A partial breadth-first execution model for prolog

MEM (Multipath Execution Model) is a novel model for the execution of Prolog programs which combines a depth-first and breadth-first exploration of the search tree. The breadth-first search allows more than one path of the SLD-tree to be explored at the same time. In this way, the computational cost of traversing the whole search tree associated to a program can be decreased because the MEM model reduces the overhead due to the execution of control instructions and also diminishes the number of unifications to be performed. This paper focuses on the description of the MEM model and its sequential implementation. Moreover, the MEM execution model can be implemented in order to exploit a new kind of parallelism, called path parallelism, which allows the parallel execution of unify operations related to simultaneously traversed pathsPeer ReviewedPostprint (published version

Maximum-entropy image reconstruction using wavelets

Wavelet functions allow the sparse and efficient representation of a signal at different scales. Recently the application of wavelets to the denoising of maps of cosmic microwave background (CMB) fluctuations has been proposed. The maximum-entropy method (MEM) is also often used for enhancing astronomical images and has been applied to CMB data. In this paper, we give a systematic discussion of combining these two approaches by the use of the MEM in wavelet bases for the denoising and deconvolution of CMB maps and more general images. Certain types of wavelet transforms, such as the a trous transform, can be viewed as a multi-channel intrinsic correlation function (ICF). We find that the wavelet MEM has lower reconstruction residuals than conventional pixel-basis MEM in the case when the signal-to-noise ratio is low and the point spread function narrow. Furthermore, the Bayesian evidence for the wavelet MEM reconstructions is generally higher for a wide range of images. From a Bayesian point of view, the wavelet basis thus provides a better model of the image.Comment: 21 pages, 20 figures, submitted to MNRA

Maximum Entropy Analysis of the Spectral Functions in Lattice QCD

First principle calculation of the QCD spectral functions (SPFs) based on the lattice QCD simulations is reviewed. Special emphasis is placed on the Bayesian inference theory and the Maximum Entropy Method (MEM), which is a useful tool to extract SPFs from the imaginary-time correlation functions numerically obtained by the Monte Carlo method. Three important aspects of MEM are (i) it does not require a priori assumptions or parametrizations of SPFs, (ii) for given data, a unique solution is obtained if it exists, and (iii) the statistical significance of the solution can be quantitatively analyzed. The ability of MEM is explicitly demonstrated by using mock data as well as lattice QCD data. When applied to lattice data, MEM correctly reproduces the low-energy resonances and shows the existence of high-energy continuum in hadronic correlation functions. This opens up various possibilities for studying hadronic properties in QCD beyond the conventional way of analyzing the lattice data. Future problems to be studied by MEM in lattice QCD are also summarized.Comment: 51 pages, 17 figures, typos corrected, discussions on the boundary conditions and renormalization constants added. To appear in Progress in Particle and Nuclear Physics, Vol.4

Charge density study with the Maximum Entropy Method on model data of silicon. A search for non-nuclear attractors

1990 Sakata and Sato applied the maximum entropy method (MEM) to a set of structure factors measured earlier by Saka and Kato with the Pendellösung method. They found the presence of non-nuclear attractors, i.e., maxima in the density between two bonded atoms. We applied the MEM to a limited set of Fourier data calculated from a known electron density distribution (EDD) of silicon. The EDD of silicon was calculated with the program ADF-BAND. This program performs electronic structure calculations, including periodicity, based on the density functional theory of Hohenberg and Kohn. No non-nuclear attractor between two bonded silicon atoms was observed in this density. Structure factors were calculated from this density and the same set of structure factors that was measured by Saka and Kato was used in the MEM analysis. The EDD obtained with the MEM shows the same non-nuclear attractors that were later obtained by Sakata and Sato. This means that the non-nuclear attractors in silicon are really an artefact of the MEM

