Random preorders and alignments

A preorder consists of linearly ordered equivalence classes called blocks, and an alignment is a sequence of cycles. We investigate the block structure of a preorder chosen uniformly at random among all preorders on n elements, and also the distribution of cycles in a random alignment chosen uniformly at random among all alignments on n elements, as n→∞.     

The probability thatn random points in a triangle are in convex position

We show thatn random points chosen independently and uniformly from a triangle are in convex position with probability $$\frac{{2^n (3n - 3)!}}{{((n - 1)!)^3 (2n)!}}$$ .     

A concentration bound for the longest increasing subsequence of a randomly chosen involution

In this short note we prove a concentration result for the length of the longest increasing subsequence (LIS) of a randomly and uniformly chosen involution of {1,…,s}.     

Precision of neural timing: The small ? limit

We explore the precision of neural timing in a model neural system with n identical input neurons whose firing time in response to stimulation is chosen from a density f. These input neurons stimulate a target cell which fires when it receives m hits within ? msec. We prove that the density of the firing time of the target cell converges as ?→0 to the input density f raised to the mth and normalized. We give conditions for convergence of the density in L¹, pointwise, and uniformly as well as conditions for the convergence of the standard deviations.     

Extractors for binary elliptic curves

We propose a simple and efficient deterministic extractor for an ordinary elliptic curve E, defined over $\mathbb{F}_{2^n}$ , where n = 2? and ? is a positive integer. Our extractor, for a given point P on E, outputs the first ${\mathbb{F}}_{2^\ell}$ -coefficient of the abscissa of the point P. We also propose a deterministic extractor for the main subgroup G of E, where E has minimal 2-torsion. We show that if a point P is chosen uniformly at random in G, the bits extracted from the point P are indistinguishable from a uniformly random bit-string of length ?.     

An algorithm for finding hamilton cycles in random directed graphs

We describe a polynomial (O(n^1.5)) time algorithm DHAM for finding hamilton cycles in digraphs. For digraphs chosen uniformly at random from the set of digraphs with vertex set {1, 2, …, n} and m = m(n) edges the limiting probability (as n → ∞) that DHAM finds a hamilton cycle equals the limiting probability that the digraph is hamiltonian. Some applications to random “travelling salesman problems” are discussed.     

Random Tight Frames

We introduce probabilistic frames to study finite frames whose elements are chosen at random. While finite tight frames generalize orthonormal bases by allowing redundancy, independent, uniformly distributed points on the sphere approximately form a finite unit norm tight frame (FUNTF). In the present paper, we develop probabilistic versions of tight frames and FUNTFs to significantly weaken the requirements on the random choice of points to obtain an approximate finite tight frame. Namely, points can be chosen from any probabilistic tight frame, they do not have to be identically distributed, nor have unit norm. We also observe that classes of random matrices used in compressed sensing are induced by probabilistic tight frames.     

Complexity of Linear Problems with a Fixed Output Basis

We use an information-based complexity approach to study the complexity of approximation of linear operators. We assume that the values of a linear operator may be elements of an infinite dimensional space G. It seems reasonable to look for an approximation as a linear combination of some elements g_i from the space G and compute only the coefficients c_i of this linear combination. We study the case when the elements g_i are fixed and compare it with the case where the g_i can be chosen arbitrarily. We show examples of linear problems where a significant output data compression is possible by the use of a nonlinear algorithm, and this nonlinear algorithm is much better than all linear algorithms. We also provide an example of a linear problem for which one piece of information is enough whereas an optimal (minimal cost) algorithm must use information of much higher cardinality.     

Identities for primal Menger algebras

This note gives a small set of identities for the primal unitary Menger algebra with n elements. It treats the constants uniformly.     

