Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters

Data analysis in science, e.g., high-energy particle physics, is often subject to an intractable likelihood if the observables and observations span a high-dimensional input space. Typically the problem is solved by reducing the dimensionality using feature engineering and histograms, whereby the latter technique allows to build the likelihood using Poisson statistics. However, in the presence of systematic uncertainties represented by nuisance parameters in the likelihood, the optimal dimensionality reduction with a minimal loss of information about the parameters of interest is not known. This work presents a novel strategy to construct the dimensionality reduction with neural networks for feature engineering and a differential formulation of histograms so that the full workflow can be optimized with the result of the statistical inference, e.g., the variance of a parameter of interest, as objective. We discuss how this approach results in an estimate of the parameters of interest that is close to optimal and the applicability of the technique is demonstrated with a simple example based on pseudo-experiments and a more complex example from high-energy particle physics

A Semantic Map for Evaluating Creativity

We present a semantic map of words related with creativity. The aim is to empirically derive terms which can be used to rate processes or products of computational creativity. The words in the map are based on association studies performed by human subjects and augmented with words derived from the literature (based on human raters). The words are used in a card sorting study to investigate the way they are categorized by human subjects. The results are arranged in a heat map of word relations based on a hierarchical cluster analysis. The cluster analysis and a principal component analysis provide a set of five to six clusters of items related to each other, and as clusters related to creativity. These clusters could form a basis for scales used to rate aspects of computational creativity

Performance Evaluation of Four Field-Scale Agricultural Drainage Denitrification Bioreactors in Iowa

Recently, interest in denitrification bioreactors to reduce the amount of nitrate in agricultural drainage has led to increased installations across the U.S. Midwest. Despite this recent attention, there are few peer-reviewed, field-scale comparative performance studies investigating the effectiveness of these denitrification bioreactors. The object of this work was to analyze nitrate removal performance from four existing bioreactors in Iowa, paying particular attention to potential performance-affecting factors including retention time, influent nitrate concentration, temperature, flow rate, age, length-to-width ratio, and cross-sectional shape. Based on a minimum of two years of water quality data from each of the four bioreactors, annual removal rates ranged from 0.38 to 7.76 g N m-3 bioreactor volume d-1. Bioreactor and total (including bypass flow) nitrate-nitrogen load reductions ranged from 12% to 76% (mean 45%) and from 12% to 57% (mean 32%), respectively, removing from 0.5 to 15.5 kg N ha-1 drainage area. Multiple regression analyses showed that temperature and influent nitrate concentration were the most important factors affecting percent bioreactor nitrate load reduction and nitrate removal rate, respectively. This analysis also indicated that load reductions within the bioreactor were significantly impacted by retention time at three of the four reactors. More field-scale performance data from bioreactors of different designs and from multiple locations around the Midwest are necessary to further enhance understanding of nitrate removal in these systems and their potential to positively impact water quality

Adaptive Technomythography: The Apotheosis Of Machine And Development Of Legend In A System Of Dynamic Technology

Human beings will effectively deify any suitably complex system that cannot be explained through basic haptic interaction. Our culture loves technology. These days it seems we need it to feel whole. In an effort to explore the development of mythology and modular aesthetic in a technological age I have designed and constructed a number of interactive robotic \u27organisms\u27 to engage in arbitrary movement in geometric enclosures. Through observation and dialog I seek to assess the extent to which people assign human characteristics to the random and oft times aberrant mechanical behavior. To supplement this endeavor, a fictional astrological system that proposes logical (albeit mythological) explanations for the peculiarities in these relationships has been created

Time Optimal Control in Spin Systems

In this paper, we study the design of pulse sequences for NMR spectroscopy as a problem of time optimal control of the unitary propagator. Radio frequency pulses are used in coherent spectroscopy to implement a unitary transfer of state. Pulse sequences that accomplish a desired transfer should be as short as possible in order to minimize the effects of relaxation and to optimize the sensitivity of the experiments. Here, we give an analytical characterization of such time optimal pulse sequences applicable to coherence transfer experiments in multiple-spin systems. We have adopted a general mathematical formulation, and present many of our results in this setting, mindful of the fact that new structures in optimal pulse design are constantly arising. Moreover, the general proofs are no more difficult than the specific problems of current interest. From a general control theory perspective, the problems we want to study have the following character. Suppose we are given a controllable right invariant system on a compact Lie group, what is the minimum time required to steer the system from some initial point to a specified final point? In NMR spectroscopy and quantum computing, this translates to, what is the minimum time required to produce a unitary propagator? We also give an analytical characterization of maximum achievable transfer in a given time for the two spin system.Comment: 20 Pages, 3 figure