertices of given degree in the undirected web-graph process, a discrete random graph process introduced in [8]. For such processes we show that as $k \rightarrow \infty$, the expected proportion of vertices of degree $k$ has power law parameter $1+1/\eta$ where $\eta$ is the limiting ratio of the expected number of edge endpoints inserted by preferential attachment to the expected total degree. The proof for the undirected process generalizes naturally to give similar results for the directed hub-authority process, and an undirected hypergraph process.
We consider instances of the maximum independent set problem that are constructed according to the following semirandom model. Let $G_{n,p}$ be a random graph, and let $S$ be a set of $k$ vertices, chosen uniformly at random. Then, let $G_0$ be the graph obtained by deleting all edges connecting two vertices in $S$. Finally, an adversary may add edges to $G_0$ that do not connect two vertices in $S$, thereby producing the instance $G=G_{n,p,k}^*$. We present an algorithm that on input $G=G_{n,p,k}^*$ finds an independent set of size $\geq k$ within polynomial expected time, provided that $k\geq C(n/p)^{1/2}$ for a certain constant $C>0$. Moreover, we prove that in the case $k\leq (1-\varepsilon)\ln(n)/p$ this problem is hard.
We will study the best way to reveal a hidden perfect matching in a balanced bipartite graph by eliminating edges, one by one, in the hope that the eliminated edge is not part of the mystery perfect matching. We will look for the strategy that maximizes the odds of finding the perfect matching without revealing a fixed number of the edges in that perfect matching. For a complete bipartite graph, this is equivalent to finding a mystery permutation via negative guesses with only a fixed number of incorrect negative guesses.
We define ${\mathcal B}_n$ to be the set of $n$-tuples of the form $(a_0, {\ldots}\,, a_{n-1})$ where $a_j = \pm 1$. If $A \in {\mathcal B}_n$, then we call $A$ a binary sequence and define the autocorrelations of $A$ by $c_k := \sum_{j=0}^{n-k-1} a_j a_{j+k}$ for $0 \leq k \leq n-1$. The problem of finding binary sequences with autocorrelations ‘near zero’ has arisen in communications engineering and is also relevant to conjectures of Littlewood and Erdős on ‘flat’ polynomials with $\pm 1$ coefficients. Following Turyn, we define \[ b(n) := \min_{A \in {\mathcal B}_n} \max_{1 \leq k \leq n-1} |c_k|.\] The purpose of this article is to show that, using some known techniques from discrete probability, we can improve upon the best upper bound on $b(n)$ appearing in the previous literature, and we can obtain both asymptotic and exact expressions for the expected value of $c_k^m$ if the $a_j$ are independent $\pm 1$ random variables with mean 0. We also include some brief heuristic remarks in support of the unproved conjecture that $b(n) = O(\sqrt{n})$.
Motivated by a scheduling problem that arises in the study of optical networks, we prove the following result, which is a variation of a conjecture of Haxell, Wilfong and Winkler.
Let $k,n$ be two positive integers, let $w_{sj}, 1 \leq s \leq n, 1 \leq j \leq k$ be nonnegative reals satisfying $\sum_{j=1}^k w_{sj}< 1/n$ for every $1 \leq s \leq n$ and let $d_{sj}$ be arbitrary nonnegative reals. Then there are real numbers $x_1, x_2, {\ldots}\,,x_n$ such that for every $j$, $1 \leq j \leq k$, the $n$ cyclic closed intervals $I_s^{(j)}=[x_s+d_{sj},x_s+d_{sj}+w_{sj}]$, $(1 \leq s \leq n)$, where the endpoints are reduced modulo 1, are pairwise disjoint on the unit circle.
The proof is based on some properties of multivariate polynomials and on the validity of the Dyson conjecture.
We observe returns of a simple random walk on a finite graph to a fixed node, and would like to infer properties of the graph, in particular properties of the spectrum of the transition matrix. This is not possible in general, but at least the set of eigenvalues can be recovered under fairly general conditions, e.g., when the graph has a node-transitive automorphism group. The main result is that by observing polynomially many returns, it is possible to estimate the spectral gap of such a graph up to a constant factor.
The Turing machine is certainly the most powerful of the machines that we have considered and, in a sense, is the most powerful machine that we can consider. It is believed that every well-defined algorithm that people can be taught to perform or that can be performed by any computer can be performed on a Turing machine. This is essentially the statement made by Alonzo Church in 1936 and is known as Church's Thesis. This is not a theorem. It has not been mathematically proven. However, no one has found any reason for doubting it.
