GPU-Accelerated Simulation of Maxwell’s Equations

Shor's algorithms for the integer factorization and the discrete logarithm problems can be regarded as a negative effect of the quantum mechanism on publickey cryptography. From the computational point of view, his algorithms illustrate that quantum computation could be more powerful. It is natural to consider that the power of quantum computation could be exploited to withstand even quantum adversaries. Over the last decade, quantum cryptography has been discussed and developed even from the computational complexity-theoretic point of view. In this paper, we will survey what has been studied in quantum computational cryptography.

The heat conduction equation is a combination of first-order and second-order differential equations. Solving first-order differential equations is necessary to examine temperature as a function of time. Meanwhile, solving second-order differential equations is needed to examine temperature as a function of space. The heat flux equation is based on Fourier's law, which shows that temperature is a function of time and space. Understanding heat conduction can be improved by building a heat propagation model on the Solar ERK dryer plate. Analysis of heat propagation on the drying plate used the Finite Difference Approach (FDA) method with explicit and implicit schemes. With an explicit scheme, the FDA method calculates the temperature (T) at a point on the spatial derivative term, when T is at time t, while the implicit scheme calculates T at a point on the space derivative term when T is at time t+Δt. Heat propagation at each time change was analyzed by developing a program using the MATLAB 17 application. The results of the analysis show that there are differences in heat propagation between the explicit and implicit schemes. The convergence and stability of calculations in explicit schemes are unstable, causing problems at the time step. Meanwhile, the implicit scheme is carried out simultaneously on all nodes so that convergence and stability are easily maintained, and there are no time-step limitations.

The Service Oriented Architecture using ISO Reference Model for Open Distributed Processing is a high performance technique for providing effective services to the users. This architecture consists of five different viewpoints namely Enterprise viewpoint, Computational viewpoint, Information viewpoint, Engineering viewpoint and Technology viewpoint. This paper discusses the details about the Computational viewpoint. Computational viewpoint defines the functional decomposition of the system into a set of services that interact at interfaces. These services can be found in a security system and present as classification based on the functionality of services. Interaction between the service requester and the security system, and the communication between the security system and the service provider is carried out through external messages. The security system receives an input message then processes it and produces an output message. The semantics of the message is the issue of information view point. If the security check fails or if the processing logic can’t be correctly applied, security services can raise exceptions signalling that the errors encountered. Exception message contain annotations and other meta-information

Higher-order symplectic integration techniques for molecular dynamics problems

This paper addresses a single-machine scheduling problem with nonresumable jobs and flexible maintenance activities (SJM) and its online version SJMO. It is showed that the competitive ratio of the classical list scheduling (LS) algorithm is 2 for SJMO, and it is the best possible polynomial time approximation algorithm for SJMO from both the competitive ratio point of view unless P = NP and the computational time complexity point of view. Based on the relationship between SJM and SJMO, it is showed that the LS algorithm is the best possible polynomial time approximation algorithm for SJM from both the worst-case ratio point of view unless P = NP and the computational time complexity point of view, which is a significant improvement of some of the existing results on SJM and its special case in the literature. Note that the worst-case ratio of the classical longest processing time first (LPT) algorithm is also 2 for SJM. In order to show which algorithm is better for SJM on average, numerical experiments are conducted. Computational results show that the LPT algorithm performs better than the LS algorithm in all combinations from an average-case error point of view.

Sudden total collapse of a dam holding back a reservoir of water, whenever it occurs, becomes formidably impressive in the extent of destruction with which it is associated. The movement on a dry bed of a two‐dimensional flood wave resulting from the break of a dam has been one of the most important and challenging subjects in rapidly varied unsteady flows from the computational point of view. An implicit time‐marching finite volume numerical scheme was developed and subsequently applied for the solution of the two‐dimensional unsteady open channel flow equations written in conservation form. In order to avoid the problems associated with a conventional grid system, a body‐fitted non‐orthogonal local co‐ordinate system was utilized. The proposed numerical technique was applied to determine the stage hydrographs, water surface profiles and velocities of flood flows resulting from suddenly breached storage dams. Predictions were compared with an analytical solution, with available numerical solutions using MacCormack's two‐step explicit scheme and with experimental measurements. Agreement between predictions and measurements regarding the wave front advancement and stage hydrographs is considered to be satisfactory.

The present work aims at comparing the performance of several quadratic programming (QP) solvers for simulating large-scale frictional rigid-body systems. Traditional time-stepping schemes for simulation of multibody systems are formulated as linear complementarity problems (LCPs) with copositive matrices. Such LCPs are generally solved by means of Lemke-type algorithms and solvers such as the PATH solver proved to be robust. However, for large systems, the PATH solver or any other pivotal algorithm becomes unpractical from a computational point of view. The convex relaxation proposed by one of the authors allows the formulation of the integration step as a QPD, for which a wide variety of state-of-the-art solvers are available. In what follows we report the results obtained solving that subproblem when using the QP solvers MOSEK, OOQP, TRON, and BLMVM. OOQP is presented with both the symmetric indefinite solver MA27 and our Cholesky reformulation using the CHOLMOD package. We investigate computational performance and address the correctness of the results from a modelling point of view. We conclude that the OOQP solver, particularly with the CHOLMOD linear algebra solver, has predictable performance and memory use patterns and is far more competitive for these problems than are the other solvers.

