An edge flipping is a non-reversible Markov chain on a given connected graph, as defined in Chung and Graham (2012). In the same paper, edge flipping eigenvalues and stationary distributions for some classes of graphs were identified. We further study edge flipping spectral properties to show a lower bound for the rate of convergence in the case of regular graphs. Moreover, we show by a coupling argument that a cutoff occurs at $\frac{1}{4} n \log n$ for the edge flipping on the complete graph.

Stein’s method is used to study discrete representations of multidimensional distributions that arise as approximations of states of quantum harmonic oscillators. These representations model how quantum effects result from the interaction of finitely many classical ‘worlds’, with the role of sample size played by the number of worlds. Each approximation arises as the ground state of a Hamiltonian involving a particular interworld potential function. Our approach, framed in terms of spherical coordinates, provides the rate of convergence of the discrete approximation to the ground state in terms of Wasserstein distance. Applying a novel Stein’s method technique to the radial component of the ground state solution, the fastest rate of convergence to the ground state is found to occur in three dimensions.

We prove some estimates for the variations of transition probabilities of the (1+1)-affine process. From these estimates we deduce the strong Feller and the ergodic properties of the total variation distance of the process. The key strategy is the pathwise construction and analysis of several Markov couplings using strong solutions of stochastic equations.

We establish exponential ergodicity for a class of Markov processes with interactions, including two-factor type processes and Gruschin type processes. The proof is elementary and direct via the Markov coupling technique.

This paper presents a novel decoupling technique for two-element multiple-in multiple-out (MIMO) antennas for smartwatch applications with floating metallic bezel. The radiating elements consist of embedded loop-type ground-radiation antennas and operate at the 2.45 GHz Bluetooth/Wi-Fi bands. An isolator, consisting of a loop-type structure with a lumped capacitor, is attached externally to the ground plane such that wideband isolation between the antennas has been achieved. It is demonstrated that the small-sized isolator is coupled with the large-sized bezel surrounding the ground plane, where the bezel operates as a low-Q decoupler between the antenna elements producing wideband isolation property. Accordingly, optimized results can be obtained by controlling the location of the isolator, the gap between the isolator and the bezel, and the loaded capacitor. Simulation and measured results have been presented to validate the design performance. The measured −10 dB impedance bandwidth of both antenna elements is more than 210 MHz, whereas the isolation bandwidth is 770 MHz with reference to 20 dB. The envelop correlation coefficient is <0.1 in the operating band. Furthermore, the proposed technique is versatile regardless of the angular separation of the antenna elements on the circular ground plane, which makes it a good candidate for smartwatch MIMO applications in practical scenarios.

Let ${\mathbb{G}(n_1,n_2,m)}$ be a uniformly random m-edge subgraph of the complete bipartite graph ${K_{n_1,n_2}}$ with bipartition $(V_1, V_2)$ , where $n_i = |V_i|$ , $i=1,2$ . Given a real number $p \in [0,1]$ such that $d_1 \,{:\!=}\, pn_2$ and $d_2 \,{:\!=}\, pn_1$ are integers, let $\mathbb{R}(n_1,n_2,p)$ be a random subgraph of ${K_{n_1,n_2}}$ with every vertex $v \in V_i$ of degree $d_i$ , $i = 1, 2$ . In this paper we determine sufficient conditions on $n_1,n_2,p$ and m under which one can embed ${\mathbb{G}(n_1,n_2,m)}$ into $\mathbb{R}(n_1,n_2,p)$ and vice versa with probability tending to 1. In particular, in the balanced case $n_1=n_2$ , we show that if $p\gg\log n/n$ and $1 - p \gg \left(\log n/n \right)^{1/4}$ , then for some $m\sim pn^2$ , asymptotically almost surely one can embed ${\mathbb{G}(n_1,n_2,m)}$ into $\mathbb{R}(n_1,n_2,p)$ , while for $p\gg\left(\log^{3} n/n\right)^{1/4}$ and $1-p\gg\log n/n$ the opposite embedding holds. As an extension, we confirm the Kim–Vu Sandwich Conjecture for degrees growing faster than $(n \log n)^{3/4}$ .

Mixing rates, relaxation rates, and decay of correlations for dynamics defined by potentials with summable variations are well understood, but little is known for non-summable variations. This paper exhibits upper bounds for these quantities for dynamics defined by potentials with square-summable variations. We obtain these bounds as corollaries of a new block coupling inequality between pairs of dynamics starting with different histories. As applications of our results, we prove a new weak invariance principle and a Hoeffding-type inequality.

Embodiment is typically given insufficient weight in debates concerning the moral status of Novel Synthetic Beings (NSBs) such as sentient or sapient Artificial Intelligences (AIs). Discussion usually turns on whether AIs are conscious or self-aware, but this does not exhaust what is morally relevant. Since moral agency encompasses what a being wants to do, the means by which it enacts choices in the world is a feature of such agency. In determining the moral status of NSBs and our obligations to them, therefore, we must consider how their corporeality shapes their options, preferences, values, and is constitutive of their moral universe. Analysing AI embodiment and the coupling between cognition and world, the paper shows why determination of moral status is only sensible in terms of the whole being, rather than mental sophistication alone, and why failure to do this leads to an impoverished account of our obligations to such NSBs.

