Systemic Modeling of Agent Coaction: A Catalog of Decentralized Coordinating Processes

Taking inspiration from natural self-organizing systems is a successful strategy to solve computational problems in distributed systems. Faced with a particular problem, application designers have to identify an appropriate dynamical behavior and decide how to induce similar behavioral modes. In order to consolidate these ad-hoc activities to a systematic dynamical design method, we discuss and exemplify a behavioral modeling approach that describes the macroscopic behavior of agent-based software systems. This formalism is used to catalog the dynamic behavior of prominent examples of natural self-organizing systems. These here presented models represent generic, reusable templates for decentralized system adaptations that serve as analysis templates for application designs. A tailored programming model allows to supplement these templates in agent-based software applications with minimal intervention in the agent models

A Software Architecture for Computer Generated Forces in Complex Distributed Virtual Environments

Complex Distributed Virtual Environments (DVEs) present an outstanding opportunity for the Department of Defense to train geographically separated units within a single realistic threat environment with minimal logistical considerations or safety concerns. To increase the fidelity of these simulations, minimize cost, and thereby maximize the training potential, DVEs must be populated with a realistic number of Computer Generated Forces (CGFs). These are currently expensive to design and build due to a lack of standard COF architectures. A solution to this problem is presented in the form of a CGF Architecture that is applicable to CGFs that model any weapon system. Mapping techniques are discussed that take the architecture from generic templates to weapon system specific templates ready for implementation. An application based on this architecture, the Fuzzy Wingman, is discussed and its results are presented

Computational Resources to Filter Gravitational Wave Data with P-approximant Templates

The prior knowledge of the gravitational waveform from compact binary systems makes matched filtering an attractive detection strategy. This detection method involves the filtering of the detector output with a set of theoretical waveforms or templates. One of the most important factors in this strategy is knowing how many templates are needed in order to reduce the loss of possible signals. In this study we calculate the number of templates and computational power needed for a one-step search for gravitational waves from inspiralling binary systems. We build on previous works by firstly expanding the post-Newtonian waveforms to 2.5-PN order and secondly, for the first time, calculating the number of templates needed when using P-approximant waveforms. The analysis is carried out for the four main first-generation interferometers, LIGO, GEO600, VIRGO and TAMA. As well as template number, we also calculate the computational cost of generating banks of templates for filtering GW data. We carry out the calculations for two initial conditions. In the first case we assume a minimum individual mass of $1 M_{\odot}$ and in the second, we assume a minimum individual mass of $5 M_{\odot}$. We find that, in general, we need more P-approximant templates to carry out a search than if we use standard PN templates. This increase varies according to the order of PN-approximation, but can be as high as a factor of 3 and is explained by the smaller span of the P-approximant templates as we go to higher masses. The promising outcome is that for 2-PN templates the increase is small and is outweighed by the known robustness of the 2-PN P-approximant templates.Comment: 17 pages, 8 figures, Submitted to Class.Quant.Gra

An elliptical tiling method to generate a 2-dimensional set of templates for gravitational wave search

Searching for a signal depending on unknown parameters in a noisy background with matched filtering techniques always requires an analysis of the data with several templates in parallel in order to ensure a proper match between the filter and the real waveform. The key feature of such an implementation is the design of the filter bank which must be small to limit the computational cost while keeping the detection efficiency as high as possible. This paper presents a geometrical method which allows one to cover the corresponding physical parameter space by a set of ellipses, each of them being associated to a given template. After the description of the main characteristics of the algorithm, the method is applied in the field of gravitational wave (GW) data analysis, for the search of damped sine signals. Such waveforms are expected to be produced during the de-excitation phase of black holes -- the so-called 'ringdown' signals -- and are also encountered in some numerically computed supernova signals.Comment: Accepted in PR

Invariant template matching in systems with spatiotemporal coding: a vote for instability