CPN−1^{N-1} model with the theta term and maximum entropy method

A $\theta$ term in lattice field theory causes the sign problem in Monte Carlo simulations. This problem can be circumvented by Fourier-transforming the topological charge distribution $P(Q)$. This strategy, however, has a limitation, because errors of $P(Q)$ prevent one from calculating the partition function ${\cal Z}(\theta)$ properly for large volumes. This is called flattening. As an alternative approach to the Fourier method, we utilize the maximum entropy method (MEM) to calculate ${\cal Z}(\theta)$. We apply the MEM to Monte Carlo data of the CP$^3$ model. It is found that in the non-flattening case, the result of the MEM agrees with that of the Fourier transform, while in the flattening case, the MEM gives smooth ${\cal Z}(\theta)$.Comment: Talk presented at Lattice2004(topology), Fermilab, June 21-26, 2004; 3 pages, 3 figure

Meteoroid Engineering Model (MEM) 3: NASAs Newest Meteoroid Model

Meteoroid impacts threaten spacecraft and astronauts at all locations within the Solar System. At certain altitudes in low-Earth orbit, orbital debris dominates the risk, but meteoroids are more significant within 250 km of the Earths surface and above 4000 km [1]. In interplanetary space, orbital debris is nonexistent and meteoroids constitute the entire population of potentially dangerous impactors. The NASA Meteoroid Environment Office (MEO) produces the Meteoroid Engineering Model (MEM) to support meteoroid impact risk assessments [2]; MEM is a stand-alone piece of software that describes the flux, speed, directionality, and bulk density of meteoroids striking a spacecraft on a user-supplied trajectory. The MEO released version 3 of MEM in 2019 [3]. This proceeding describes the orbital populations that form the core of MEM, highlights key differences between MEM 3 and its predecessors, discusses the implications of these changes for spacecraft, summarizes our validation against meteor and in-situ data, and delineates the models limitations

Comparative study of an Eden model for the irreversible growth of spins and the equilibrium Ising model

The Magnetic Eden Model (MEM) with ferromagnetic interactions between nearest-neighbor spins is studied in $(d+1)-$dimensional rectangular geometries for $d = 1,2$. In the MEM, magnetic clusters are grown by adding spins at the boundaries of the clusters. The orientation of the added spins depends on both the energetic interaction with already deposited spins and the temperature, through a Boltzmann factor. A numerical Monte Carlo investigation of the MEM has been performed and the results of the simulations have been analyzed using finite-size scaling arguments. As in the case of the Ising model, the MEM in $d = 1$ is non-critical (only exhibits an ordered phase at $T= 0$). In $d = 2$ the MEM exhibits an order-disorder transition of second-order at a finite temperature. Such transition has been characterized in detail and the relevant critical exponents have been determined. These exponents are in agreement (within error bars) with those of the Ising model in 2 dimensions. Further similarities between both models have been found by evaluating the probability distribution of the order parameter, the magnetization and the susceptibility. Results obtained by means of extensive computer simulations allow us to put forward a conjecture which establishes a nontrivial correspondence between the MEM for the irreversible growth of spins and the equilibrium Ising model. This conjecture is certainly a theoretical challenge and its confirmation will contribute to the development of a framework for the study of irreversible growth processes.Comment: 21 pages, 11 figure

On the Photometric Accuracy of RHESSI Imaging and Spectrosocopy

We compare the photometric accuracy of spectra and images in flares observed with the Ramaty High Energy Solar Spectroscopic Imager (RHESSI)}spacecraft. We test the accuracy of the photometry by comparing the photon fluxes obtained in different energy ranges from the spectral-fitting software SPEX with those fluxes contained in the images reconstructed with the Clean, MEM, MEM-Vis, Pixon, and Forward-fit algorithms. We quantify also the background fluxes, the fidelity of source geometries, and spatial spectra reconstructed with the five image reconstruction algorithms. We investigate the effects of grid selection, pixel size, field-of-view, and time intervals on the quality of image reconstruction. The detailed parameters and statistics are provided in an accompanying CD-ROM and web page. We find that Forward-fit, Pixon, and Clean have a robust convergence behavior and a photometric accuracy in the order of a few percents, while MEM does not converge optimally for large degrees of freedom (for large field-of-views and/or small pixel sizes), and MEM-Vis suffers in the case of time-variable sources. This comparative study documents the current status of the RHESSI spectral and imaging software, one year after launch.Comment: 2 Figures, full version on http://www.lmsal.com/~aschwand/eprints/2003_photo/index.htm