Approximating quasi-stationary distributions with interacting reinforced random walks

We propose two numerical schemes for approximating quasi-stationary distributions (QSD) of finite state Markov chains with absorbing states. Both schemes are described in terms of interacting chains where the interaction is given in terms of the total time occupation measure of all particles in the system and has the impact of reinforcing transitions, in an appropriate fashion, to states where the collection of particles has spent more time. The schemes can be viewed as combining the key features of the two basic simulation-based methods for approximating QSD originating from the works of Fleming and Viot (1979) and Aldous, Flannery and Palacios (1998), respectively. The key difference between the two schemes studied here is that in the first method one starts with $a(n)$ particles at time $0$ and number of particles stays constant over time whereas in the second method we start with one particle and at most one particle is added at each time instant in such a manner that there are $a(n)$ particles at time $n$. We prove almost sure convergence to the unique QSD and establish Central Limit Theorems for the two schemes under the key assumption that $a(n)=o(n)$. Exploratory numerical results are presented to illustrate the performance.

Eigenvalue-Based Spectrum Sensing with Small Samples Using Circulant Matrix

In cognitive radio (CR) networks, eigenvalue-based detectors (EBDs) have attracted much attention due to their good performance of detecting secondary users (SUs). In order to further improve the detection performance of EBDs with short samples, we propose two new detectors: average circulant matrix-based Roy’s largest root test (ACM-RLRT) and average circulant matrix-based generalized likelihood ratio test (ACM-GLRT). In the proposed method, the circulant matrix of samples at each time instant from SUs is calculated, and then, the covariance matrix of the circulant matrix is averaged over a short period of time. The eigenvalues of the achieved average circulant matrix (ACM) are used to build our proposed detectors. Using a circulant matrix can improve the dominant eigenvalue of covariance matrix of signals and also the detection performance of EBDs even with short samples. The probability distribution functions of the detectors undernull hypothesis are analyzed, and the asymptotic expressions for the false-alarm and thresholds of two proposed detectors are derived, respectively. The simulation results verify the effectiveness of the proposed detectors.

Magnetized Dusty Black Holes and Wormholes

We consider the generalized Tolman solution of general relativity, describing the evolution of a spherical dust cloud in the presence of an external electric or magnetic field. The solution contains three arbitrary functions f(R), F(R) and τ0(R), where R is a radial coordinate in the comoving reference frame. The solution splits into three branches corresponding to hyperbolic (f>0), parabolic (f=0) and elliptic (f<0) types of motion. In such models, we study the possible existence of wormhole throats defined as spheres of minimum radius at a fixed time instant, and prove the existence of throats in the elliptic branch under certain conditions imposed on the arbitrary functions. It is further shown that the normal to a throat is a timelike vector (except for the instant of maximum expansion, when this vector is null), hence a throat is in general located in a T-region of space-time. Thus, if such a dust cloud is placed between two empty (Reissner–Nordström or Schwarzschild) space-time regions, the whole configuration is a black hole rather than a wormhole. However, dust clouds with throats can be inscribed into closed isotropic cosmological models filled with dust to form wormholes which exist for a finite period of time and experience expansion and contraction together with the corresponding cosmology. Explicit examples and numerical estimates are presented. The possible traversability of wormhole-like evolving dust layers is established by a numerical study of radial null geodesics.

On hybrid type of cathode attachment in high current vacuum arcs

This paper discusses the issues of a possible change of the type of cathode attachment of high-current vacuum arcs (HCVA) with an average cathode current density of more than 105 A/cm2. This type of HCVA is used as pumping plasma gun in experiments with plasma puff z-pinches. These experiments showed that the measured linear mass of the HCVA plasma jet is much higher (by a factor of 10 or more) than the expected mass, which can be obtained from the assumption that cathode attachment occurs only through a multitude of cathode spots emitting supersonic plasma jets. It is shown that in HCVA of the type under consideration, at some time instant there are two types of cathode attachments - cathode spots and thermionic erosion attachment (TEA). It can be said that HCVA of this type have a hybrid cathodic attachment. Unlike cathode spots, TEA produces a subsonic plasma flow, which contributes to an increase in the linear mass of the HCVA plasma jet.

