2,866 research outputs found

    Probabilistic abductive logic programming using Dirichlet priors

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    Probabilistic programming is an area of research that aims to develop general inference algorithms for probabilistic models expressed as probabilistic programs whose execution corresponds to inferring the parameters of those models. In this paper, we introduce a probabilistic programming language (PPL) based on abductive logic programming for performing inference in probabilistic models involving categorical distributions with Dirichlet priors. We encode these models as abductive logic programs enriched with probabilistic definitions and queries, and show how to execute and compile them to boolean formulas. Using the latter, we perform generalized inference using one of two proposed Markov Chain Monte Carlo (MCMC) sampling algorithms: an adaptation of uncollapsed Gibbs sampling from related work and a novel collapsed Gibbs sampling (CGS). We show that CGS converges faster than the uncollapsed version on a latent Dirichlet allocation (LDA) task using synthetic data. On similar data, we compare our PPL with LDA-specific algorithms and other PPLs. We find that all methods, except one, perform similarly and that the more expressive the PPL, the slower it is. We illustrate applications of our PPL on real data in two variants of LDA models (Seed and Cluster LDA), and in the repeated insertion model (RIM). In the latter, our PPL yields similar conclusions to inference with EM for Mallows models

    Neutrons from 9Be/alpha,n/ reaction for E alpha between 6 and 10 MeV

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    Neutron energy spectra measured as function of neutron emission angle and ion bombardment energ

    Transparent modelling of finite stochastic processes for multiple agents

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    Stochastic Processes are ubiquitous, from automated engineering, through financial markets, to space exploration. These systems are typically highly dynamic, unpredictable and resistant to analytic methods; coupled with a need to orchestrate long control sequences which are both highly complex and uncertain. This report examines some existing single- and multi-agent modelling frameworks, details their strengths and weaknesses, and uses the experience to identify some fundamental tenets of good practice in modelling stochastic processes. It goes on to develop a new family of frameworks based on these tenets, which can model single- and multi-agent domains with equal clarity and flexibility, while remaining close enough to the existing frameworks that existing analytic and learning tools can be applied with little or no adaption. Some simple and larger examples illustrate the similarities and differences of this approach, and a discussion of the challenges inherent in developing more flexible tools to exploit these new frameworks concludes matters

    Some Observations on Triplet Ground-States in the Context of ‘Topological’ (HLPM) Ring-Currents in Conjugated Systems

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    When the quasi graph-theoretical HĂŒckel–London–Pople–McWeeny (HLPM) approach is used to calculate ‘topological’ π-electron ring-currents and bond-currents in conjugated hydrocarbons, a problem is identified that occurs whenever application of the Aufbau process gives rise to a π-electronic ground-state configuration that is a triplet. This circumstance seems to occur only occasionally and, even when it does, the generally somewhat outrĂ© molecular graphs in question appear unlikely to represent extant or viable conjugated systems. The molecular graphs of four examples are used to illustrate this ‘triplet ground-state problem’, only one of which represents a hydrocarbon that has actually been synthesised. It is pointed out that the ‘triplet ground-state problem’ does constitute an intrinsic limitation of the HLPM approach. It is, though, a limitation that is also necessarily inherent in other equivalent (though ostensibly different) methods of calculating magnetic properties due to π-electron ring-currents — methods that are likewise founded on the HĂŒckel molecular-orbital conventions. When a triplet ground-state arises, topological ring-currents and bond-currents cannot be calculated by the HLPM method and its equivalents. Infinite paramagnetism is formally to be predicted in such situations. This work is licensed under a Creative Commons Attribution 4.0 International License

    A C-13(alpha,n)O-16 calibration source for KamLAND

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    We report on the construction and performance of a calibration source for KamLAND using the reaction C-13(alpha,n)O-16 with Po-210 as the alpha progenitor. The source provides a direct measurement of this background reaction in our detector, high energy calibration points for the detector energy scale, and data on quenching of the neutron visible energy in KamLAND scintillator. We also discuss the possibility of using the reaction C-13(alpha,n)O-16 as a source of tagged slow neutrons.Comment: 6 pages, 4 figures. Revised to agree with the published tex
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