Defence resource distribution between protection and decoys for constant resource stockpiling pace

The paper considers the optimal resource distribution between increasing protection of genuine elements and deploying decoys (false targets) in a situation when the attacker's and defender's resources are stockpiling and the resource increment rate is constant. It is assumed that the system must perform within an exogenously given time horizon and the attack time probability is uniformly distributed over this horizon. Series and parallel systems are considered. The defender optimizes the resource distribution in order to minimize the system vulnerability. The attacker cannot distinguish genuine and false elements and can attack a randomly chosen subset of the elements.     

Monotonicity and complex convexity in Banach lattices

The goal of this article is to study the relations among monotonicity properties of real Banach lattices and the corresponding convexity properties in the complex Banach lattices. We introduce the moduli of monotonicity of Banach lattices. We show that a Banach lattice E is uniformly monotone if and only if its complexification EC is uniformly complex convex. We also prove that a uniformly monotone Banach lattice has finite cotype. In particular, we show that a Banach lattice is of cotype q for some 2?q<∞ if and only if there is an equivalent lattice norm under which it is uniformly monotone and its complexification is q-uniformly PL-convex. We also show that a real Köthe function space E is strictly (respectively uniformly) monotone and a complex Banach space X is strictly (respectively uniformly) complex convex if and only if Köthe-Bochner function space E(X) is strictly (respectively uniformly) complex convex.     

Root statistics of random polynomials with bounded Mahler measure

The Mahler measure of a polynomial is a measure of complexity formed by taking the modulus of the leading coefficient times the modulus of the product of its roots outside the unit circle. The roots of a real degree N polynomial chosen uniformly from the set of polynomials of Mahler measure at most 1 yield a Pfaffian point process on the complex plane. When N is large, with probability tending to 1, the roots tend to the unit circle, and we investigate the asymptotics of the scaled kernel in a neighborhood of a point on the unit circle. When this point is away from the real axis (on which there is a positive probability of finding a root) the scaled process degenerates to a determinantal point process with the same local statistics (i.e.   scalar kernel) as the limiting process formed from the roots of complex polynomials chosen uniformly from the set of polynomials of Mahler measure at most 1. Three new matrix kernels appear in a neighborhood of ±1 which encode information about the correlations between real roots, between complex roots and between real and complex roots. Away from the unit circle, the kernels converge to new limiting kernels, which imply among other things that the expected number of roots in any open subset of C$\mathbb{C}$ disjoint from the unit circle converges to a positive number. We also give ensembles with identical statistics drawn from two-dimensional electrostatics with potential theoretic weights, and normal matrices chosen with regard to their topological entropy as actions on Euclidean space.     

Expected length of the longest common subsequence for large alphabets

We consider the length L of the longest common subsequence of two randomly uniformly and independently chosen n character words over a k-ary alphabet. Subadditivity arguments yield that E[L]/n converges to a constant γ_k. We prove a conjecture of Sankoff and Mainville from the early 1980s claiming that as k→∞.     

Probability thatn random points are in convex position

We show thatn random points chosen independently and uniformly from a parallelogram are in convex position with probability $$\left( {\frac{{\left( {\begin{array}{*{20}c} {2n - 2} \\ {n - 1} \\ \end{array} } \right)}}{{n!}}} \right)^2 $$ . A finite set of points in the plane is calledconvex if its points are vertices of a convex polygon. In this paper we show the following results:     

Sharp estimates and a central limit theorem for the invariant law for a large star-shaped loss network

Calls arrive in a Poisson stream on a symmetric network constituted of N links of capacity C. Each call requires one channel on each of L distinct links chosen uniformly at random; if none of these links is full, the call is accepted and holds one channel per link for an exponential duration, else it is lost. The invariant law for the route occupation process has a semi-explicit expression similar to that for a Gibbs measure: it involves a combinatorial normalizing factor, the partition function, which is very difficult to evaluate. We study the large N limit while keeping the arrival rate per link fixed. We use the Laplace asymptotic method. We obtain the sharp asymptotics of the partition function, then the central limit theorem for the empirical measure of the occupancies of the links under the invariant law. We also obtain a sharp version for the large deviation principle proved in Graham and O'Connell (Ann. Appl. Probab. 10 (2000) 104).     