It is interesting that although the computer, as we know it, had not yet been invented when the Turing machine was created, the Turing machine contains the theory on which computers are based. Many students have been amazed to find that, using a Turing machine, they are actually writing computer programs. Thus computer programs preceded the computer.
We warn the reader in advance that if they look at different books on Turing machines, they will find the descriptions to be quite different. One author will state a certain property to be required of their machine. Another author will strictly prohibit the same property on their machine. Nevertheless, the machines, although different, have the same capabilities.
The Turing machine has an input alphabet Σ, a set of tape symbols, Γ containing Σ, and a set of states Q, similar to the automaton. The Turing machine has two special states, the start state s0 and the halt state h. When the machine reaches the halt state it shuts down. It also has a tape which is infinitely long on the right.
Sets form the foundation for mathematics. We shall define a set to be a well-defined collection of objects. This definition is similar to the one given by Georg Cantor, one of the pioneeers in the early development of set theory. The inadequacy of this definition became apparent when paradoxes or contradictions were discovered by the Italian logician Burali-Forti in 1879 and later by Bertrand Russell with the famous Russell paradox. It became obvious that sets had to be defined more carefully. Axiomatic systems have been developed for set theory to correct the problems discussed above and hopefully to avoid further contradictions and paradoxes. These systems include the Zermelo–Fraenkel–von Neumann system, the Gödel–Hilbert–Bernays system and the Russell–Whitehead system. In these systems the items that were allowed to be sets were restricted. Axioms were created to define sets. Any object which could not be created from these axioms was not allowed to be a set. These systems have been shown to be equivalent in the sense that if one system is consistent, then they all are. However, Gödel has shown that if the systems are consistent, it is impossible to prove that they are.
Definition 1.1An object in a set is called an element of the set or is said to belong to the set. If an object x is an element of a set A, this is denoted by x ∈ A. If an Objects in a set are called elements. Finite sets may be described by listing their elements.
Formal language theory is overlapped by a close relative among the family of mathematical disciplines. This is the specialty known as Combinatorics on Words. We must use a few of the most basic concepts and propositions of this field. A nonnull word, q, is said to be primitive if it cannot be expressed in the form xk with x a word and k > 1. Thus, for any alphabet containing the symbols a and b, each of the words a, b, ab, bab, and abababa is primitive. The words aa and ababab are not primitive and neither is any word in (aba)+ other than aba itself. One of the foundational facts of word combinatorics, which is demonstrated here in Section 6.2, is that each nonnull word, ω, consisting of symbols from an alphabet Σ, can be expressed in a unique way in the form ω = qn where q is a primitive word and n is a positive integer. The uniqueness of the representation, ω = qn, allows a useful display of the free semigroup Σ+, consisting of the nonnull words formed from symbols in Σ, in the form of a Cartesian product, Q × N, where Q is the set of all primitive words in Σ+ and N is the set of positive integers. Each word ω = qn is identified with the ordered pair (q, n). This chapter provides the groundwork for investigations of concepts that arise naturally in visualizing languages as subsets of Q × N. In the suggested visualizations, the order structure of N is respected. We regard N as labeling a vertical axis (y-axis) that extends upward only.
Living systems on our planet rely on the construction of long molecules by linking relatively small units into sequences where each pair of adjoining units is connected in a uniform manner. The units of polypeptides (proteins) are a set of twenty amino acids. These units are connected by the carboxyl group (COOH) of one unit being joined through the amino group (NH2) of the next unit, with a water molecule being deleted in the process. The units of RNA are a set of four ribonucleotides. These units are connected by the phosphate group (PO4 attached at the 5′ carbon) of one unit being joined through replacement of the hydroxyl group (OH attached at the 3′ carbon) of the next unit, with a water molecule being deleted in the process. The units of single stranded DNA are a set of four deoxyribonucleotides with the joining process as in the case of RNA.
Molecules lie in three-dimensional space, whereas words lie on a line. One may adopt the convention of listing the amino acids of a protein on a line with the free amino group on the left and the free carboxyl group on the right. For both single stranded RNA and DNA molecules one may adopt the convention of listing their units on a line with the phosphate at the left and the free hydroxyl group at the right. These conventions allow us to model (without ambiguity) these biopolymers as words over finite alphabets: a twenty letter alphabet of symbols that denote the twenty amino acids and two four letter alphabets of symbols denoting the four units for RNA and DNA, respectively.