Simulation of Rare Events in Stochastic Systems

The paper presents algorithms for simulation rare events in stochastic systems based on the theory of large deviations. Here, this approach is used in conjunction with the tools of optimal control theory to estimate the probability that some observed states in a stochastic system will exceed a given threshold by some upcoming time instant. Algorithms for obtaining controlled extremal trajectory (A-profile) of the system, along which the transition to a rare event (threshold) occurs most likely under the influence of disturbances that minimize the action functional, are presented. It is also shown how this minimization can be efficiently performed using numerical-analytical methods of optimal control for linear and nonlinear systems. These results are illustrated by an example for a precipitation-measured monsoon intraseasonal oscillation (MISO) described by a low-order nonlinear stochastic model.

Analysing Temporal Evolution of Complex Data Using Similarity Queries

Regardless of the data domain, there are applications that must track the temporal evolution of data elements. Based on the instances present in the database, the goal is to estimate the state of a given element at a different time instant from those available in the database. This kind of task is common in many database application domains, such as medicine, meteorology, agriculture, financial, and others. In content-based retrieval with complex data (such as images, sounds and videos), data are usually represented in metric spaces, where only the distances between elements are available. Without dimensional coordinates, it is not possible simply to add a time dimension for trajectory estimation in these spaces, as is the case in multidimensional spaces. In this article we propose to map the metric data to a multidimensional space so that we can estimate the element’s status at a given time instant, based on known states of the same element. As it is not possible to create the complex data equivalent to its estimated position in mapped space, we propose to apply similarity queries using this position as query center. Then, we estimate how this element would be, retrieving the real data elements present in the database that are close to the estimate. In this article, in addition to the nearest neighbor query (k-NN), we propose to use two other queries: kAndRange and kAndRev. With both methods, we aim to prune non-relevant elements from the query results, retrieving only the elements that are really close to the estimates. We present experiments with different query scenarios, evaluating the effects of varying input parameters of the proposed queries.

On the Existence of XOR-Based Codes for Private Information Retrieval with Private Side Information

We consider the problem of Private Information Retrieval with Private Side Information (PIR-PSI), wherein the privacy of the demand and the side information are jointly preserved. Although the capacity of the PIR-PSI setting is known, we observe that the underlying capacity-achieving code construction uses Maximum Distance Separable (MDS) codes therefore contributing to high computational complexity when retrieving the demand. Pointing at this drawback of MDS-based PIR-PSI codes, we propose XOR-based PIR-PSI codes for a simple yet non-trivial setting of two non-colluding databases and two side information files at the user. Although our codes offer substantial reduction in complexity when compared to MDS-based codes, the code-rate marginally falls short of the capacity of the PIR-PSI setting. Nevertheless, we show that our code-rate is strictly higher than that of XOR-based codes for PIR with no side information. As a result, our codes can be useful when privately downloading a file especially after having downloaded a few other messages privately from the same database at an earlier time-instant.

Pseudospectral Roaming Contour Integral Methods for Convection-Diffusion Equations

We generalize ideas in the recent literature and develop new ones in order to propose a general class of contour integral methods for linear convection–diffusion PDEs and in particular for those arising in finance. These methods aim to provide a numerical approximation of the solution by computing its inverse Laplace transform. The choice of the integration contour is determined by the computation of a few suitably weighted pseudo-spectral level sets of the leading operator of the equation. Parabolic and hyperbolic profiles proposed in the literature are investigated and compared to the elliptic contour originally proposed by Guglielmi, López-Fernández and Nino 2020, see Guglielmi et al. (Math Comput 89:1161–1191, 2020). In summary, the article provides a comparison among three different integration profiles; proposes a new fast pseudospectral roaming method; optimizes the selection of time windows on which one may arbitrarily approximate the solution by no extra computational cost with respect to the case of a fixed time instant; focuses extensively on computational aspects and it is the reference of the MATLAB code [20], where all algorithms described here are implemented.

A method for constructing an optimal control strategy in a linear terminal problem

This paper deals with an optimal control problem for a linear discrete system subject to unknown bounded disturbances, where the control goal is to steer the system with guarantees into a given terminal set while minimising the terminal cost function. We define an optimal control strategy which takes into account the state of the system at one future time instant and propose an efficient numerical method for its construction. The results of numerical experiments show an improvement in performance under the optimal control strategy in comparison to the optimal open-loop worst-case control while maintaining comparable computation times.