We consider the design of a pattern recognition that matches templates to images, both of which are spatially sampled and encoded as temporal sequences. The image is subject to a combination of various perturbations. These include ones that can be modeled as parameterized uncertainties such as image blur, luminance, translation, and rotation as well as unmodeled ones. Biological and neural systems require that these perturbations be processed through a minimal number of channels by simple adaptation mechanisms. We found that the most suitable mathematical framework to meet this requirement is that of weakly attracting sets. This framework provides us with a normative and unifying solution to the pattern recognition problem. We analyze the consequences of its explicit implementation in neural systems. Several properties inherent to the systems designed in accordance with our normative mathematical argument coincide with known empirical facts. This is illustrated in mental rotation, visual search and blur/intensity adaptation. We demonstrate how our results can be applied to a range of practical problems in template matching and pattern recognition.Comment: 52 pages, 12 figure

Matched filtering of gravitational waves from inspiraling compact binaries: Computational cost and template placement

We estimate the number of templates, computational power, and storage required for a one-step matched filtering search for gravitational waves from inspiraling compact binaries. These estimates should serve as benchmarks for the evaluation of more sophisticated strategies such as hierarchical searches. We use waveform templates based on the second post-Newtonian approximation for binaries composed of nonspinning compact bodies in circular orbits. We present estimates for six noise curves: LIGO (three configurations), VIRGO, GEO600, and TAMA. To search for binaries with components more massive than 0.2M_o while losing no more than 10% of events due to coarseness of template spacing, initial LIGO will require about 1*10^11 flops (floating point operations per second) for data analysis to keep up with data acquisition. This is several times higher than estimated in previous work by Owen, in part because of the improved family of templates and in part because we use more realistic (higher) sampling rates. Enhanced LIGO, GEO600, and TAMA will require computational power similar to initial LIGO. Advanced LIGO will require 8*10^11 flops, and VIRGO will require 5*10^12 flops. If the templates are stored rather than generated as needed, storage requirements range from 1.5*10^11 real numbers for TAMA to 6*10^14 for VIRGO. We also sketch and discuss an algorithm for placing the templates in the parameter space.Comment: 15 pages, 4 figures, submitted to Phys. Rev.

Optimum Placement of Post-1PN GW Chirp Templates Made Simple at any Match Level via Tanaka-Tagoshi Coordinates

A simple recipe is given for constructing a maximally sparse regular lattice of spin-free post-1PN gravitational wave chirp templates subject to a given minimal match constraint, using Tanaka-Tagoshi coordinates.Comment: submitted to Phys. Rev.

Improving the efficiency of the detection of gravitational wave signals from inspiraling compact binaries: Chebyshev interpolation

Inspiraling compact binaries are promising sources of gravitational waves for ground and space-based laser interferometric detectors. The time-dependent signature of these sources in the detectors is a well-characterized function of a relatively small number of parameters; thus, the favored analysis technique makes use of matched filtering and maximum likelihood methods. Current analysis methodology samples the matched filter output at parameter values chosen so that the correlation between successive samples is 97% for which the filtered output is closely correlated. Here we describe a straightforward and practical way of using interpolation to take advantage of the correlation between the matched filter output associated with nearby points in the parameter space to significantly reduce the number of matched filter evaluations without sacrificing the efficiency with which real signals are recognized. Because the computational cost of the analysis is driven almost exclusively by the matched filter evaluations, this translates directly into an increase in computational efficiency, which in turn, translates into an increase in the size of the parameter space that can be analyzed and, thus, the science that can be accomplished with the data. As a demonstration we compare the present "dense sampling" analysis methodology with our proposed "interpolation" methodology, restricted to one dimension of the multi-dimensional analysis problem. We find that the interpolated search reduces by 25% the number of filter evaluations required by the dense search with 97% correlation to achieve the same efficiency of detection for an expected false alarm probability. Generalized to higher dimensional space of a generic binary including spins suggests an order of magnitude increase in computational efficiency.Comment: 23 pages, 5 figures, submitted to Phys. Rev.

Matched filters for coalescing binaries detection on massively parallel computers

We discuss some computational problems associated to matched filtering of experimental signals from gravitational wave interferometric detectors in a parallel-processing environment. We then specialize our discussion to the use of the APEmille and apeNEXT processors for this task. Finally, we accurately estimate the performance of an APEmille system on a computational load appropriate for the LIGO and VIRGO experiments, and extrapolate our results to apeNEXT.Comment: 19 pages, 6 figure