We analyze average-based distributed algorithms relying on simple and pairwise random interactions among a large and unknown number of anonymous agents. This allows the characterization of global properties emerging from these local interactions. Agents start with an initial integer value, and at each interaction keep the average integer part of both values as their new value. The convergence occurs when, with high probability, all the agents possess the same value, which means that they all know a property of the global system. Using a well-chosen stochastic coupling, we improve upon existing results by providing explicit and tight bounds on the convergence time. We apply these general results to both the proportion problem and the system size problem.

In the design of long fibre reinforced thermoplastic (LFT) structures, there is a direct dependency on the manufacturing. Therefore, it is indispensable to integrate the manufacturing influences into the design process. This not only offers new opportunities for material- and load-adapted designs, but also reduces cost-intensive modifications in later stages. The goal of this contribution is to make the complexity manageable by presenting a method which couples LFT manufacturing and structural simulations in an automated optimization loop. Herein, the influence of linear-elastic, local anisotropic material properties as well as residual stresses resulting from the compression molding of LFT on the stiffness-optimized design of beaded plates is investigated. Based on the simulation studies in this contribution, it can be summarized that the resulting bead height and flank angle, considering anisotropies and residual stresses, are smaller compared to isotropic modelling. As a conclusion, the strength constraint limits the maximum bead height and the flank angle needs to be additionally chosen as a consequence of the local fibre orientations and residual stresses resulting from manufacturing. Optimized bead cross sections are only valid for a specific system under investigation, as they depend on the defined boundary conditions (load case, initial charge geometry and position, fibre orientations, etc.).

A uniform recursive tree on n vertices is a random tree where each possible $(n-1)!$ labelled recursive rooted tree is selected with equal probability. We introduce and study weighted trees, a non-uniform recursive tree model departing from the recently introduced Hoppe trees. This class generalizes both uniform recursive trees and Hoppe trees, providing diversity among the nodes and making the model more flexible for applications. We analyse the number of leaves, the height, the depth, the number of branches, and the size of the largest branch in these weighted trees.

In this paper we integrate two strands of the literature on stability of general state Markov chains: conventional, total-variation-based results and more recent order-theoretic results. First we introduce a complete metric over Borel probability measures based on ‘partial’ stochastic dominance. We then show that many conventional results framed in the setting of total variation distance have natural generalizations to the partially ordered setting when this metric is adopted.

We prove existence and uniqueness of a stationary distribution and absolute regularity for nonlinear GARCH and INGARCH models of order (p, q). In contrast to previous work we impose, besides a geometric drift condition, only a semi-contractive condition which allows us to include models which would be ruled out by a fully contractive condition. This results in a subgeometric rather than the more usual geometric decay rate of the mixing coefficients. The proofs are heavily based on a coupling of two versions of the processes.

We examine a system of interacting random walks with leftward drift on ℤ, which begins with a single active particle at the origin and some distribution of inactive particles on the positive integers. Inactive particles become activated when landed on by other particles, and all particles beginning at the same point possess equal leftward drift. Once activated, the trajectories of distinct particles are independent. This system belongs to a broader class of problems involving interacting random walks on rooted graphs, referred to collectively as the frog model. Additional conditions that we impose on our model include that the number of frogs (i.e. particles) at positive integer points is a sequence of independent random variables which is increasing in terms of the standard stochastic order, and that the sequence of leftward drifts associated with frogs originating at these points is decreasing. Our results include sharp conditions with respect to the sequence of random variables and the sequence of drifts that determine whether the model is transient (meaning the probability infinitely many frogs return to the origin is 0) or nontransient. We consider several, more specific, versions of the model described, and a cleaner, more simplified set of sharp conditions will be established for each case.

Let (Mn,Sn)n≥0 be a Markov random walk with positive recurrent driving chain (Mn)n≥0 on the countable state space 𝒮 with stationary distribution π. Suppose also that lim supn→∞Sn=∞ almost surely, so that the walk has almost-sure finite strictly ascending ladder epochs σn>. Recurrence properties of the ladder chain (Mσn>)n≥0 and a closely related excursion chain are studied. We give a necessary and sufficient condition for the recurrence of (Mσn>)n≥0 and further show that this chain is positive recurrent with stationary distribution π> and 𝔼π>σ1><∞ if and only if an associated Markov random walk (𝑀̂n,𝑆̂n)n≥0, obtained by time reversal and called the dual of (Mn,Sn)n≥0, is positive divergent, i.e. 𝑆̂n→∞ almost surely. Simple expressions for π> are also provided. Our arguments make use of coupling, Palm duality theory, and Wiener‒Hopf factorization for Markov random walks with discrete driving chain.

We consider a Markov chain of point processes such that each state is a superposition of an independent cluster process with the previous state as its centre process together with some independent noise process and a thinned version of the previous state. The model extends earlier work by Felsenstein (1975) and Shimatani (2010) describing a reproducing population. We discuss when closed-form expressions of the first- and second-order moments are available for a given state. In a special case it is known that the pair correlation function for these type of point processes converges as the Markov chain progresses, but it has not been shown whether the Markov chain has an equilibrium distribution with this, particular, pair correlation function and how it may be constructed. Assuming the same reproducing system, we construct an equilibrium distribution by a coupling argument.

The transfer operator corresponding to a uniformly expanding map enjoys good spectral properties. We verify that coupling yields explicit estimates that depend continuously on the expansion and distortion constants of the map. For non-uniformly expanding maps with a uniformly expanding induced map, we obtain explicit estimates for mixing rates (exponential, stretched exponential, polynomial) that again depend continuously on the constants for the induced map together with data associated with the inducing time. Finally, for non-uniformly hyperbolic transformations, we obtain the corresponding estimates for rates of decay of correlations.