Method for High Accuracy Multiplicity Correlation Measurements

Multiplicity correlation measurements provide insight into the dynamics of high energy collisions. Models describing these collisions need these correlation measurements to tune the strengths of the underlying QCD processes which influence all observables. Detectors, however, often possess limited coverage or reduced efficiency that influence correlation measurements in obscure ways. In this paper, the effects of non-uniform detection acceptance and efficiency on the measurement of multiplicity correlations between two distinct detector regions (termed forward-backward correlations) are derived. An analysis method with such effects built-in is developed and subsequently verified using different event generators. The resulting method accounts for acceptance and efficiency in a model independent manner with high accuracy thereby shedding light on the relative contributions of the underlying processes to particle production.Comment: 28 pages, 13 figures. Updated for having pseudorapidity dependent efficiency gradient

Pseudoparticle Multipole Method: A Simple Method to Implement High-Accuracy Treecode

In this letter we describe the pseudoparticle multipole method (P2M2), a new method to express multipole expansion by a distribution of pseudoparticles. We can use this distribution of particles to calculate high order terms in both the Barnes-Hut treecode and FMM. The primary advantage of P2M2 is that it works on GRAPE. GRAPE is a special-purpose hardware for the calculation of gravitational force between particles. Although the treecode has been implemented on GRAPE, we could handle terms only up to dipole, since GRAPE can calculate forces from point-mass particles only. Thus the calculation cost grows quickly when high accuracy is required. With P2M2, the multipole expansion is expressed by particles, and thus GRAPE can calculate high order terms. Using P2M2, we implemented an arbitrary-order treecode on GRAPE-4. Timing result shows GRAPE-4 accelerates the calculation by a factor between 10 (for low accuracy) to 150 (for high accuracy). Even on general-purpose programmable computers, our method offers the advantage that the mathematical formulae and therefore the actual program is much simpler than that of the direct implementation of multipole expansion.Comment: 6 pages, 4 figures, latex, submitted to ApJ Letter

A high-reproducibility and high-accuracy method for automated topic classification

Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requires algorithms that extract and record metadata on unstructured text documents. Assigning topics to documents will enable intelligent search, statistical characterization, and meaningful classification. Latent Dirichlet allocation (LDA) is the state-of-the-art in topic classification. Here, we perform a systematic theoretical and numerical analysis that demonstrates that current optimization techniques for LDA often yield results which are not accurate in inferring the most suitable model parameters. Adapting approaches for community detection in networks, we propose a new algorithm which displays high-reproducibility and high-accuracy, and also has high computational efficiency. We apply it to a large set of documents in the English Wikipedia and reveal its hierarchical structure. Our algorithm promises to make "big data" text analysis systems more reliable.Comment: 23 pages, 24 figure

Method of directing a laser beam with very high accuracy

System will collimate and direct an argon laser beam with high angular tracking accuracy at objects on the moons surface. It can be adapted to missile and satellite tracking

High resolution satellite imagery orientation accuracy assessment by leave-one-out method: accuracy index selection and accuracy uncertainty

The Leave-one-out cross-validation (LOOCV) was recently applied to the evaluation of High Resolution Satellite Imagery orientation accuracy and it has proven to be an effective method alternative with respect to the most common Hold-out-validation (HOV), in which ground points are split into two sets, Ground Control Points used for the orientation model estimation and Check Points used for the model accuracy assessment. On the contrary, the LOOCV applied to HRSI implies the iterative application of the orientationmodel using all the known ground points as GCPs except one, different in each iteration, used as a CP. In every iteration the residual between imagery derived coordinates with respect to CP coordinates (prediction error of the model on CP coordinates) is calculated; the overall spatial accuracy achievable from the oriented image may be estimated by computing the usual RMSE or, better, a robust accuracy index like the mAD (median Absolute Deviation) of prediction errors on all the iterations. In this way it is possible to overcome some drawbacks of the HOV: LOOCVis a reliable and robustmethod, not dependent on a particular set of CPs and on possible outliers, and it allows us to use each known ground point both as a GCP and as a CP, capitalising all the available ground information. This is a crucial problem in current situations, when the number of GCPs to be collected must be reduced as much as possible for obvious budget problems. The fundamentalmatter to deal with was to assess howwell LOOCVindexes (mADand RMSE) are able to represent the overall accuracy, that is howmuch they are stable and close to the corresponding HOV RMSE assumed as reference. Anyway, in the first tests the indexes comparison was performed in a qualitative way, neglecting their uncertainty. In this work the analysis has been refined on the basis of Monte Carlo simulations, starting from the actual accuracy of ground points and images coordinates, estimating the desired accuracy indexes (e.g. mAD and RMSE) in several trials, computing their uncertainty (standard deviation) and accounting for them in the comparison. Tests were performed on a QuickBird Basic image implementing an ad hoc procedure within the SISAR software developed by the Geodesy and Geomatics Team at the Sapienza University of Rome. The LOOCV method with accuracy evaluated by mAD seemed promising and useful for practical case

A method for high accuracy geo-referencing of data from field operations

In this project a Real Time Kinematic Global Position System (RTKGPS) was used to provide high accuracy field operation data. The deviations and errors of the RTKGPS when used in static and dynamic modes were studied as well as the accuracy of RTK GPS in eastern Denmark (55 40 N, 12 18 E) during a 24-hour test. The project introduced a novel real time data acquisition system and post-processing algorithms for improving positioning by merging RTKGPS data with vehicle altitude

Initial data for black hole-neutron star binaries: a flexible, high-accuracy spectral method

We present a new numerical scheme to solve the initial value problem for black hole-neutron star binaries. This method takes advantage of the flexibility and fast convergence of a multidomain spectral representation of the initial data to construct high-accuracy solutions at a relatively low computational cost. We provide convergence tests of the method for both isolated neutron stars and irrotational binaries. In the second case, we show that we can resolve the small inconsistencies that are part of the quasi-equilibrium formulation, and that these inconsistencies are significantly smaller than observed in previous works. The possibility of generating a wide variety of initial data is also demonstrated through two new configurations inspired by results from binary black holes. First, we show that choosing a modified Kerr-Schild conformal metric instead of a flat conformal metric allows for the construction of quasi-equilibrium binaries with a spinning black hole. Second, we construct binaries in low-eccentricity orbits, which are a better approximation to astrophysical binaries than quasi-equilibrium systems.Comment: 19 pages, 11 figures, Modified to match final PRD versio