Elementary Unitary MO Transformations and SCF Theory

This volume has been inspired by the aim of gathering a number of theoretical papers that, though from different schools of inference—frequentist andBayesian, share the same interest towards studying complex statistical models. Indeed, both frequentist and Bayesian inference can entail various drawbacks, due to the complexity or misspecification of the model, or to the presence of many nuisance parameters. These difficulties may be overcome from a theoretical point of view through approximate likelihoods and scoring rules, and from a computational point of view through higher-order asymptotic expansions or computational tools from Bayesian inference. Specifically, the volume focuses on the interplay between Bayesian and frequentist inference in addressing these problems. The goal is to highlight and to disseminate some of the topics emerged in the international Workshop Recent advances in Statistical Inference: Theory and case studies, held in Padova, Italy, March 21–23, 2013. The Workshop has been a forum for the exchange of new ideas and thoughts on recent and ongoing research in both Bayesian methodology and modern likelihood inference. Although the topics covered in this volume are diverse, similar themes recur, as research ismostly fueled by the need to deal with complex models, for which traditional methods do not provide viable solutions. Among the topics presented we have Bayesian/frequentist challenges for categorical data analysis, Bayesian-frequentist sample size determination, integrated likelihood inference in semi parametric regression models, approximate Bayesian computation with modified log-likelihood ratios, theory and applications of proper scoring rules, quasi likelihood approximation of posterior distributions for likelihood-intractable complex models, mitigating multicollinearity with spike-and-slab priors, empirical Bayes methods in classical and Bayesian inference. While not exhaustive, this list should give a feeling of the issues discussed at the Workshop.

The electric potential created by a point source in a stratified model is usually written, in a spectral representation, in terms of a Hankel transform because of the cylindrical symmetry of the model. The solution in the radial wavenumber domain is called the kernel function. This kernel function, as a function of the depth coordinate, is the solution of a 1-D differential equation. The conventional procedure for the calculation of the kernel function consists in applying a recursive scheme. This procedure is effective from a computational point of view but becomes cumbersome from an analytical point of view, especially in the case of an arbitrary number of layers for arbitrary positions of the source and measurement points. I reformulate the problem of the kernel function by establishing the equivalence between the 1-D differential equation and a set of two boundary integral equations. This equivalence lowers the dimension of the problem by one unit so that the integration is performed over a space of dimension zero. The equations thus obtained are called jump summation equations. They are derived from a weighted product of two distinct models. The explicit form of these equations with the use of Green’s kernel (i.e., the kernel function for a homogeneous reference model) leads to the introduction of two basic representations, monopolar and dipolar. Each representation is related to a specific integral operator, but the basic representations are equivalent. The kernel function is computed by solving a linear system of equations. Our formulation is also well adapted to the inverse problem. The relationship between a perturbation of the model and the resulting perturbation of the kernel function is expressed by a Fréchet derivative. This sensitivity quantity is obtained by means of the jump summation equation, and its computation appears straightforward with the basic representations. An application to a novel evaluation of the depth of investigation for usual arrays is given.

The way that ciliates transform genes from their micronuclear to their macronuclear form is very interesting (and unique), particularly from a computational point of view. In this paper, we describe the model of gene assembly in ciliates presented in [2], [4], and [3]. Moreover, we prove that the set of three operations underlying this model is universal, in the sense that it suffices for gene assembly from any micronuclear pattern. We also prove that the set of simple versions of these operations is not universal — this fact is interesting from the experimental point of view.

The generation of random values corresponding to an underlying Gamma distribution is a key capability in many areas of knowledge, such as Probability and Statistics, Signal Processing, or Digital Communication, among others. Throughout history, different algorithms have been developed for the generation of such values and advances in computing have made them increasingly faster and more efficient from a computational point of view. These advances also allow the generation of higher-quality inputs (from the point of view of randomness and uniformity) for these algorithms that are easily tested by different statistical batteries such as NIST, Dieharder, or TestU01 among others. This article describes the existing algorithms for the generation of (independent and identically distributed—i.i.d.) Gamma distribution values as well as the theoretical and mathematical foundations that support their validity.

In this paper, we study the efficiency (both theoretically and computationally) of a class of valid inequalities for the minimum weighted elementary directed cycle problem (MWEDCP) in planar digraphs with negative weight elementary directed cycles. These valid inequalities are called cycle valid inequalities and are parametrized by an integer called inequality’s order. From a theoretical point of view, we prove that separating cycle valid inequalities of order 1 in planar digraph can be done in polynomial time. From a computational point of view, we present a cutting plane algorithm featuring the efficiency of a lifted form of the cycle valid inequalities of order 1. In addition to these lifted valid inequalities, our algorithm is also based on a mixed integer linear formulation of the MWEDCP. The computational results are carried out on randomly generated planar digraph instances of the MWEDCP. For all 29 instances considered, we obtain in average 26.47% gap improvement. Moreover, for some of our instances the strengthening process directly displays the optimal integer elementary directed cycle.

An extension of the loop representation of quantum gravity is studied. It has computational and mathematical advantages. From the computational point of view, it is simpler to find solutions of the constraints. From the mathematical point of view, the extended representation provides a new scenario to analyze the regularization problem in quantum gravity.

We consider the problem in which a set of products has to be shipped from a common origin to a common destination through one or several intermediate nodes with the objective of minimizing the sum of inventory and transportation costs when a set of possible shipping frequencies is given on each link. From the theoretical point of view, the main issue is the computation of the inventory cost in the intermediate nodes. From the computational point of view, given that the simpler single link problem is known to be NP-hard, we present four classes of heuristic algorithms. The first two classes are based on the decomposition of the sequence in links, the third class on the adaptation of the EOQ-type solution known for the continuous case, and the fourth on the optimal solution of a simpler problem through dynamic programming techniques. Finally, we compare them on a set of randomly generated problem instances. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 399–417, 1999