Continuity of the Asymptotics of Expected Zeros of Fewnomials

In “Random complex fewnomials, I,” the limiting formula of the (normalized) expected distribution of complex zeros of a system of k random m-variate fewnomials where the coefficients are taken from the \({\mathrm {SU}}(m+1)\) ensemble and the spectra are chosen uniformly at random is determined. We recall this result and show the limiting formula is a (k, k)-form with continuous coefficients.     

Stabilization of a Class of Uncertain Systems

We consider the problem to synthesize a stabilizing control u synthesis for systems \(\frac{{dx}}{{dt}} = Ax + Bu\) where A ∈ ?^n×n and B ∈ ?^n×m, while the elements α_i,j(·) of the matrix A are uniformly bounded nonanticipatory functionals of arbitrary nature. If the system is continuous, then the elements of the matrix B are continuous and uniformly bounded functionals as well. If the system is pulse-modulated, then the elements of the matrix B are differentiable uniformly bounded functions of time. It is assumed that k isolated uniformly bounded elements \({\alpha _{{i_l},{j_l}}}\left( \cdot \right)\) satisfying the condition \(\mathop {\inf }\limits_{\left( \cdot \right)} \left| {{\alpha _{{i_l},{j_l}}}\left( \cdot \right)} \right|{\alpha _ - } > 0,\quad l \in \overline {1,k}\) are located above the main diagonal of the matrix A(·), where G _k is the set of all isolated elements of the system, J₁ is the set of indices of rows of matrix A(·) containing isolated elements, and J₂ is the set of indices of its rows free of isolated elements. It is assumed that other elements located above the main diagonal are sufficiently small provided that their row indices belong to J₁, i.e., \(\mathop {\sup }\limits_{\left( \cdot \right)} \left| {{\alpha _{i,j}}\left( \cdot \right)} \right| < \delta ,\quad {\alpha _{i,j}} \notin {G_k},\quad i \in {J_1},\quad j > i\). All other elements located above the main diagonal are uniformly bounded. The relation u = S(·)x is satisfied in the continuous case, while the relation u = ξ(t) is satisfied in the pulse-modulated case; here the components of the vector ξ are outputs of synchronous pulse elements. Constructing a special quadratic Lyapunov function, one can determine a matrix S(·) such that the closed system becomes globally exponentially stable in the continuous case. In the pulse-modulated case, input pulses are synthesized such that the system becomes globally asymptotically stable.     

On distribution of the norm for normal random elements in the space of continuous functions

We consider distributions of norms for normal random elements X in separable Banach spaces, in particular, in the space C(S) of continuous functions on a compact space S. We prove that, under some nondegeneracy condition, the functions $ {{\mathcal{F}}_X}=\left\{ {\mathrm{P}\left( {\left\| {X-z} \right\|\leqslant r} \right):\;z\in C(S)} \right\},\;r\geqslant 0 $ , are uniformly Lipschitz and that every separable Banach space B can be ε-renormed so that the family $ {{\mathcal{F}}_X} $ becomes uniformly Lipschitz in the new norm for any B-valued nondegenerate normal random element X.     

Adjunction of unity and invertible elements in uniformly locally a-convex algebras

We show by a counter example that the adjunction of unity is not always possible for the class of uniformly locallyA-convex algebras contrary to Cochran's affirmation and we characterize uniformly locallyA-convex algebras for which this adjunction is possible. We also exhibit examples of complete uniformly locallyA-convex algebras which do not satify properties of Banach algebras.     

Connected permutation graphs

A permutation graph is a simple graph associated with a permutation. Let c_n be the number of connected permutation graphs on n vertices. Then the sequence {c_n} satisfies an interesting recurrence relation such that it provides partitions of n! as . We also see that, if uniformly chosen at random, asymptotically almost all permutation graphs are connected.